Global Land One-kilometer Base Elevation (GLOBE)
UNITED STATES DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
NATIONAL ENVIRONMENTAL SATELLITE, DATA, AND INFORMATION SERVICE
National Geophysical Data Center
Boulder, Colorado 80305-3328
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Key to Geophysical Records Documentation No. 34
May 1999
This document was edited for NGDC
email addresses and URLs on
April 1, 2008
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Front Cover
Upper Image: Color image showing the GLOBE digital elevation model. Black
denotes areas flagged as ocean in GLOBE.
Lower Image: Shaded-relief image of southern and eastern Asia. Earthquake
depths are shown in purple (shallow earthquakes) and pink (deeper earthquakes).
Nighttime lights (from NOAA’s archive of Defense Meteorological Satellite Program
imagery) is shown in greens (less intense) and yellows (most intense). The nighttime
lights are primarily settled areas, plus industrial features such as gas flares in
petroleum fields.
Back Cover
GLOBE data come from eighteen combinations of source/lineage, described in
Section 5A. This summary map shows the distributions of data by these sources/
lineages.
Global Land One-kilometer Base Elevation (GLOBE)
Digital Elevation Model, Version 1.0
Documentation Version 1.0
Edited by
David A. Hastings
Paula K. Dunbar
for the GLOBE Task Team of the Committee on Earth Observation Satellites
NGDC Key to Geophysical Records Documentation No. 34
May 1999
UNITED STATES DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
NATIONAL ENVIRONMENTAL SATELLITE, DATA, AND INFORMATION SERVICE
National Geophysical Data Center
Boulder, Colorado 80305-3328
AcrB538.pdf 4/1/2008 11:14:27 AM
Global Land One-kilometer Base Elevation
ii
Disclaimer
While every effort has been made to ensure that these data are accurate and reliable within the limits of the
current state of the art, NOAA cannot assume liability for any damages caused by any inaccuracies in the
data or as a result of the failure of the data to function on a particular system. NOAA makes no warranty,
expressed or implied, nor does the fact of distribution constitute such a warranty. The user must be cautious
when using these data. None of the data represented here are perfect. As in many complex scientific endeavors,
error can be expected.
Trademark Acknowledgments
In this documentation for the Global Land One-kilometer Base Elevation (GLOBE), trademarked commercial
products and companies are named. Mention of a commercial company or product does not imply endorsement
by NOAA or the Department of Commerce. Use for publicity or advertising purposes of information from
this publication concerning proprietary products or the test of such products is not authorized. Throughout
the publication, rather than put a trademark symbol in every occurrence of a trademarked name, we state that
we are using the names only in an editorial fashion with no intention of infringement of the trademark.
Publication Citation
The Global Land One-kilometer Base Elevation (GLOBE) was developed on behalf of the GLOBE Task
Team, created by the Committee on Earth Observation Satellites (CEOS), Working Group on Information
Systems and Services (WGISS), Data Subgroup (DS). GLOBE also coordinates with the International
Geosphere-Biosphere Programme’s Data and Information System, and International Society of
Photogrammetry and Remote Sensing (ISPRS) Working Group IV/6 on Global Databases in Support of
Environmental Monitoring. The data base citation is found on page 8. The documentation manual should be
cited as follows:
Hastings, David A., and Paula K. Dunbar, 1999. Global Land One-kilometer Base Elevation
(GLOBE) Digital Elevation Model, Documentation, Volume 1.0. Key to Geophysical Records
Documentation (KGRD) 34. National Oceanic and Atmospheric Administration, National
Geophysical Data Center, 325 Broadway, Boulder, Colorado 80303, U.S.A.
Documentation Version 1.0
iii
Contents
1. Executive Summary.......................................................................................................... 1
2. Introduction ...................................................................................................................... 4
2.A. What GLOBE Is ..................................................................................................... 4
2.B. A Brief History of GLOBE..................................................................................... 5
2.C. Major Collaborators in GLOBE ............................................................................. 6
2.D. Contributions Invited for Future Enhancements to GLOBE .................................. 7
3. Citation of GLOBE and Copyright Information ............................................................... 8
3.A. Citation of GLOBE................................................................................................. 8
3.B. Copyright and Redistribution Information.............................................................. 9
4. General Characteristics of GLOBE ................................................................................ 10
5. Data Set Development .................................................................................................... 11
5.A. DEM Sources and Processing............................................................................... 11
5.A.i. Digital Terrain Elevation Data (DTED) ....................................................... 13
5.A.i.a. Source Characteristics......................................................................... 14
5.A.i.b. Derivation of the 30" DEM from Source Materials ............................ 15
5.A.i.c. Extracts from Prototype NIMA Documentation of DTED Level 0 .... 18
5.A.i.d. Characteristics of 30" DEMs from DTED .......................................... 19
5.A.ii. DEM for Australia ...................................................................................... 37
5.A.iii. DEM for Japan........................................................................................... 41
5.A.iv. DEM for Italy ............................................................................................. 42
5.A.v. DEM for New Zealand ................................................................................ 44
5.A.vi. DEM for Greenland.................................................................................... 45
5.A.vii. Digital Chart of the World......................................................................... 48
5.A.viii. Maps for Parts of Asia and South America.............................................. 51
5.A.ix. Maps for Part of Brazil............................................................................... 53
5.A.x. Map for Part of Peru .................................................................................... 54
5.A.xi. Antarctic Digital Database ......................................................................... 55
5.B. Assembly of GLOBE Version 1.0......................................................................... 56
5.B.i. Quality Assessment ...................................................................................... 58
5.B.i.a. Japan.................................................................................................... 58
5.B.i.b. Italy ..................................................................................................... 58
5.B.i.c. Australia .............................................................................................. 59
5.B.i.d. Greenland ............................................................................................ 59
5.B.i.e. Antarctica ............................................................................................ 60
5.B.i.f. Conterminous United States and Vicinity ............................................ 60
5.B.i.g. DTED within 50° of the Equator......................................................... 61
5.B.i.h. DTED Poleward of 50° North and South Latitudes ............................ 61
5.B.i.i. DCW vs. Other Cartographic Sources ................................................. 62
5.B.ii. Global Data Set Assembly .......................................................................... 62
Global Land One-kilometer Base Elevation
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5.B.iii. Georeferencing of GLOBE ........................................................................ 64
5.B.iv. Comparison of GLOBE with Other Available DEMs ................................ 64
5.B.v. GLOBE’s Development as Additional DEMs Are Created ......................... 65
6. Imperfections in Digital Elevation Data ......................................................................... 66
6.A. Grid Spacing and Resolution................................................................................ 66
6.B. Topographic Detail and Accuracy ........................................................................ 67
6.C. Production Artifacts.............................................................................................. 68
7. Accuracy......................................................................................................................... 69
7.A. Horizontal Accuracy............................................................................................. 69
7.A.i. Data from Raster Data Sources .................................................................... 69
7.A.ii. Data from Cartographic Sources ................................................................. 70
7.B. Vertical Accuracy ................................................................................................. 70
7.B.i. Absolute Accuracy: Data from Raster Sources ............................................ 70
7.B.ii. Absolute Accuracy: Data from Cartographic Sources ................................ 71
7.B.iii. Relative Accuracy ...................................................................................... 72
7.B.iv. Summary: How to Use These Assessments ................................................ 73
7.C. Additional Accuracy Assessments by Peer Reviewers ......................................... 74
7.D. Additional Comments on Accuracy ..................................................................... 75
8. Visualizations of GLOBE and Ancillary Data................................................................ 76
8.A. Visualizations of GLOBE ..................................................................................... 76
8.B. Ancillary Data....................................................................................................... 76
8.B.i. Source/Lineage File (with Contained Ocean Mask)..................................... 76
8.B.ii. Slope and Aspect Data (Why Aren’t They Provided?) ............................... 77
9. Upcoming Improvements ............................................................................................... 78
9.A. Integration with Other Data.................................................................................. 78
9.B. Additional Contributions of Land Elevation Data ................................................ 78
10. Data Distribution .......................................................................................................... 79
11. Data Format and Importing GLOBE Data .................................................................... 80
11.A. Data and Source File-Naming Convention ......................................................... 80
11.B. Metadata File-Naming Convention and Directory Structure .............................. 81
11.C. Elevation Data File Sizes, Regional Extent, and Statistics ................................. 82
11.D. Digital Elevation Data File Format..................................................................... 82
11.E. Source/Lineage Map ........................................................................................... 84
11.F. Header Files and Associated Files ....................................................................... 85
11.F.i. Information about GeoVu Headers and Associated Files ............................ 85
11.F.ii. Information about Idrisi Headers and Associated Files.............................. 87
11.F.iii. Information about GRASS Headers and Associated Files ........................ 88
11.F.iv. Information about Arc/INFO (and ArcView) Headers, Associated Files .. 88
11.G. Obtaining and Importing GLOBE Data .............................................................. 89
11.G.i. Obtaining the Data ..................................................................................... 89
11.G.ii. GUNZIP the Compressed Data from the Web Site ................................... 89
11.G.iii. Which Computer Are You Using? ........................................................... 90
11.G.iv. Importing into NGDC’s GeoVu ................................................................ 90
11.G.iv.a. Accessing GLOBE Data on the CD-ROM ...................................... 90
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11.G.iv.b. Accessing GLOBE Data Obtained from the GLOBE Web Site ...... 91
11.G.v. Importing into Clark University’s Idrisi..................................................... 92
11.G.vi. Importing into the U.S. Army Corps of Engineers’ GRASS .................... 92
11.G.vi.a. Importing GLOBE Data Using a Sample GRASS Data Base ......... 93
11.G.vi.b. Importing GLOBE Data into Your Own GRASS Data Base .......... 94
11.G.vii. Importing into ERDAS............................................................................ 94
11.G.viii. Importing into ESRI’s Arc/INFO ........................................................... 95
11.G.ix. Importing into ESRI’s ArcView ............................................................... 96
11.G.x. Importing into Adobe Photoshop .............................................................. 97
11.G.xi. Importing into Other Software Packages.................................................. 98
11.H. Projection Information........................................................................................ 98
11.I. Georeferencing in GLOBE................................................................................... 98
12. Disclaimers ................................................................................................................... 99
13. References .................................................................................................................. 102
Appendix A. Participants in the GLOBE Project and Acknowledgments........................ 108
Appendix B. Glossary of Acronyms ................................................................................. 112
Appendix C. Federal Geographic Data Committee Metadata, and Global Change Master
Directory .DIF for GLOBE ........................................................................................ 114
Index ................................................................................................................................. 134
Documentation Version 1.0
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1. Executive Summary
This is the first version of documentation for the Global Land One-kilometer Base Elevation (GLOBE)
data set. GLOBE is an internationally designed, developed, and independently peer-reviewed global
digital elevation model (DEM), at a latitude-longitude grid spacing of 30 arc-seconds (30"). This
report describes the history of the GLOBE project, the candidate data sets, data compilation techniques,
organization, and use of the data base. The data are available on CD-ROM and the World Wide Web.
The previous standards for global digital elevation models (DEMs) are ETOPO5 (NGDC, 1988) and
TerrainBase (Row and Hastings, 1994; Row and others, 1995), which were at 5 arc-minute (5')
gridding. Higher resolution DEMs exist for parts of the world (Gittings, 1997). However, when
GLOBE was conceived, no DEM of higher resolution was known that covered more than two-thirds
of Earth’s land surface. That DEM (NIMA, various dates) and most higher-resolution DEMs outside
the United States are restricted by copyright or other limitation on their distribution.
Two global DEMs have been produced at 30" gridding during the design and development of GLOBE.
The Jet Propulsion Laboratory, a Federally-funded Research and Development Center operated by
the California Institute of Technology for the National Aeronautics and Space Administration (NASA),
developed a DEM from Digital Terrain Elevation (DTED) and other sources, for internal use in
support of NASA satellite missions. Separately, the U.S. Geological Survey developed a DEM called
GTOPO30. Both of these data sets have provided important pieces of GLOBE Version 1.0. However,
GLOBE Version 1.0 differs from such projects:
n Additional contributions have been made directly to GLOBE, and to the National Oceanic
and Atmospheric Administration’s (NOAA’s) long-standing program in international digital
elevation data. Eighteen (18) combinations of data source/lineage have been mosaicked and
described.
n GLOBE is an ongoing program of data collection, with enhancement of the data base and
documentation for as long as the data are useful.
n GLOBE is an active program to enhance access to the data. This includes evolving
improvements to the GLOBE Web site, and to CD-ROM and other possible distributions of
GLOBE data. This also includes plans to make available many source DEMs, not just the
final GLOBE mosaic, plus documentation.
GLOBE data are suitable for many regional and continental applications, such as:
n Design for communications infrastructure (such as cellular communications networks and
radio/television broadcast antenna systems) in the absence of higher-resolution data. For
example, the U.S. Federal Communications Commission certified 30" data for the
conterminous United States for such purposes. The data have been distributed for almost two
decades by NOAA’s National Geophysical Data Center (NGDC).
Global Land One-kilometer Base Elevation
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? Logistical design for other civil works in remote areas, in the absence of higher-quality data.
? Development of flight safety systems (navigational aids, terrain avoidance aids, etc.). Note
that such critical applications require careful adaptation of DEMs with current levels of quality.
? Processing of satellite data such as geometric and atmospheric correction of medium and
coarse resolution satellite image data (Gesch, 1994; Jet Propulsion Laboratory, 1998, in press),
as well as initial geometric correction of higher-resolution satellite data.
? Various forms of environmental study, such as climate modeling, continental-scale land cover
mapping, and extraction of drainage features for hydrologic modeling (Danielson, 1996;
Verdin and Greenlee, 1996).
? “Validation” of future global DEMs (especially when the candidates for GLOBE are also
used) and of future regional DEMs lacking better, available regional DEMs for the same
region.
Caveats: Note that GLOBE Version 1.0, like other digital topographic data, are insufficiently accurate
over their full global extent to be taken too literally for mission-critical applications. They must
always be interpreted with extreme caution. They should not be used exclusively in mission-critical
or life-critical applications. Nevertheless, GLOBE Version 1.0, with its present 30" gridding, multiple
sources, and documentation designed to inform users of the character of such data, is a remarkable
improvement over previously available data and ancillary materials. It greatly exceeds the original
expectations of its developers. This document contains discussions about data quality; caveats are
concentrated in Sections 6 and 12.
GLOBE remains in active development. Peer review continues to be an integral part of the GLOBE
process; please see our peer review site on the World Wide Web linked from http://www.ngdc.noaa.gov/
seg/topo/globe.shtml. Future versions of GLOBE should be even more valuable, as they are expected
to include:
? Additional improved elevation data
? Global bathymetric coverage
? Multiple indices (such as quasi-maximum and quasi-minimum elevations as well as
representative values) where available
? Multiple source files and documentation designed so that the user may be able to develop
custom DEMs
? Visualizations, such as NGDC provides for other DEMs that it distributes. (See Web sites
http://www.ngdc.noaa.gov/mgg/topo/state.html and http://www.ngdc.noaa.gov/mgg/image/
images.html for examples.)
GLOBE has been creative in negotiating ways to release new DEMs to the public:
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Documentation Version 1.0
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? The GLOBE project negotiated the first public release of the previously restricted Digital
Terrain Elevation Data (DTED) from the Defense Mapping Agency (now the National Imagery
and Mapping Agency). DTED Level 0 was initiated as a joint DMA/GLOBE design, and was
contributed to NGDC for GLOBE.
? The GLOBE project negotiated development of non-copyright derivations from copyright
DEMs. This has involved joint design of a DEM with lower horizontal and/or vertical resolution
or a different datum or map projection than is subject to local copyright requirements or
desires. The resultant DEM is still valuable as part of the GLOBE compilation.
? GLOBE has developed creative licensing agreements with sources of high-resolution data,
allowing high-quality data that must be kept under copyright to still be accessible.
GLOBE cites sources of data, and can mention, when appropriate, that certain sources can directly
supply higher quality data. We hope you will contact the GLOBE Secretariat about the benefit to
yourselves (and the public) from contributing to the GLOBE data base. Please contact:
David Hastings, Secretary of GLOBE
National Oceanic and Atmospheric Administration
National Geophysical Data Center
325 Broadway
Boulder, Colorado 80305, U.S.A.
Tel: (+1-303) 497-6729
Fax: (+1-303) 497-6513
email: [email protected]
Participants in the GLOBE Task Team are noted in Section 2.C and in Appendix A.
Note: The Web-based version of this documentation will receive more frequent updates than the
printed version. Go to http://www.ngdc.noaa.gov/mgg/topo/report/.
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Global Land One-kilometer Base Elevation
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2. Introduction
2.A. What GLOBE Is
The Global Land One-kilometer Base Elevation (GLOBE) project is several things.
n GLOBE is a data base. It is a unique, global, digital elevation model (DEM) designed,
openly peer-reviewed, implemented, and documented while being coordinated by a global
consortium of scientists and organizations. During GLOBE’s development, at least two global
DEMs were developed by other groups supporting various objectives. However, GLOBE’s
objectives (as noted here) are broader than merely the development of the data base.
n GLOBE is a file format. GLOBE began with the conceptual opening of a two-dimensional
thirty-arc-second (30") latitude-longitude digital data array, and the hope to populate it with
both the Best Available Data (B.A.D.), and the Globally Only Open-Access Data (G.O.O.D.).
The former could include copyright data that might be made available for distribution by
GLOBE with minimal restrictions, while the latter could not contain any restricted data.
Allowing for both options has enabled GLOBE, for example, to work with the Australian
Surveying and Land Information Group to develop a DEM much better than could otherwise
be included while respecting the intellectual property rights of the Australian government.
n GLOBE is a data management philosophy. GLOBE’s original array actually was a nested
grid that allowed multiple overlapping coverage at various grid spacings, but all in latitude-
longitude projection. The design followed the raster data model of the Geographic Resources
Analysis Support System (GRASS), a scientific geographic information system. This concept
was used in NGDC’s TerrainBase (Row and Hastings, 1994), which was a prototype of GLOBE
at lower resolution. The concept proved stable throughout the 8 years of GLOBE’s
development.
n GLOBE is a working environment. GLOBE was never a source for funding DEM data
creation. Rather, GLOBE was (and is) an ad-hoc group that meets to share information on
data sources and development techniques. Semiannual to annual GLOBE meetings were
attached to other assemblies to allow for synergy between GLOBE participants and other
scientists. The simultaneous development of increased cooperation between agencies in several
countries, and between certain military and civilian institutions, led to increased public access
to a major military DEM. In addition, that climate led to an agreement for joint development
of a dedicated Space Shuttle mission designed to create an almost-global DEM (between 60°
North and South latitudes, the orbital coverage of the Space Shuttle). The currently funded
U.S. Department of Defense/NASA Shuttle Radar Topography Mapper mission hopes to
provide publicly-available 3 arc-second digital elevation data during 2001–2002.
Documentation Version 1.0
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2.B. A Brief History of GLOBE
GLOBE was initially spearheaded in 1990 by Gunter Schreier of the Deutsches Fernerkundungs-
datenzentrum (DFD, the German Remote Sensing Data Center), part of the Deutsches Zentrum für
Luft- und Raumfahrt (DLR, the German Aerospace Center). Schreier was interested in improved
regional and global DEMs for satellite data processing. His goal was to create a diplomatic environment
among:
n U.S. Geological Survey (USGS), which was experimenting with contour-to-grid conversions
of Digital Chart of the World (DCW) hypsography to DEMs
n University College London (UCL), which was experimenting with several techniques of
creating DEMs
n National Geophysical Data Center (NGDC), with its long-standing program of increased
access to international and global digital terrain data
n Others who might be interested in such cooperation and data development
GLOBE began as an ad-hoc group, though Schreier hoped to affiliate GLOBE with the Committee
on Earth Observation Satellites (CEOS) Working Group on Data (WGD, later largely reformed into
the Working Group on Information Systems and Services, WGISS), and the International Geosphere-
Biosphere Programme’s (IGBP) Data and Information System (DIS). Formal affiliation with CEOS/
WGD came in 1993. GLOBE is also an official project within Focus 1 of IGBP-DIS (http://
www.cnrm.meteo.fr:8000/igbp/frame/activities/activity_13/index2.html).
GLOBE held meetings at DLR, USGS, and NGDC, and participated in meetings of the CEOS-
WGD, the CEOS-WGISS, and the CEOS Working Group on Calibration and Validation. In addition,
a Digital Elevation Model Science Working Group (DEM/SWG) formed later by NASA to support
objectives of its Earth Observing System, had significant common interests with GLOBE participants
and mission. The distribution of these meetings allowed various specialists in topography to share
their expertise with the GLOBE Task Team (as CEOS-WGD named the group). Gunter Schreier was
the first head (and only “officer”) of the GLOBE Task Team.
The original concept opened an empty 30 arc-second latitude-longitude array, and began listing
possible sources of DEMs that could populate that array. Initial plans were to encourage experiments
by USGS to convert DCW hypsography to 30" grids, and to seek additional contributions of DEMs.
NGDC’s ETOPO5, or possibly its TerrainBase (then being conceived) would be over-sampled for
use as filler wherever better data were not made available.
1992: DMA published DCW. Prototypes had been evaluated for several years prior to 1992, but this
year marked the availability of DCW’s full global coverage.
1993: Techniques for converting DCW were well underway by USGS with participation by UCL.
UCL’s J.-P. Muller determined that SPOT imagery, by nature of pricing and restrictions on the data,
Global Land One-kilometer Base Elevation
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would not be feasible for GLOBE. Also in 1993, a change in Schreier’s duties made it difficult for
him to continue as Secretary of GLOBE; David Hastings of NGDC succeeded him in late 1993.
1994: Hastings was able to negotiate, in cooperation with Gerald Elphingstone and others at the
Defense Mapping Agency (DMA), the design and development of a 30" DEM derived by DMA for
contribution to GLOBE. This became the prototype for DTED Level 0, which is now available on the
National Imagery and Mapping Agency’s (NIMA, DMA’s successor) Web site and on CD-ROM
from NGDC. This became the single largest contribution to GLOBE by coverage area.
1995: The Geographical Survey Institute (GSI) of Japan created an unrestricted DEM for the
international scientific community, contributing it to the GLOBE project. This became an example
for some other sources of copyright DEMs to derive publicly releasable versions to the scientific
community. The first contribution by DMA was released on CD-ROM by NGDC as GLOBE Prototype
Version 0.1.
1996: The Australian Surveying and Land Information Group (AUSLIG) negotiated to have NGDC
create a 30" DEM of Australia from AUSLIG source materials. This data set remains the property of
AUSLIG, but is licensed to NGDC for distribution with GLOBE. AUSLIG also became a distributor
of GLOBE by this agreement. Also in 1996, DTED Level 0 was placed on NIMA’s Web site.
1997: Several DEMs were brought to the GLOBE project’s attention. Several of these are still under
consideration.
1998: GLOBE Version 1.0 neared completion.
1999: GLOBE Version 1.0 was completed and released. Work on updated releases are in progress.
2.C. Major Collaborators in GLOBE
The members of the GLOBE Task Team, with representative contributions, are summarized below,
in time-sequential order. Acronyms are defined in Appendix B.
Before 1993:
DLR (Gunter Schreier and Achim Roth): initial coordinator (Schreier), design considerations,
quality control
NOAA/NGDC (David Hastings and Paula Dunbar): later coordinator (Hastings); prototype
construction in the form of NGDC’s TerrainBase; DEM collection, creation, and conversion;
coordinating GLOBE review, compilation, documentation, and access
UCL (Jan-Peter Muller): Design considerations, DCW conversion prototyping, quality control
testing
USGS/EDC (Susan Jenson and Dean Gesch): DCW conversion, DEM collection and conversion,
construction of USGS’s GTOPO30
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1993:
CEOS-WGD (via Gunter Schreier): design and distribution considerations
1994:
DMA (now NIMA; Gerald Elphingstone): developing publicly releasable DTED prototype, design
considerations
GSI (Hiroshi Murakami, later Hiromichi Maruyama): DEM of Japan, quality control, digitizing
IGBP-DIS (John MacDonald): design and distribution considerations
1995:
JPL (Nevin Bryant): design and distribution considerations, development of MISR DEM
1996:
AUSLIG (Peter Holland): data from which to create a DEM of Australia
1997:
ISPRS Working Group IV/6 (Ryutaro Tateishi): design considerations
2.D. Contributions Invited for Future Enhancements to GLOBE
GLOBE remains an active project. Contributions are still valuable. If you have a DEM that could be
appropriately formatted to 30" latitude-longitude projection, World Geodetic System-84 horizontal
datum, and Mean Sea Level vertical datum, please contact the GLOBE Secretariat.
If your data are proprietary or copyright, we would still like to discuss cooperation with you. Several
holders of proprietary or copyright data have found it useful to adapt their data for distribution with
GLOBE (or the similarly designed TerrainBase). If your data are of higher resolution, for example, a
30" “sampler” in GLOBE, with proper source citation, could help bring attention to your data.
Global Land One-kilometer Base Elevation
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3. Citation of GLOBE and Copyright Information
3.A. Citation of GLOBE
The GLOBE data base should be cited as follows:
GLOBE Task Team and others (Hastings, David A., Paula K. Dunbar, Gerald M. Elphingstone,
Mark Bootz, Hiroshi Murakami, Hiroshi Maruyama, Hiroshi Masaharu, Peter Holland, John
Payne, Nevin A. Bryant, Thomas L. Logan, J.-P. Muller, Gunter Schreier, and John S.
MacDonald), eds., 1999. The Global Land One-kilometer Base Elevation (GLOBE) Digital
Elevation Model, Version 1.0. National Oceanic and Atmospheric Administration, National
Geophysical Data Center, 325 Broadway, Boulder, Colorado 80303, U.S.A. Digital data base
on the World Wide Web (URL: http://www.ngdc.noaa.gov/mgg/topo/globe.html) and CD-
ROMs.
This documentation manual should be cited as follows:
Hastings, David A., and Paula K. Dunbar, 1999. Global Land One-kilometer Base Elevation
(GLOBE) Digital Elevation Model, Documentation, Volume 1.0. Key to Geophysical Records
Documentation (KGRD) 34. National Oceanic and Atmospheric Administration, National
Geophysical Data Center, 325 Broadway, Boulder, Colorado 80305, U.S.A.
Some other editorial efforts of the National Geophysical Data Center, such as the Global Ecosystems
Database (NOAA and EPA, 1992) and TerrainBase (Row and Hastings, 1994), are edited as symposium
volumes. In those efforts, individual constituents are treated as chapters in the symposium volumes,
and are separately citable.
GLOBE is somewhat different. GLOBE contains a combination of data sets, derived from a different
combination of sources, and reprocessed through a still different combination of lineages. Some
sources are not fully cited. In addition, several processing methods are not fully cited. For example,
Digital Terrain Elevation Data come from “best available sources,” which are not cited, and are
derived by methods which are also not cited. Thus, full citability of GLOBE components is not
currently possible, and will not be possible until some sources of data for GLOBE are better
documented. Our alternative for GLOBE is to cite the entire data set as above, and to cite individual
parts of GLOBE by source and lineage, as described in Sections 5 and 11.E.
Each individual data set used in GLOBE may be cited separately, using the asterisked (*) citation for
that data set (Sections 5.A.i through 5.A xi).
If you’re planning to use GLOBE for research or development issues, please cite GLOBE in your
bibliography as noted above. GLOBE is a peer-reviewed formal scientific publication. In addition,
please read Sections 6 and 12 if you plan to develop anything from GLOBE, or plan to redistribute
GLOBE (or any derivation of GLOBE).
AcrB546.pdf 4/1/2008 12:19:10 PM
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3.B. Copyright and Redistribution Information
Though an improvement over previous global DEMs, GLOBE data are imperfect. See the caveats
and disclaimers in Sections 6 and 12 of this document.
3.B.i. Copyright Information
For the most part, these data are not copyright, nor are they restricted in any way. This is true of all
data files and information, except for selected data within the B.A.D. (Best Available Data) data files.
(See Section 11.A for the file-naming convention.) In GLOBE version 1.0 the only area with B.A.D.
GLOBE coverage is Australia, with data copyright AUSLIG.
The documentation, source/lineage, and G.O.O.D. files (Globally Only Open-access Data) files are
all unrestricted. (See Section 11.A for the file-naming convention.). However, these are scientific
data, and should be cited accordingly. The citation of the full G.O.O.D. files should be made as noted
in Section 3.A. If you want more detailed citation of geographic parts of GLOBE, you should refer to
the source/lineage map, and its legend (given in Section 11.E).
3.B.ii. Redistribution Information
If you repackage and/or redistribute G.O.O.D. GLOBE files in any way, please be aware of the
disclaimers in Section 12, and others throughout this document.
The copyright data in B.A.D. GLOBE files may not be repackaged or reproduced in any way without
permission of the copyright holders. The distribution of copyright data (contained only in files with
???B pattern names) is shown in the source files with the ???T pattern names. Contact names and
addresses are in Appendix A.
Global Land One-kilometer Base Elevation
10
4. General Characteristics of GLOBE
The Global Land One-Kilometer Base Elevation (GLOBE) digital elevation model (DEM) is a global
data set covering 180
o
West to 180
o
East longitude and 90
o
North to 90
o
South latitude. The horizontal
grid spacing is 30 arc-seconds (0.008333... degrees) in latitude and longitude, resulting in dimensions
of 21,600 rows and 43,200 columns. At the Equator, a degree of latitude is about 111 kilometers.
GLOBE has 120 values per degree, giving GLOBE slightly better than 1 km gridding at the Equator,
and progressively finer longitudinally toward the Poles (see Section 6.A).
The horizontal coordinate system is seconds of latitude and longitude referenced to World Geodetic
System 84 (WGS84). The vertical units represent elevation in meters above Mean Sea Level. The
elevation values range from -407 to 8,752 meters on land. In GLOBE Version 1.0, ocean areas have
been masked as “no data” and have been assigned a value of -500.
Besides the GLOBE DEM, associated files include a source/lineage file. This source/lineage file
provides a mask of ocean coverage (by using category 0 of the source/lineage file), so that the user
may reassign the -500 flag values for ocean coverage to 0, then later re-separate those values from 0
values on land.
Due to the nature of the raster structure of the DEM, small islands in the ocean less than approximately
1 square kilometer (specifically, those that are not characterized by at least one 30" grid cell and/or
do not have coastlines digitized into Digital Chart of the World or World Vector Shoreline) may not
be represented.
Though an improvement over previous global DEMs, GLOBE data are imperfect. See the caveats
and disclaimers contained in Sections 6 and 12 of this document.
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5. Data Set Development
Six gridded DEMs, and five cartographic sources, were adapted for use in GLOBE. Several of these
sources were processed in more than one way (sometimes involving several different organizations)
to create 30" grids. This resulted in 18 combinations of source/lineage used in GLOBE.
The source materials are discussed immediately below, followed by discussions of regional quality
control assessments and merges of the data. Thirty histograms showing distribution values for all
source/lineage combinations are presented.
5.A. DEM Sources and Processing
GLOBE version 1.0 has 11 broad sources of information. Many of these sources themselves have
multiple sources, such as different series of imagery, maps, cadastral surveys, etc. In addition, some
of these 11 broad sources of information have been reprocessed in various ways, by various
organizations, before being combined into GLOBE Version 1.0.
GLOBE is not monolithically uniform in its characteristics. In fact, no monolithically uniform DEM
of any great coverage area has yet been demonstrated to the GLOBE Task Team.
GLOBE cites data sources by original source and subsequent lineage. The importance of this for data
stewardship is apparent.
Besides DTED Levels 1–5, distributed only by NIMA, and DTED Level 0, distributed via NIMA’s
Web site and on CD-ROM by NGDC, several other data sets developed from DTED or its precursors
are distributed by other organizations. For example:
n The USGS’s 3 arc-second DEMs for the conterminous United States and Alaska are actually
an embryonic version of DTED that was transferred to USGS in the 1970s for public
distribution.
n Similarly, some 30" and 5' DEMs distributed by NGDC since the early 1980s were derived
by DMA and contributed to NGDC for public distribution.
n Subsequently, many DTED cells for the same area have been updated, beyond the versions
originally contributed to USGS and NGDC.
n USGS used some of its 3" data in its GTOPO30 compilation that contributed significantly to
GLOBE Version 1.0.
n Data from the NGDC version was added to GLOBE, as appropriate.
We thus prefer to cite the full lineage of the data in GLOBE documentation, including source and
intermediate steps in the lineage of the data.
Global Land One-kilometer Base Elevation
12
When citation of original source plus subsequent lineage is done, the contribution of the National
Imagery and Mapping Agency and its predecessors (via DTED, Digital Chart of the World, and their
derivatives) is noteworthy. A preponderance of the data began at this source. In addition, several
previously copyright DEMs have been adapted for inclusion on an unrestricted or highly open basis.
Also, GLOBE borrowed procedures, and in some cases data, from previous global DEM efforts,
listed in Appendix A. The GLOBE project is indebted to these initiatives.
Various combinations of data source and lineage have resulted in subtle differences in georegistration
and the actual type of elevation values used in different parts of GLOBE. The decisions that led to
these differences were often based on scientific/technical analyses by diverse teams of data producers.
However, some decisions may appear arbitrary to the user of GLOBE data. Considering the wide
variety of possible influences on a DEM, the variety of georeferencing and sampling techniques
incorporated into GLOBE is far from its greatest possible source of error.
Table 1. Percentage of the Global Land Surface Derived from Each Source
% of global appx. % of number of 30"
Source 30" grid cells global area grid cells
Oceanic coverage 66.8 71.1 623,579,513
Land coverage 33.1 29.9 309,525,237
% of non-oceanic appx. % of number of 30"
Source 30" grid cells land area grid cells
Digital Terrain Elevation Data
*
46.6 57.5 144,162,669
Digital Chart of the World 16.5 22.6 51,368,537
Australian DEM
**
3.2 5.2 10,031,254
Antarctic Digital Database 28.1 8.3 86,945,078
Brazil 1:1,000,000-scale maps 2.0 3.5 6,027,490
DEM for Greenland 2.6 1.0 7,344,478
AMS 1:1,000,000-scale maps 0.67 1.1 2,088,224
DEM for Japan 0.18 0.26 556,763
DEM for Italy 0.16 0.21 490,585
DEM for New Zealand 0.14 0.18 419,894
Peru 1:1,000,000-scale map 0.03 0.05 90,625
*
This line shows percentages of GLOBE derived from DTED sources, by all intermediate steps used. This includes
DTED Level 0, and other 30" derivations from DTED and its prototypes distributed by the National Oceanic and
Atmospheric Administration, and the U.S. Geological Survey.
**
There are two versions of GLOBE. One version is completely unrestricted, and uses a DEM developed from Digital
Chart of the World (DCW). Another version contains a licensed DEM from the Australian Surveying and Land
Information Group. The figure given for Australia covers the area of that country/continent. If you are using the
version of GLOBE that incorporates the DCW-based DEM for Australia, the total percentage of global land area with
DCW source combines this line with the line above, for a total of 27.7% of the global land surface, 19.6% of non-
oceanic 30" grid cells, and 60,666,875 total 30" grid cells. The unrestricted (G.O.O.D.) version of GLOBE has slightly
less land area than the best available (B.A.D.) version of GLOBE in Australia. Table 1 shows the B.A.D. version.
Note that in source/lineage category 13, the blend between categories 12 and 14 contains 1,435,022 grid cells. Half
this number (717,511 grid cells) has been assigned
each
to categories 12 (JPL model for Greenland) and 14 (DCW).
This is because Table 1 treats
sources,
and the blending process used to make category 13 is dominated by category
12 in half its area, and by category 14 in the other half of its area.
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5.A.i. Digital Terrain Elevation Data (DTED)
Primary Developer: National Imagery and Mapping Agency (NIMA, formerly Defense
Mapping Agency (DMA); prior to DMA, the Army Map Service).
Title: Digital Terrain Elevation Data Levels 1 and 0
Publication Dates: Regular releases since the 1960s
Bibliographic Citations:** National Imagery and Mapping Agency, 1996. Digital Terrain
Elevation Data Level 0. National Imagery and Mapping Agency,
Fairfax, Virginia. (Partly in GLOBE Task Team and others, 1999.)
National Imagery and Mapping Agency, various dates. Digital
Terrain Elevation Data Level 1 and derivations (in USGS, ed., 1997,
and partly in GLOBE Task Team and others, 1999).
Post-processing: Defense Mapping Agency (versions described below contributed
to U.S. Geological Survey and National Geophysical Data Center),
U.S. Geological Survey (for GTOPO30), and NOAA/National
Geophysical Data Center (for GLOBE).
DTED Level 0 is the outcome of joint GLOBE/DMA design and
DMA/NIMA implementation. Its prototype was contributed directly
to the GLOBE project, as was a copy of DTED Level 0.
Bibliographic Citation * NIMA, USGS, and NGDC, 1997. 30"-gridded DEM from DTED,
for Post-processed DEMs: Precursors, and Derivatives. National Geophysical Data Center,
Boulder, Colorado (in GLOBE Task Team and others, 1999).
Source/Lineage Categories: 1–7
*
Primary reference citation for all data from this source
** Primary reference citation for DTED Level 0
DTED is a raster topographic data base provided by NIMA and its predecessors: (1) between 1 July
1972 and 30 September 1996 by the DMA, (2) between September 1968 and June 1972 by the U.S.
Army Topographic Command (USATC), and (3) before September 1968 by the Army Map Service
(AMS), which was formed in May 1942. The earliest digital antecedents to DTED were developed in
the 1950s by AMS.
DTED was used as the source for most of Eurasia and large parts of Africa and the Americas.
DTED Level 0, a new NIMA data base, is the result of a joint GLOBE/DMA initiative, which resulted
in the joint design and DMA production (just before DMA was reorganized into NIMA) of DTED
Level 0.
Global Land One-kilometer Base Elevation
14
5.A.i.a. Source Characteristics
DTED Level 1 is produced in 3 arc-second gridding, on a latitude-longitude projection. DTED Level
1 data files have the following characteristics:
n They cover 1
o
by 1
o
of latitude-longitude, and are called “DTED cells.”
n DTED files have their origin in the southwestern corner of the DTED cell. The grid cell
registration is centered on that corner. Thus the first 3" DTED grid cell in the file continuing
north from 40
o
N latitude and east from 40
o
E longitude would be centered at exactly that
location.
n Grid cell sequencing begins at the southwestern corner (the origin of the file just noted), then
continues upwards (column-wise) to the northwestern corner. Successive eastward columns
are presented. The final value in the file is the value of the northeastern corner.
n DTED files have 1201 columns by 1201 rows, overlapping at their edge columns and rows
with neighboring DTED cells.
DTED Level 1 data are created from a variety of “best-available” sources. These may be:
n cartographic: maps containing elevation contours and/or point values created by national,
local, or non-U.S. agencies, or by NIMA itself or its predecessors
n imagery: aerial photography or satellite imagery, from U.S. or non-U.S. sources
n other possible sources such as Global Positioning Survey measurements or satellite altimetry
Sources are not publicly cited. However, certain characteristics of resultant DEMs help interpret
general source characteristics. For example, analysis of shaded-relief images digitally derived from
DEMs often detect blockiness, striping, or other patterns symptomatic of various data development
techniques. Some of these are discussed below, and explicitly illustrated on the GLOBE Web site’s
public Beta Test area (linked to the GLOBE Home Page at http://www.ngdc.noaa.gov/seg/topo/
globe.shtml).
Common artifacts in DTED Level 1 data include:
n Vertical offsets between many 1
o
by 1
o
DTED files. These may be seen as vertically offset
blocks in shaded-relief or slope maps derived from the data. These offsets may be caused by
discontinuities in cartographic source materials, such as topographic contour lines that fail to
match across map boundaries. They may also be caused by inadequately documented geodetic
models, such as incorrect or missing information on projection or datum. Edge “feathering”
as an attempt to provide continuity between 1
o
by 1
o
DTED cells also contributed artifacts of
its own.
n Directional biases in resolution. These may be seen as striped patterns in shaded-relief, slope,
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or aspect maps derived from such data. Such anisotropies in DEMs may be caused by
stereoprofiling techniques (often involving oversampling between stereoprofiles to make the
final grid). These techniques were sometimes used to create DEMs from analog stereoscopic
imagery or undeterminable satellite source sensor characteristics.
The artifacts are common to other DEMs derived by similar techniques from similar sources.
Prototype correction techniques have been developed at the Jet Propulsion Laboratory, Pasadena,
California. Presentations at GLOBE Task Team meetings (Nevin Bryant, California Institute of
Technology, 1995, verbal communication; see also Ritter and Bryant, 1997) have demonstrated the
contribution that such techniques might make toward rectifying some artifacts in DTED. However,
in the absence of a more substantial study, the GLOBE Task Team decided not to attempt such
repairs for GLOBE Version 1.0.
Between 50
o
North and South latitudes, DTED Level 1 data are 3x3 arc-second grids. Outside these
latitudes the longitudinal gridding gets coarser:
latitude seconds seconds
range (N & S) of latitude of longitude
0°–50° 3 3
50°–70° 3 6
70°–75° 3 9
75°–80° 3 12
80°–90° 3 18
Stated accuracy objectives are within 50m horizontal (at 90% circular error; twice the standard
deviation), and 30m vertical (at 90% linear error; two sigma). However, areas lacking source materials
that meet these standards may still have DTED created for them, if adequate alternatives are not
envisaged.
DTED seeks to use World Geodetic System 84 (WGS84) for horizontal reference, and Mean Sea
Level as vertical reference. However, this may not always be the case as cartographic sources may
not be completely or accurately described, and materials from such sources may not be accurately
converted to WGS84 and Mean Sea Level.
5.A.i.b. Derivation of the 30" DEM from Source Materials
In 1994, NGDC and DMA jointly designed a 30" DEM which DMA would contribute to NGDC for
GLOBE. In the original design, a 10x10 array of 3" DTED Level 1 grid cells was processed to
determine the minimum, maximum, and mean of 3" values in each available 30" GLOBE grid cell.
The data were restructured at NGDC for more convenient processing in raster geographic information
systems (GIS), and released to the public as GLOBE Prototype Version 0.1 in 1995.
NIMA added a discrete (spot) 3" value to the data collection. This compilation is available at NIMA’s
Global Land One-kilometer Base Elevation
16
Web site (http://www.nima.mil) at the time of writing this document, and also on CD-ROM from
NGDC as GLOBE Prototype Version 0.5. The latter version has the files restructured for greater ease
of use in a GIS.
Southwestern corner 3" value assigned to 30" grid cell.
Graphic describing georeferencing and sampling for DTED Level 0
discrete (spot) data (source/lineage category 1).
In addition, DMA had contributed coverage for most of the United States from an early precursor of
DTED to USGS for public distribution. USGS calls these data “USGS 3 arc-second data.” USGS
resampled these data to 30" by nearest-neighbor techniques, for incorporation into GTOPO30. These
data form GLOBE 1.0 source/lineage category 5.
Cell-centered registration, nearest-neighbor 3" value used.
Graphic describing georeferencing and sampling for DMA/USGS 3
arc-second data to 30” for the U.S.A. (source/lineage category 5).
Similarly, DMA provided 30" grids for the conterminous U.S. (from an early version of DTED) for
public distribution by NGDC in the early 1980s. This 30" DEM included mean and spot (nearest-
neighbor from 3") values. The spot data form GLOBE 1.0 source/lineage category 4.
Cell-centered registration, nearest-neighbor 3" value used.
Graphic describing georeferencing and sampling for DMA/USGS 30”
spot data for the conterminous U.S.A. and vicinity (source/lineage
category 4).
As noted previously, USGS developed a 30" global DEM, called GTOPO30. GTOPO30 development
involved specific groups assembling data for the different continents. Decisions made by these groups
resulted in the following resampling methods:
n For Africa (the first continent attempted), the resampling of 3" data used a “breakline” approach
that favored ridges and valleys (Gesch and Larson, 1996). This was done to best fit with the
ANUDEM-based methods (Hutchinson, 1989, 1996; Danielson, 1996) used for Digital Chart
of the World gridding for Africa. (See next page for graphic.)
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Cell-centered registration, breakline value computed.
Graphic describing georeferencing and sampling for DTED for Africa
(source/lineage category 6).
n For Eurasia, the resampling consisted of computing median values of non-oceanic locations
within each 30" arc-second grid cell.
Cell-centered registration, 10x10 median value computed.
Graphic describing georeferencing and sampling for DTED for Eurasia
(source/lineage category 2).
n For the Americas, the resampling consisted of taking a (“nearest-neighbor”) 3" value nearest
the center of each respective 30" grid cell. Due to the georeferencing of the 30" GLOBE grid
compared to that of 3" DTED Level 1 data, there is a 3" DTED Level 1 grid cell-centered
directly at the center of a 30" GLOBE cell. That value was used in the Americas.
Cell-centered registration, nearest-neighbor 3" value used.
Graphic describing georeferencing and sampling for DTED for the
Americas (source/lineage category 3).
n The DEMs for Eurasia and Africa were mosaicked along 39
o
N latitude, and 59
o
E longitude.
The data were linearly blended along a 2-degree-wide zone centered along these lines. Thus
at 40
o
N, median derivations were used, at 38
o
N (west of 58
o
E) breakline methods were used
exclusively, and at 39
o
N (west of 59
o
E) 50% weighting of both of these methods was used.
This blending is category 7 in the source/lineage map.
Thus, data originally from DTED sources have been contributed to GLOBE directly from NIMA. In
addition, data were previously contributed by DMA for public distribution to USGS and NGDC at
various times during the past 20 years. The source/lineage map (on the back cover of this publication)
shows where different versions of these data were used in GLOBE Version 1.0.
Global Land One-kilometer Base Elevation
18
5.A.i.c. Extracts from Prototype NIMA Documentation of DTED Level 0
The following text is from NIMA’s provisional description of DTED Level 0 (http://www.nima.mil/
geospatial/products/DTED/dted.html) at the time of release of DTED Level 0:
“In support of military applications, the National Imagery and Mapping Agency
(NIMA) has developed a standard digital dataset (Digital Terrain Elevation Data
(DTED) Level 0) which may be of value to scientific, technical, and other communities.
This DTED product is a uniform matrix of terrain elevation values which provides
basic quantitative data for systems and applications that require terrain elevation,
slope, and/or surface roughness information. DTED Level 0 elevation post spacing is
30 arc-second (nominally one kilometer). In addition to this discrete elevation file, a
separate binary file provides the minimum, maximum, and mean elevation values
computed in 30 arc-second square areas (organized by one degree cell). Finally, DTED
Level 0 contains the NIMA Digital Mean Elevation Data . . . providing minimum,
maximum, and mean elevation values and standard deviation for each 15 minute by
15 minute area in a one degree cell. This initial prototype release is a “thinned” data
file extracted from the NIMA DTED Level 1 holdings in combination with other
publicly releasable data. As such, this version of DTED Level 0 is a step toward a
worldwide digital terrain dataset. Efforts to fully populate a worldwide DTED Level
0 dataset continue . . . The current DTED Level 0 and subsequent releases will be
updated consistent with established NIMA production maintenance procedures.
Support from select international mapping organizations was instrumental in the
generation of the Level 0 dataset. The following nations have contributed data to this
effort: Belgium, Denmark, France, Germany, Italy, Netherlands, Norway, Spain, and
the United Kingdom. In many cases, higher resolution terrain data of the above listed
nations is available for public sale. If you are interested in obtaining such data over
any of the above listed countries, please contact the civil mapping authorities of the
individual nation directly.
This data set may be freely copied, manipulated, adapted or combined with other
geospatial information as desired by the user. It allows a gross representation of the
Earth’s surface for general modeling and assessment activities. Such reduced resolution
data is not intended and should not be used for automated flight guidance or other
precision activity involving the safety of the public.
The data contained in DTED Level 0 is a derivative set only, and does not represent
the entire Department of Defense (DOD) archive of terrain data. In making this data
available to the general public, the NIMA in no way alters the controlled status of the
remaining archives. Technical support or general assistance with respect to DTED
Level 0 is available only to U.S. Government users. The NIMA requests that products
developed using DTED Level 0 credit the source with the following statement, ‘This
product was developed using DTED Level 0, a product of the National Imagery and
Mapping Agency.’”
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[
text continues on page 34]
5.A.i.d. Characteristics of 30" DEMs from DTED
Analysis of Histograms: Histograms showing distribution of values for all source/lineage
combinations are presented in this Section (Section 5) on data set development. Some histograms are
presented with two linear axes, while others have logarithmic vertical axes (ordinates). The abscissa
(horizontal axis) values are meters of elevation. The ordinate (vertical axis) values are normalized to
percentages by source/lineage for an individual elevation value (in meters).
Plate 1 shows the overall distribution of elevation values in GLOBE. It is shown here for comparison
with Plates 2 through 30, which show distributions of elevation values for individual parts of GLOBE.
Plate 1 is discussed in Section 5.B.ii.
The NIMA discrete (spot) data encompass about forty percent of GLOBE Version 1.0. In order to
initiate discussions on the major components of GLOBE, this analysis dissects the NIMA discrete
data into regions:
n Africa/Europe: Plate 2 covers DTED discrete data for 40
o
S to 60
o
N latitude and 18
o
W to
60
o
E longitude. There is a relatively linear decline (on the semi-logarithmic plot) between
about 1100m and 4000m. There is a broad, low, peak about 1000–1100m (much of Africa is
high plains of this altitude), several small spikes, and an apparently large spike at -400m.
This spike is an artifact of the semi-logarithmic plot, and involves less than 200 square
kilometers around the Dead Sea. The largest spike in this region occurs at -28m, corresponding
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to the surface of the Caspian Sea. Another large spike at 1875m corresponds to Lake Sevan in
Armenia. The DEM is generally smooth, with few (or no) spikes characteristic of cartographic
source materials.
n Asia: Plate 3 covers DTED discrete data for 0
o
to 50
o
N latitude and 60
o
to 150
o
E longitude.
There is a gradual decline in the semi-logarithmic plot to 4000m, with a broad peak about
1000m elevation (corresponding to large areas in central Asia), a small peak about 2700m,
and a large and relatively sharp peak at 5000m (corresponding to the Qinghai-Tibetan Plateau),
with a much steeper quasi-linear drop off between 5000m and 7000m. A small area in Asia
extends to over 8000m in elevation. There are few large spikes in this data set. Most notable
are one at 1601m, corresponding to Lake Issyk-Kul south of Alma-Aty, and another at 3176m,
corresponding to Lake Qinghai in Qinghai Province, China. The relatively low occurrence of
spikes, and the large areas of Asia with banded shaded relief images, suggest that imagery
was the major source of DTED in this area.
n North America: Plate 4 (covering DTED discrete data for 15
o
to 50
o
N latitude and 15
o
to
180
o
W longitude) shows considerable effect of spiking at various contour intervals. Though
these spikes are not as prominent as those in DEMs derived from DCW, the histogram suggests
that cartographic source materials may be more common in North America than in (for
example) Asia. The overall histogram has a modest trough below 300m (and a significant
trough for elevations below sea level), then a roughly linear decline from 300m to about
4500m, with additional troughs about 700m and 1100m.
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n South America: Plate 5 covers DTED discrete data for 55
o
S to 15
o
N latitude and 20
o
to
95
o
W longitude. There is a modest trough below 100m elevation, then a curved decline in
numbers of elevation values between 100m and 3000m. This curve continues slightly upward
to about 3600m, where a spike marks a discontinuous increase in area at 3600m to 4600m,
followed by a relatively rapid dropoff to 6000m. A few elevations occur to about 6800m. A
spike at 2300m corresponds to the Salazar de Atacama, east of Antofagasta, Chile. Spikes
between 3600m and 3800m correspond to elevations of the Altiplano, with 3810m being the
elevation of Lake Titicaca. Surrounding high plains and lower reaches of the Andes range
between 4000m and 5000m.
The data from DTED sources poleward of 50
o
(North or South) latitude (and in a few other
areas where NIMA discrete data were unavailable) were selected from GTOPO30. Those data
used three different sampling methods, plus a fourth type where two types were blended:
n Eurasia: Plate 6 primarily covers Eurasia north of 50
o
N latitude, plus a few areas not covered
by NIMA discrete data, such as France. The semi-logarithmic plot shows an almost linear
decrease between 600m and 3500m, with very modest bulges around 1000m and 2300m
(suggesting slight concentrations of elevations at those heights). Spiking is modest below
1700m, with one prominent spike at 1640m, corresponding to Lake Hovsgol in western
Mongolia. Above 1800m elevation, significant spiking is largely absent from the histogram.
There is a prominent spike at 1m, partly resulting from GTOPO30’s forcing sea level areas
on land to a nominal one meter elevation.
n Americas: Plate 7 has significant, narrow spikes at approximately 150m (500ft) intervals,
with secondary spikes at several lesser intervals. This suggests that a variety of contour intervals
was available in the DEM source maps. The semi-logarithmic plot is not linear as are a few
other semi-log plots of other DEMs. Modest peaks (broader than spikes) in the histogram
occur between 250–300m (just short of 1000ft), and 650–700m (just above 2000ft). Between
700m and 1200m the histogram is relatively smooth, with superimposed spikes. Modest
peaks occur around 1200m and above, at similar values to those of spikes. This suggests that
vertical granularity of the data is coarsest at 1200m (4000ft) and above. At such higher
elevations, major spikes occur at approximately 300m (1000ft) intervals. Such spikes exist at
lower elevations, but they are less prominent.
n Africa: Plate 8 is also somewhat similar to that for the median and nearest-neighbor
resamplings (source/lineage categories 2 and 3). This linear plot shows a granularity, but at
about 500m and 1000m, with a subsidiary peak at about 100m. The sharp spike at 1121m is
caused by Lake Beysehit in Turkey. These data appear in limited areas in GLOBE as they
were overwritten by DTED discrete (source/lineage category 1) data in most areas.
n Africa-Eurasia blend: Plate 9 shows data used only in a small portion of GLOBE. The data
were overwritten by DTED discrete (source/lineage category 1) data in most areas. The
Anatolian Plateau dominates the data set, with elevations about 1000 meters. The major
spikes in the data set represent lakes and playas in Turkey. For example, the spike at 892m
(2055 grid cells, compared to 300–600 grid cells for similar elevations) corresponds to Lake
Global Land One-kilometer Base Elevation
36
Tuzand. The spike at 1634m (5455 grid cells, compared to 300–320 cells for similar elevations)
corresponds to Lake Van.
Two additional DTED derivations were used in North America:
n DMA/NGDC: Plate 10 shows spikes about every 150m (500ft), with broader peaks about
300m and 600m. As with other DEMs for North America, a cartographic lineage appears to
dominate these data.
n DMA/USGS: Plate 11 shows an almost linear decline in frequency of occurrence below
about 3500m of elevation, with superimposed spikes denoting concentrations of elevation
values at various intervals. The major increments (shown by the most prominent spikes) are
about every 300m (1000ft), with lesser intervals at about 150m (500ft) and 75m (250ft).
Below 250m, smaller subsidiary contour intervals appear to have been included in the source
materials for this DEM.
Other Assessments: DTED Level 0 (the .dt0 and .mmm files on NIMA’s Web site) generally contains
four values of elevation for each 30" grid cell where 3" data are available. The following countries
have 3" DTED coverage: United Kingdom, France, Greece, Turkey, Cyprus, Israel, South Korea, and
Iceland. However, permission had not been received in time to place DTED Level 0 coverage at
NIMA’s Web site by October 1996: Subsequent permission allowed USGS to derive 30" DEMs for
all these countries but the United Kingdom.
DTED Level 0 data were produced by NIMA at consistent decimation rates, rather than for consistent
grid spacings. USGS resampled DTED to constant 30" grid spacings poleward of 50
o
latitude, where
permissible. Thus, poleward of 50
o
North and South latitudes, DTED Level 0 resolution is less than
GTOPO30’s.
In order to maintain consistent cell-centered georegistration, an 11x11 array of 3" DTED Level 1 grid
cells should have been sampled to arrive at DTED Level 0 values. Thus there is a very slight
misregistration implied by the 10x10 array actually used to make DTED Level 0. Considering the
other variabilities in current global DEM compilation, this should be of minor consequence.
DTED Levels 1 and 0 are integer values, as are other DEMs used here, resulting in some artifacts in
low-lying areas.
Peer review encouraged by NGDC resulted in the discovery that DTED Level 0 “mean” data were
frequently lower than DTED Level 0 “minima.” Further investigations at NGDC suggest that this
pattern varies by location—some areas experience this phenomenon more than others. To date, NIMA
has not updated these data. Discussions with peer reviewers led to the consensus that NIMA discrete
(spot) sample values, though displaced to the southwestern corners of the 30" grid cells, were the
most globally consistent and desirable candidate data for their areas of coverage, between 50
o
North
and South latitude, when other national sources were not better. Where USGS and NGDC have 30"
data with cell-centered nearest-neighbor georeferencing, NIMA discrete (spot) data may have less
desirable georeferencing. However, NIMA includes several updates and improvements not available
in the older versions available through NGDC and USGS.
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In addition to these observations, original characteristics of DTED, noted in Section 5.A.i.a still
apply to DTED Level 0, with minor alterations due to the different resolution of the 30" data.
The median, nearest-neighbor, and “breakline” versions within GTOPO30 are not shown in the
GTOPO30 source map available from USGS. As these may affect applications of the data, we have
attempted to illustrate where each version is located. We have modified our source map for GTOPO30
data, as well as our source map for GLOBE data, to reflect these different derivations, based on
descriptions of the process from USGS scientists. USGS’s blend between breakline and median data
processing is also depicted on GLOBE’s source/lineage map (back cover), where such data are used.
5.A.ii. DEM for Australia
Primary Developers: Australian Surveying and Land Information Group (AUSLIG) and
the National Geophysical Data Center (NGDC)
Title: 30" DEM for Australia
Publication Date: 1998
Bibliographic Citations: Australian Surveying and Land Information Group, 1996. Point
Elevation Data File for Australia. Australian Surveying and Land
Information Group, Belconnen, ACT, Australia.
* AUSLIG and NGDC, 1998. 30 Arc-second Digital Elevation Model
for Australia (in GLOBE Task Team and others, 1999).
Post-processing: None. The original development was directly for GLOBE.
Source/Lineage Category: 8
*
Primary reference citation for all data from this source
In 1996, NGDC and the Australian Surveying and Land Information Group (AUSLIG) signed an
agreement to provide access to high-quality Australian elevation information for GLOBE. AUSLIG
offered access to a data base of 5,190,624 point elevations, from which NGDC would derive a 30"
gridded DEM for use in GLOBE. The original data base was proprietary to AUSLIG; the resultant
DEM would be owned by AUSLIG and any other providers of data. AUSLIG would license the data
to NGDC for distribution with GLOBE.
Inspection of the data base (AUSLIG, 1996) by NGDC suggested that it consisted primarily of digitized
contours from topographic maps, supplemented by coastlines, and point elevations. AUSLIG describes
the data as follows (John Payne, AUSLIG, 1998, written communication):
“The elevation data in the relief theme supplied by AUSLIG had been derived from
AUSLIG’s published 1:100,000 scale topographic maps and unpublished 1:100,000
scale map compilation material. The elevation data are point elevations captured at
an irregular interval spacing to best portray the terrain. The spot elevation feature
Global Land One-kilometer Base Elevation
38
contains either spot heights on the source material or points selected from contours.
Spot heights are individual point elevations in the source material. They are generally
located at local high points such as sand ridges, hills and mountain tops or at the low
points in depressions. These points were observed directly by stereoplotter in the
map production process.”
Inspection of the source data found that topographic contour intervals tended to range from 10 meters
upwards. In some areas, data density averaged one value per 30" grid cell (sometimes slightly more,
sometimes less). More commonly, data were almost this dense in areas of high topographic relief and
high population—less than this in areas of low population and topographic relief. Of course, in areas
of low relief, one might expect fewer topographic contours. Overall data density may be inferred
from over five million elevation values for about ten million 30" grid cells for Australia (a 1/2 ratio).
In the view of NGDC scientists, this source data set was appropriate for the task of interpolating a
30" grid. A map showing coverage in AUSLIG (1996) is shown below.
NGDC experimented with various options of surface generation: the Generic Mapping Tools’
interpolation routines, Arc/INFO’s Triangular Irregular Network module, the Geographic Resources
Analysis Support System (GRASS)’ functions s.surf.idw, s.surf.tps, r.surf.idw, and r.surf.idw2. Several
Coverage by AUSLIG point source file (AUSLIG,
1996) is shown in black. Areas in white show gaps
in coverage.
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39
of the packages had difficulty in handling the volume of data required for this surface generation. In
the end, s.surf.idw in GRASS was selected as the smoothest running, yet appropriate for data
distributions as provided. Quality control at NGDC, University College London, and elsewhere,
determined that this DEM was of relatively high quality.
The surface generation was run in GRASS, within a mask derived as follows. Kent Lethcoe of USGS’s
EROS Data Center provided a 30" gridded mask of oceans (derived from World Vector Shoreline
[WVS]) and lakes (derived from Digital Chart of the World) vectors. Every 30" grid cell containing
at least one point of zero or higher elevation in the AUSLIG point data base was added to the land
area in this mask.
AUSLIG notes (John Payne, AUSLIG, 1998, written communication) that:
“In the AUSLIG data, all points which coincided with the coastline were derived by
selecting representative points on the waterline feature in the framework layer, and
assigning an elevation of 0 metres. Because the framework layer is 1:250,000 scale
source data, their accuracy is considerably different to the rest of the elevation data
contained in the relief theme. Zero values in the interior, and subzero elevations for
Australia, are well inland around Lake Eyre.”
The land mask for Australia provided by USGS was enlarged to include all 30" grid cells containing
point elevations in AUSLIG (1996). In so doing, we accepted the Australian source materials as
adding detail to the land mask previously based only on WVS coastlines. Areas on land (not counting
lakes and oceans) received interpolated elevations, where point elevations did not exist. The output
interpolated elevations were the inverse-distance-weighted mean of the three closest point elevations.
Elevations for each lake in the mask were taken to be the lowest DEM value around that lake. These
were determined as follows. Lake areas were “spread” one grid cell into adjacent shore areas, using
the GRASS function r.grow. The lowest elevation for each lake shore was determined by finding the
lowest non-zero value in each of the “spread” lake areas. These lowest shoreline values were then
assigned to their respective lakes as the highest water level that could be contained in the catchment
area.
Cell-centered registration, value interpolated from points.
Graphic describing georeferencing and sampling for AUSLIG/NGDC’s
model for Australia.
Analysis of Histograms: Plate 12 has spikes about every 20 and 50 meters, probably corresponding
to contour values on AUSLIG source maps. This histogram shows a few elevations below sea level
to about -30m, a modest trough above sea level to 60m, then a relative steady decline in frequency of
occurrence beyond 3500m, punctuated by spikes at apparent contour values in cartographic source
materials. These spikes are relatively high; likely the result of a high density of source point values at
Global Land One-kilometer Base Elevation
40
contour values, leaving relatively fewer gaps for the interpolation routine to populate with other
values.
Plate 13 shows spikes at approximately 30m (100ft) intervals, corresponding to contour values in the
source Digital Chart of the World. The largest spike in USGS’s DCW-derived DEM occurs at 304m,
corresponding to 1000ft elevation. Subsidiary contour intervals of 30m (100ft) below 600m (and to
a lesser degree to 1200m) are suggested by the histogram. There is a modest trough in this histogram
below 60m, then a plateau between 60m and 300m. There is a sharp drop to a lower plateau at 300–
600m, another sharp to a lower level (more a decay curve than a plateau) at 600–900m, and then
more gradual drops to 2400m. Finally, there is a slightly steeper drop to 3600m, after which there are
few elevations in Australia. This DEM has no elevations below sea level.
The spikes are more pronounced in the AUSLIG/NGDC DEM than in the DCW/USGS DEM, probably
a result of the “minimalist” approach to interpolation and the relatively dense network of points in
the AUSLIG source data set. Where a 30" grid cell had an elevation assigned from the AUSLIG
source file, NGDC’s procedure accepted that value. Since there are over five million source data
points for ten million square km of Australia, slightly over half of the 30" grid cells were already
assigned elevation values (usually in multiples of 20 or 50 meters).
Local histograms are smoother in areas with coarser-spaced AUSLIG source points, where interpolated
points are more numerous than source points. The contour interval is coarser in the DCW/USGS
DEM, consistent with the coarser scale of the DCW source materials.
Other assessments: Australia is unique in GLOBE Version 1.0. It has two DEMs: a completely
unrestricted DEM derived (as described in Section 5.A.vii) from Digital Chart of the World contours,
and a DEM derived by NGDC and licensed by AUSLIG from its source materials. Comparing the
two DEMs to Operational Navigation Charts (ONCs, the source materials for DCW) yields some
interesting features.
For example, in South Australia, west of Port Augusta, the ONC graphically depicts (via shading
patterns) a large dune field. However, the dune field has only a very modest influence on the topographic
contours in that area, as the contour interval is rather course on ONCs. The DCW DEM almost
completely misses the dune field. The AUSLIG DEM shows the dune field in good detail since
contour intervals and supplemental point elevations are of sufficient resolution. However, individual
dunes within the dune field, sketched (probably slightly stylistically) on the ONC, appear to be too
subtle for the contour interval on the AUSLIG maps used to make the point data base. This suggests
that the 30" GLOBE DEM is of appropriate resolution for the AUSLIG source materials.
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41
5.A.iii. DEM for Japan
Primary Developer: Geographical Survey Institute (GSI)
Title: 30" DEM for Japan
Publication Date: 1995
Bibliographic Citation: * Geographical Survey Institute, 1995. 30 Arc-second Digital
Elevation Model of Japan. Geographical Survey Institute, Tsukuba,
Japan (in GLOBE Task Team and others, 1999).
Post-processing: None
Source/Lineage Category: 9
*
Primary reference citation for all data from this source
The Geographical Survey Institute (GSI) of Japan has two series of DEMs: a 50-meter grid based on
1:25,000-scale maps (in progress), and a 250-meter grid also based on 1:25,000-scale maps
(completed). The data are in Japan’s standard projection. The horizontal datum is the Tokyo datum;
the vertical datum is mean sea level of Tokyo Bay. Both versions are copyright, based on the Survey
Law in Japan.
The Digital Map 250m Grid Elevation data set was produced by manually measuring elevation values
at approximately 250m intervals from 1:25,000 scale topographic maps. The actual intervals were
11.25 arc-seconds of longitude and 7.5 arc-seconds in latitude. These intervals correspond to a 40 x
40 division of one 1:25,000-scale GSI Topographic Map sheet, which covers 7.5 minutes in longitude
and 5 minutes in latitude. The contour interval of these source maps is 10 meters. The source maps
were derived from 1:40,000-scale stereoscopic aerial photographs, using 9 inch (23cm) film size and
a lens of 6-inch (150mm) focal length, and using traditional stereoplotting techniques. Japan has
large amounts of mountainous terrain, and about 65% of the land surface is forested. However,
experienced operators are skilled at recreating the ground surface elevation despite these obstacles.
GSI reprojected and resampled the Digital Map 250m Grid Elevation data to WGS84 horizontal
datum, with vertical datum kept at mean sea level (for Tokyo Bay), and averaged the resultant 11.25"
x 7.5" data to a 30" latitude-longitude grid. It considers the vertical accuracy to be 5–10m RMSE.
GSI contributed these data for unrestricted use by the international scientific community, giving a
copy to NGDC for GLOBE.
Cell-centered registration, mean of source 7.5” x 11.25” grid cells
in output 30” cell.
Graphic describing georeferencing and sampling for the DEM for Japan.
Global Land One-kilometer Base Elevation
42
Plates 14 and 15 both show the DEM for Japan; with linear and semi-logarithmic scaling, respectively.
Surprisingly, for data derived from cartographic sources, a histogram of this DEM is almost unnaturally
smooth, and is linear between 200m and 2900m. It shows only one prominent spike, at 85m. This
spike corresponds to Lake Biwa, just northeast of Kyoto. This suggests a very dense distribution of
contours, little “artistic license” taken in creating the original map contours from source materials,
and highly appropriate “contour-to-grid” conversion techniques in making the DEM from the
cartographic source.
There appear to be a few, very subtle, breaks in topographic style in a pattern that suggests edge
effects in source maps, or in contour-to-grid creation of the DEM. These may reflect subtle
discontinuities in horizontal or vertical datum that affected the data when reprojected. GSI notes that
slight initial discrepancies occur during the production of topographic maps, but that these are adjusted
to ensure continuity between sheets (and thus in DEMs derived from them).
5.A.iv. DEM for Italy
Primary Developers: Servizio Geologico Nazionale (SGN) and National Geophysical
Data Center (NGDC)
Title: 30" DEM for Italy
Publication Date: 1994
Bibliographic Citations: Carrozzo, M.T., D. Luzio, C. Margiotta, T. Quarta, F. Zuanni, A.
Chirenti, and A.M. Tundo, 1985. Data base of mean height values
for the whole Italian landmass and surrounding areas: determining
and statistical analysis. Bollettino di Geodesia e Science Affini, No.
1, 1985, pp. 38–56.
* Servizio Geological Nazionale and Row, L.W., 1994. 30 Arc-second
Digital Elevation Model for Italy, in Row and Hastings, 1994 (in
GLOBE Task Team and others, 1999).
Post-processing: None. This DEM was originally created for TerrainBase.
Source/Lineage Category: 10
*
Primary reference citation for all data from this source
The DEM for Italy was derived at NGDC, from a 7.5x10-second DEM developed by the Servizio
Geologico Nazionale (SGN) of Italy. This section summarizes documentation prepared by Row and
others (1995, pp. 4-91 through 4-95) for TerrainBase (Row and Hastings, 1994), and is also described
by Carrozzo and others (1985).
The 7.5x10-second DEM developed by SGN was developed for use in gravity terrain corrections.
Organizations involved with either developing, analyzing, or financing the data set included AGIP (a
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major petroleum company in Italy), the National Research Council, National Group of Solid Earth
Geophysicists (GNGTS), Ministry of Education (MPI), and the University of Lecce. Source materials
included several topographic map sources cited in Row and others (1995), at scales of 1:25,000 to
1:50,000 for land, plus hydrographic maps at 1:100,000.
Mean height values were manually extracted from the topographic maps at regular grid intervals.
The size of the grid was selected to maximize the amount of reliable detail obtainable from the
source maps, while keeping the resolution from becoming so fine as to overly burden the developers.
Grid spacings of 7.5x10 seconds were used for 1:25,000 scale maps, 15x20 seconds for 1:50,000
maps, and 30x40 seconds for the 1:100,000 scale maps. A map of sources is presented in Carrozzo
and others (1985), and reproduced in Row and others (1995, p. 4-94).
Grid lines were printed on transparent acrylic sheets in 20-minute latitude sections, and overlain on
the maps to guide data collection. For each grid cell, a mean height was manually estimated from the
contours and point heights that appeared within and adjacent to each cell.
The 6,210,000 elevation values were derived from 3450 maps, 1,878,000 heights in coastal regions
from 130 coastal maps, and 3,456,000 depth values from 120 maps. The coarser grids were then
interpolated to 7.5x10-second gridding by an undocumented technique. SGN then tiled the data into
20x30-minute areas.
Data were analyzed for errors by SGN using the following procedures:
1. SGN checked that data were expressed in proper metric terms, and that they were intrinsically
valid. SGN verified that the data fell within a predetermined range of values for the area
under consideration.
2. SGN checked the slope at each cell by testing whether the difference between each cell and
its neighbors did not exceed a threshold value as determined by the type of local terrain.
3. SGN spot-checked data by independently collecting data from various cells twice. SGN then
verified that the two values did not differ beyond predetermined values, based on the local
terrain.
4. SGN generated contour maps from the gridded data in each area, and overlaid these on the
source maps for comparison.
5. SGN generated contour maps from several adjacent areas, and overlaid these on 1:100,000-
scale source maps, to confirm proper edge matching between processed areas.
SGN and NGDC jointly developed a method for compiling these proprietary data into an unrestricted
30" grid. According to this method, NGDC computed the mean value of all 7.5x10-second grid
values contained in each 30" output grid cell. Areas containing significant errors were removed from
the model (these were filled by NIMA DTED Level 0 discrete values during the patching process
making GLOBE Version 1.0).
Global Land One-kilometer Base Elevation
44
Cell-centered registration, mean of source 7.5” x 10” grid cells in an
output 30” grid.
Graphic describing georeferencing and sampling for the DEM for
Italy.
Plates 16 and 17 are histograms for the DEM of Italy, on linear and semi-logarithmic scales,
respectively. There is a trough in the histogram for elevations below 80m in the SGN DEM, a broad
peak at about 70m to 200m (the elevations of the lakes in the Italian Alps), and modest spikes at
about 400m and 440m. Otherwise, the histogram is relatively smooth. The semi-logarithmic plot
shown is not quite linear between 100m and 2000m elevation. Then a modest bulge occurs at about
2500m, with a rapid diminution of elevation values above about 2800m. This DEM is not quite so
smooth as the GSI DEM for Japan. Nevertheless, it is unusually free of spikes, considering its
cartographic source.
5.A.v. DEM for New Zealand
Primary Developer: Manaaki Whenua Landcare Research, Ltd. (LCR)
Title: DEM for New Zealand
Publication Date: 1996
Bibliographic Citation: * Manaaki Whenua Landcare Research, 1996. 500-metre Digital
Elevation Model for New Zealand. Manaaki Whenua Landcare
Research, Ltd., Lincoln, New Zealand (in USGS, 1997; also in
GLOBE Task Team and others, 1999).
Post-processing: U.S. Geological Survey (for GTOPO30).
Source/Lineage Category: 11
*
Primary reference citation for all data from this source
Manaaki Whenua Landcare Research, Ltd. (LCR), contributed a DEM with a 500m horizontal grid
spacing for New Zealand to USGS for GTOPO30. This map was in New Zealand’s national projection.
The DEM was adapted from elevation information on 1:63,360-scale maps (e.g. 1 inch = 1 mile
scale). The source maps have a 30m (100ft) contour interval.
The original projection is described as follows:
Method of projection: Modified Cylindrical. A sixth-order conformal modification of a Mercator
using the International spheroid.
Points of tangency: 41°00' South, 173°00' East.
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Linear graticules: None.
Properties:
Shape: Conformal. Local shapes are correct.
Area: Minimal distortion, less than 0.04 percent for New Zealand.
Direction: Minimal distortion within New Zealand.
Distance: Scale is within 0.02 percent of true scale for New Zealand.
Limitations: Projection not useful for areas outside New Zealand.
USGS reprojected the data to 30" latitude-longitude projection using bilinear resampling.
Cell-centered registration, bilinear resampling of source 500m grid.
Graphic describing georeferencing and sampling for the DEM for New
Zealand.
Plates 18 and 19 show spikes at approximately 30m (100ft) intervals below 606m (2000ft). There are
additional spikes at about 750m (2500ft) and 900m (3000ft). Above that elevation, the histograms
are relatively smooth. This suggests that the vertical granularity of the source maps may be more
appropriate at higher elevations than for lower elevations. Nevertheless, the DEM is of relatively
high quality for one apparently derived from cartographic sources. There is a modest trough in values
between 100m and 150m.
5.A.vi. DEM for Greenland
Primary Developers: H. Jay Zwally and Robert A. Bindschadler (NASA Goddard Space
Flight Center), Anita Brenner and John DiMarzio (Hughes STX)
for the Oceans and Ice Branch of the Laboratory for Hydrospheric
Physics, NASA/Goddard Space Flight Center.
Title: DEM for Greenland from GEOSAT Altimetry
Publication Date: 1997
Bibliographic Citations: National Snow and Ice Data Center (NSIDC), 1997. SEASAT and
GEOSAT Altimetry Data for the Antarctic and Greenland Ice Sheets.
University of Colorado, National Snow and Ice Data Center,
Boulder, Colorado. (CD-ROM)
** Zwally, H. Jay, Anita C. Brenner, John DiMarzio, and Robert A.
Birndschadler, 1997. DEM of Greenland from GEOSAT Altimetry
(in NSIDC, 1997).
Global Land One-kilometer Base Elevation
46
Zwally, H. Jay, A.C. Brenner, J.A. Major, T.V. Martin, and R.A.
Bindschadler, 1990. Satellite radar altimetry over ice. Volume 1,
Processing and Corrections of SEASAT Data over Greenland.
NASA Reference Publication 1:1233.
Zwally, H. Jay, Judith A. Major, Anita C. Brenner, Robert A.
Bindschadler, and Thomas V. Martin, 1990. Satellite radar altimetry
over ice. Volume 2, Users’ Guide for Greenland Elevation Data
from SEASAT. NASA Reference Publication 2:1233.
Post-processing: Jet Propulsion Laboratory (JPL) for the Multiangle Imaging Spectro-
Radiometer DEM.
Post-processing (Step 2): National Oceanic and Atmospheric Administration (for GLOBE).
Bibliographic Citation * Bryant, Nevin, Richard Fretz, Niles Ritter, and Rafael Alanis, 1995.
for Post-processed DEM: JPL/MISR 30 Arc-second Digital Elevation Model. Jet Propulsion
Laboratory, Pasadena, California.
Source/Lineage Category: 12 (and partly 13)
Note: The best current DEM for Greenland is a hybrid of this DEM, DTED,
and DCW-based contours as described below and in Section 5.B.i.d.
*
Primary reference citation for all data from this source
** Definitive citation of GEOSAT data source
There is only limited DTED coverage for Greenland. Where available, these data were used.
For other areas, several DEMs have been created using SEASAT, GEOSAT, and ERS-1 satellite
altimetry. These data provide closely spaced spot measurements of the distance between the satellite
platform carrying the altimeter. These measurements undergo various corrections and calibrations to
produce spot measurements of elevation. Statistical processes may be used to reduce noise where
measurement densities are sufficiently high. The resultant spot measurements are then interpolated
into elevation grids (e.g. DEMs). The only version of such data that we have evaluated enough to use
is this contribution based on GEOSAT data (see two paragraphs below). Further improvements of
altimetry-based data are anticipated.
Alternatively, Operational Navigation Charts, upon which DCW was based, provide topographic
contours south of about 72
o
N latitude. North of that latitude, contours exist in some coastal areas,
with inland areas having only a sparse collection of point elevations apparently collected on traverses.
USGS used DCW to create its DEM of Greenland, except where DTED was available.
Another DEM was created from GEOSAT altimetry by Zwally and others (NSIDC, 1997; see list
under “Primary Developers,” above). This was provided to the MISR/JPL DEM project, in support
of the NASA EOS Multiangle Imaging SpectroRadiometer mission, by GLOBE Task Team member
J.-P. Muller. The original DEM had 10 km gridding, but was resampled to 30” by JPL for use in the
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47
MISR mission. (Further documentation is available from NSIDC at http://www-nsidc.colorado.edu.)
North of 72
o
N latitude, JPL used Digital Chart of the World contours to create a gridded DEM.
Cell-centered registration at lower resolution; value replicated from
10km grid for Greenland.
Graphic describing georeferencing and sampling for the Zwally (and
others)/NSIDC/JPL data for Greenland
Plate 20 only incorporates data for the area of the original Zwally (and others)/NSIDC/JPL DEM
ultimately used in GLOBE. As that area is dominated by the Greenland Ice Sheet, it is not surprising
that the histogram is dominated by elevations of 2000–3000m. Note that this DEM is dissimilar from
other DEMs in GLOBE, as are its sources. Further assessment may follow in future versions of
GLOBE, after other candidate DEMs from altimetric sources are assembled and analyzed.
Plate 21 shows the two-degree wide blend zone between the data contributed by JPL and those from
DCW and DTED in Greenland. The histogram shows that dominant elevations are about 2000m in
this area off the center of the ice cap.
NGDC’s assessment of NIMA DTED, USGS, and Zwally (and others)/NSIDC/JPL DEMs suggested
that NIMA DTED were preferred where available. The USGS model was preferred in many coastal
areas in the south, southeast and southwest, where DCW hypsography was relatively detailed. However,
in the interior, even south of 72
o
latitude where DCW contours were fairly detailed, the Zwally (and
others)/NSIDC/JPL DEM appeared preferable.
It was suggested by J.-P. Muller of University College London (Geomatic Engineering Department)
that even where DCW contours existed on the Greenland Ice Sheet, that they were not necessarily
very accurate compared to the NSIDC model. Inspection at NGDC for terrain-like characteristics in
the two DEMs supported this assessment. The Zwally (and others)/NSIDC/JPL DEM was thus
preferred primarily at higher latitudes and inland. At these latitudes, this DEM appeared to overrun
coastlines in some areas, perhaps because the satellite altimetry gave readings on ice features (and
thus considered land by that model, whereas World Vector Shoreline (WVS) coastlines considered
some of these areas to be oceanic).
Therefore, NGDC mosaicked a DEM for Greenland based on the following priorities:
1. DTED-based 30" data where available.
2. USGS/GTOPO30 data based on DCW, where DCW contained sufficient detail (generally
southerly near-coastal areas not characterized by substantially permanent ice).
3. Zwally (and others)/NSIDC/JPL data in other areas (generally in the interior of Greenland,
and in northerly coastal areas characterized by substantially permanent ice).
4. NGDC performed a linear transition between the Zwally (and others)/NSIDC/JPL DEM and
Global Land One-kilometer Base Elevation
48
the DCW-based DEM, over a two-degree wide zone. This transition is category 13 in the
source/lineage map.
5. In some northern coastal areas characterized by substantially permanent ice, USGS/GTOPO30
values sometimes extended oceanward of the limit of Zwally (and others)/NSIDC/JPL
coverage. In this case, the USGS/GTOPO30 data were used. In some other areas, Zwally
(and others)/NSIDC/JPL values sometimes extended oceanward of USGS/GTOPO30 data
coverage, which was limited by a selection of DCW and WVS coastlines. In such cases, the
coastlines used by USGS/GTOPO30 were accepted, thus masking out Zwally (and others)/
NSIDC/JPL elevations in areas considered oceanic by USGS/GTOPO30.
5.A.vii. Digital Chart of the World
Primary Developer: Defense Mapping Agency (now National Imagery and Mapping
Agency)
Title: Digital Chart of the World
Publication Date: 1992
Bibliographic Citation:** Defense Mapping Agency (DMA), 1992. Digital Chart of the World.
Defense Mapping Agency, Fairfax, Virginia. (Four CD-ROMs.)
Post-processing: U.S. Geological Survey (USGS) for GTOPO30.
Bibliographic Citation * DMA and USGS, 1996. 30" DEM from Digital Chart of the World
for Post-processed DEM: (in USGS, ed., 1997).
Source/Lineage Category: 14
*
Primary reference citation for all data from this source
** Primary reference citation for Digital Chart of the World
Digital Chart of the World (DCW) is a vector cartographic data set based largely on the 1:1,000,000-
scale Operational Navigation Chart (ONC) series of aircraft navigation charts. ONC has been cited
as the largest scale base map source with global coverage (Danko, 1992). ONCs were products of the
Army Mapping Service (AMS), then DMA, now National Imagery and Mapping Agency (NIMA).
They were based on photogrammetric analyses of Department of Defense Corona imagery acquired
in the 1960s.
ONCs contain vector base map information such as political boundaries, transportation infrastructure,
waterways, and coastlines, as well as raster-like shading for selected categories of land cover type.
The objective of this information is to facilitate navigation by pilots. In addition, for much (but not
all) of the world, ONCs contain topographic contours. The primary contour interval is 1000ft (305m),
with supplemental contours at 250ft (76m) intervals in areas below 1000ft elevations. Limited
supplemental contours at 500ft (152m) intervals exist above 1000ft elevations.
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Point elevations also appear in ONCs, often at airports, cities, or topographic features such as selected
mountain peaks. In addition, some lake surfaces are labeled with typical elevations. In many areas
lacking topographic contours, sparse point elevations are still available.
ONCs (and DCW, which is derived from ONCs) use World Geodetic System 84 (WGS84) for horizontal
reference, and Mean Sea Level as vertical reference. However, this may not always be the case, as
cartographic sources (for example) may not be completely or accurately described, and materials
from such sources may not be accurately converted to WGS84 and Mean Sea Level.
In the late 1980s, DMA instigated a design and contracting process to digitize the contents of ONCs.
The work was contracted to a private company. The resultant data base occupies four CD-ROMs,
which is distributed by USGS for DMA.
Absolute horizontal accuracy of the DCW hypsography is reported to be 2040m rounded to the
nearest 5m at 90% circular error. Vertical accuracy is considered to be 610m for contours, and 30m
for spot elevations (DMA, 1990).
Errors can exceed such figures locally. For example, the ONC for northern Greenland contains notices
such as: “CAUTION: Arctic Institute of North America Project Nord (Control Data Corp.) indicates
position discrepancies in excess of 11 nautical miles (Nov. 68).”
Topographic contours and point elevations are the primary data for deriving DEMs from DCW.
Supplementary data include drainage information. Streams were used to guide the contour-to-grid
process using the ANUDEM program of Hutchinson (1989, 1996). Lake shorelines and ocean
coastlines provide further guidance.
DCW was used as the primary source for filling gaps in the DTED coverage, including all of the
unrestricted DEM for Australia, and large areas of Africa, South America, and Canada. University
College London was active in early development of DCW conversion techniques. The Jet Propulsion
Laboratory used contour-to-grid techniques to make much of its 30" DEM noted in Section 1 and in
Section 5.A.vi. However, all of DCW contour-to-grid data used in GLOBE were produced by USGS.
The following is USGS, 1997b, description of its vector data processing techniques. These apply to
DCW, as well as the other cartographic source materials listed in Sections 5.A.viii to 5.A.xi:
“The topographic information from the vector cartographic sources, including the
DCW, the ADD [Antarctic Digital Database], and the Army Map Service, International
Map of the World, and Peru 1:1,000,000-scale maps, was converted into elevation
grids through a vector-to-raster gridding approach. Contours, spot heights, stream
lines, lake shorelines, and ocean coastlines were input to the ANUDEM surface
gridding program developed at the Australian National University (Hutchinson, 1989).
ANUDEM, specifically designed for creating DEM’s [sic] from digital contour, spot
height, and stream line data, employs an approach known as drainage enforcement to
produce raster elevation models that represent more closely the actual terrain surface
and contain fewer artifacts than those produced with more general purpose surface
Global Land One-kilometer Base Elevation
50
interpolation routines. Drainage enforcement was performed for all areas covered by
vector source data except Antarctica and Greenland.
A significant amount of preprocessing was required to prepare and format the vector
source data for input to ANUDEM. This processing included editing and updating
the vector stream lines so that the direction of each was oriented downstream (a
requirement of ANUDEM). Further preprocessing involved detection and correction
of erroneous contour and point elevations (Larson, 1996). Ocean coastlines were
assigned an elevation of zero for input as contours. Also, shorelines of lakes for
which the DCW included elevations were tagged and used as contour input. The
output from ANUDEM was an elevation model grid referenced in the same horizontal
coordinate system as the generalized raster source data. The output grid spacing of
30 arc-seconds has been shown to be appropriate for the information content present
in the DCW hypsography layers (Hutchinson, 1996; Shih and Chiu, 1996).”
The following passage is from another part of USGS (1997b):
“Prior to merging with the generalized raster data, lakes for which the DCW did not
indicate an elevation were updated on the DCW grid with the lowest grid cell elevation
found along the shoreline. When each of the vector sources was gridded, an overlap
area with the adjacent raster sources was included so that smoothing could be
performed to minimize the elevation discrepancies among the sources. Also, additional
point control was input into the ANUDEM gridding process so interpolated elevations
in the overlap region would more closely match the raster source elevations. The
additional control was derived from the generalized raster sources within a 1-degree
buffer surrounding the vector source areas.”
Cell-centered registration; contour-to-grid value computed.
Graphic describing georeferencing and sampling for DCW
conversion.
Analysis of Histograms: As the Digital Chart of the World was the source for about 23% of GLOBE,
we performed histogram analyses on DEMs from DCW for the same areas as NIMA discrete data.
Note that only data used in GLOBE were run through the histogramming process, so DTED- and
DCW-based histograms should be different.
n Africa/Europe: Plate 22 plots DCW coverage of Africa and Europe (0
o
to 60
o
N latitude and
0
o
to 60
o
E longitude) is largely similar to that of DTED discrete data for the same region. A
similar trough at low elevations (including some elevations below sea level), peak about
450m, and gradual quasi-linear decline to 4500m is apparent. The DCW-based DEM is,
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however, punctuated by spikes at approximately 300m (1000ft) intervals, with subsidiary
spikes at lower elevations, as might be expected from its source, Operational Navigation
Charts. A spike at 1200m is superimposed upon the broader peak at the same elevation that
is more apparent in the histogram of DTED discrete for Africa and Europe. However, that
elevation appears to exhibit a slightly more pronounced peak around 1200m in the DCW-
derived DEM, as well.
n Asia: Plate 23 plots DCW coverage for Asia (between 0
o
to 90
o
N latitude and 60
o
to 180
o
E
longitude) shows a similar pattern of steady decrease in frequency of occurrence, with a
broad peak about 5000m elevation. As for Asia, the DCW-based DEM shows prominent
spikes at 300m increments, with spikes at subsidiary contour intervals for lower elevations.
n North America: A similar broad pattern to that shown for DTED discrete data for North
America is apparent in Plate 24. Spiking at contour intervals in source maps (with associated
broader peaks probably derived in gridding) is typical of this series of DCW-based DEMs.
There appear to be fewer higher elevations than in Plate 4, as might be expected considering
the coverage of these data.
n South America: In Plate 25, the DCW-based DEM has a similar pattern to that of DTED
discrete data, with the superposition of more spikes (at about 300m increments, with
intermediate spikes at lower elevations). The broad peak at 4000–5000m apparent in the
DTED-based data is not so apparent in the DCW-based DEM. This is because the Altiplano
is covered more by DTED (and, to a lesser degree, by AMS and Peruvian maps) than by
DCW.
5.A.viii. Maps for Parts of Asia and South America
Primary Developer: Army Map Service (now National Imagery and Mapping Agency)
Title: Maps
Publication Date: 1950s and 1960s
Bibliographic Citations: Army Map Service (AMS), various dates. South America
1:1,000,000. World (South America) 1:1,000,000. World (South
Pacific) 1:1,000,000. East Indies 1:1,000,000. Army Map Service,
Washington, D.C. (Map series, with global coverage but various
regional names, consistent with International Map of the World
specifications.)
U.S. Army Topographic Command (USATC), various dates. World
(South America) 1:1,000,000. U.S. Army Topographic Command,
Washington, D.C. (Map series consistent with International Map of
the World specifications.)
Global Land One-kilometer Base Elevation
52
Defense Mapping Agency (DMA), various dates. World (Asia)
1:1,000,000. Defense Mapping Agency Topographic Center,
Washington, D.C. (Map series consistent with International Map of
the World specifications.)
Post-processing: Geographical Survey Institute (GSI, Japan) and U.S. Geological
Survey (for GTOPO30).
Bibliographic Citation * AMS, GSI, and USGS, 1997. 30"-gridded DEMs from AMS Maps.
for Post-processed DEM: USGS, EROS Data Center, Sioux Falls, South Dakota.
Source/Lineage Category: 15
*
Primary reference citation for this source
Paper maps at a scale of 1:1,000,000 produced by the Army Map Service (AMS) were acquired and
digitized by the Geographical Survey Institute of Japan. Contours (with intervals of 100, 150, 300,
and 500 meters), spot heights, drainage lines, and coastlines for some islands of southeast Asia and
some small areas in South America were delivered to USGS as digital vector cartographic data sets.
USGS used ANUDEM-based contour-to-grid techniques to create DEMs from these digitized map
areas. That procedure is described in Section 5.A.vii.
Cell-centered registration; contour-to-grid value computed.
Graphic describing georeferencing and sampling for AMS map
conversion.
Histogram analysis of AMS maps divides the source into maps for South America (Plate 26) and for
Asia (Plate 27). Plate 26 shows prominent sharp spikes and broader peaks at about 150m, 200m,
500m, and 1000m increments. This suggests relatively sparse contour information.
Plate 27 shows prominent sharp spikes and broader peaks at approximately 300m and 500m increments,
plus at 100m, 150m, and 200m. This suggests a combination of contour values in 1000ft and 500m
increments, with subsidiary contour values at lower elevations. It also suggests relatively sparse
contour information.
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5.A.ix. Maps for Part of Brazil
Primary Developer: Instituto Brasiliero de Geografia e Estatistica
Title: Maps for the International Map of the World on the Millionth Scale
Publication Date: Various, 1970s and 1980s.
Bibliographic Citation: Instituto Brasiliero de Geografia e Estatistica (IBGE), various dates.
Carta Internacional do Mundo, ao Milionesimo. Instituto Brasiliero
de Geografia e Estatistica, Rio de Janeiro, Brazil. (Physical,
including topographic, maps of the world on a scale of 1:1,000,000;
sheets covering Brazil.)
Post-processing: Geographical Survey Institute (GSI, Japan), and U.S. Geological
Survey (USGS) for GTOPO30.
Bibliographic Citation * IBGE, GSI, and USGS, 1997. 30"-gridded DEMs from IBGE Maps.
for Post-processed DEM: USGS, EROS Data Center, Sioux Falls, South Dakota.
Source/Lineage Category: 16
*
Primary reference citation for this source
The International Map of the World (IMW) on the Millionth Scale project was created in 1913, when
a number of national and other cartographic agencies joined to form the Central Bureau of the IMW.
In 1953, IMW activities were transferred to the Secretariat of the United Nations (UNO, 1973).
The IMW project sets standards for presentation of such maps, to increase uniformity of content and
presentation. Actual maps are produced by many public (and a few private) organizations. The maps
used in this instance were produced by Instituto Brasiliero de Geografia e Estatistica (IBGE), the
Brazilian Institute of Geography and Statistics, which has a program for 10-yearly updates to maps in
this series. This forms Brazil’s 1:1,000,000 topographic map series, designed to be compatible with
IMW standards.
Paper maps from this series were adapted for digitizing, then digitized by the Geographical Survey
Institute of Japan to provide source data for the Amazon basin and adjacent areas. The maps used for
this project had a 100-meter contour interval. USGS used ANUDEM-based contour-to-grid techniques
to create DEMs from these digitized map areas. That procedure is described in Section 5.A.vii.
Cell-centered registration; contour-to-grid value computed.
Graphic describing georeferencing and sampling for IMW map
conversion.
Global Land One-kilometer Base Elevation
54
Plate 28 shows sharp spikes and broader peaks occurring at 100m increments below 1000m. There is
also a separate spike at 1200m, spikes at 500m increments to 3000m, and at 1000m increments above
3000m, suggesting these are contour values in the original source maps. The histogram shows a
proportionately large amount of coverage around 4000m elevation.
5.A.x. Map for Part of Peru
Primary Developer: Ministerio de Guerra, Peru
Title: Mapa Fisico Politico del Peru
Publication Date: 1984
Bibliographic Citation: Ministerio de Guerra, 1984. Mapa Fisico Politico del Peru.
Ministerio de Guerra, Lima, Peru.
Post-processing: Geographical Survey Institute (GSI, Japan) and U.S. Geological
Survey (USGS) for GTOPO30.
Bibliographic Citation * Ministerio de Guerra, GSI and USGS, 1997. 30"-gridded DEM from
for Post-processed DEM: Peruvian Maps. USGS, EROS Data Center, Sioux Falls, South
Dakota.
Source/Lineage Category: 17
*
Primary reference citation for this source
Small areas of a 1:1,000,000-scale map, entitled Ministerio de Guerra Mapa Fisico Politico del
Peru, produced in 1984, were adapted for digitizing to fill gaps in source data for South America.
The map had a contour interval of 1000 meters. Digitizing was done by the Geographical Survey
Institute of Japan.
USGS used ANUDEM-based contour-to-grid techniques to create DEMs from these digitized map
areas. That procedure is described in Section 5.A.vii.
Cell-centered registration; contour-to-grid value computed.
Graphic describing georeferencing and sampling for Peru map
conversion.
Plate 29 has broad peaks and sharp spikes at increments of 1000m, with a subsidiary peak/spike at
500m, and few values below 400m. The latter is consistent with the coverage of this data set, which
includes no coastal areas.
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5.A.xi. Antarctic Digital Database
Primary Developer: Scientific Committee for Antarctic Research
Title: Antarctic Digital Database
Publication Date: 1993
Bibliographic Citation: Scientific Committee for Antarctic Research, 1993. Antarctic Digital
Database on CD-ROM. Scott Polar Research Institute, Cambridge,
England.
Post-processing: U.S. Geological Survey (for GTOPO30); NOAA/National
Geophysical Data Center (for GLOBE).
Bibliographic Citation * USGS, 1996b. 30 Arc-second-gridded Digital Elevation Model
for Post-processed DEM: Derived from the Antarctic Digital Database (SCAR, 1993). USGS,
EROS Data Center, Sioux Falls, South Dakota. (In USGS, 1997;
also in GLOBE Task Team and others, 1999.)
** Hastings, David A., and Paula K. Dunbar, 1999. Global Land One-
kilometer Base Elevation (GLOBE) Digital Elevation Model,
Documentation, Volume 1.0. KGRD 34, NOAA, National
Geophysical Data Center, Boulder, Colorado, pp. 55-56.
Source/Lineage Category: 18
*
Primary reference citation for this source
** Reference citation noting repairs to data from this source
The Antarctic Digital Database (ADD) was produced under the auspices of the Scientific Committee
on Antarctic Research (SCAR). This project compiled topographic contour maps from eleven nations
into one collection. ADD vector data were compiled from maps ranging in scale from 1:200,000 to
1:5,000,000.
The detail, density, and interval of the contours in ADD vary widely, with the more detailed data near
the coastline and very generalized data in the interior of the continent. The coastline was updated
using 1:1,000,000-scale satellite images. Detailed documentation and metadata provided in ADD
identifies the map scale from which each contour line was extracted. The data base is available on
CD-ROM.
Digital contours and coastlines from ADD were used as source material for Antarctica. They were
converted to DEMs at USGS, using contour-to-grid techniques. That procedure is described in Section
5.A.vii.
GLOBE quality control detected edge-effect errors in the USGS adaptation of ADD. The westernmost
column bordering on 180
o
W longitude, easternmost two columns, and southernmost row bordering
on the South Pole contained nominal flag values instead of actual elevations. These errors were
corrected by NGDC for GLOBE.
Global Land One-kilometer Base Elevation
56
Cell-centered registration; contour-to-grid value computed.
Graphic describing georeferencing and sampling for ADD conversion.
Plate 30 shows a broad peak about 3000m elevation, typical for ice caps. The precipitous drop in the
histogram at 4050m, with very few elevation values trailing off to about 4700m is notable, as is the
modest trough in values between 0 and 200m elevation. Spikes at every 100m of elevation from
200m through 4000m suggests 100m contour intervals for significant parts of the map. However, the
data base is documented as having various horizontal scales and levels of contour detail.
There are several DEMs and spot elevation data sets derived from satellite altimetry for Antarctica.
Several of these are being evaluated for future versions of GLOBE.
5.B. Assembly of GLOBE Version 1.0
DEMs from various sources were merged several times during the life of the GLOBE project:
1. Twenty-six DEMs and Digital Bathymetric Models from various sources were merged at
NGDC to form TerrainBase. TerrainBase was primarily a lower-resolution data set. However,
DEMs for the U.S. and environs, and for Italy, were available at 30" gridding for GLOBE.
2. DEMs for various sources were merged at JPL for its MISR DEM. The JPL contribution to
GLOBE consists of coverage of Greenland, where DTED are not available.
3. DEMs from many sources were merged by USGS, during the creation of its GTOPO30.
These merges included USGS’s selection of its preferred raster-derived DEMs, then its
selection of preferred DEMs from cartographic sources. The following text is USGS’s (1997b)
description of its process of “learning as the project progresses”:
“GTOPO30 was developed over a 3 year period during which continental
and regional areas were produced individually. As such, processing techniques
were developed and refined throughout the duration of the project. Although
the techniques used for the various continental areas are very similar, there
were some differences in approach due to varying source material. More details
about data development for several of the continental areas are reported by
Verdin and Greenlee (1996), Bliss and Olsen (1996), and Gesch and Larson
(1996).
Data processing was accomplished using commercially available geographic
information system software, public domain image processing software,
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vector-to-raster gridding software, and utilities developed specifically for this
project. To more efficiently handle the numerous input data sets and to
standardize the proper sequence of processing steps, the production procedures
were automated to a great extent by employing preset parameter values,
scripted command files, and consistent naming schemes for input and output
data files.”
The following is USGS’s (1997b) description of its merging of raster- and vector-derived
DEMs within GTOPO30:
“Merging of the generalized raster sources and the gridded vector sources
was accomplished by mosaicking the data sets. The generalized raster sources
had the highest priority so coverage of the data with the greater topographic
detail and accuracy was maximized. The grid derived from DCW data had
the highest priority among the vector sources, and the other digitized map
data was used when DCW hypsography was unavailable. The merging
procedure including blending of the generalized raster sources and the vector-
derived grids within an approximate 1-degree overlap area along the irregular
boundaries. The blending algorithm computes a weighted average with the
weights for each data source determined on a cell-by-cell basis according to
the cell’s proximity to the edges of the overlap area (Franke, 1982).
A final processing step performed on the mosaicked and blended product
involved “clipping out” the land (as defined by vector coastline data) and
setting the ocean areas to a constant background value. Use of vector coastline
data resulted in a more consistent portrayal of the land/ocean interface,
especially in areas where raster source data (which had an implied coastline)
met with vector source data. The DCW coastline was used to clip the following
areas: Africa, Eurasia, South America, Australia, New Zealand, Greenland,
and isolated ocean islands. The World Vector Shoreline (WVS), a vector
shoreline data set from NIMA, was used for North America, including Hawaii,
the Caribbean islands, and Central America. The islands of Borneo and
Sulawesi in southeast Asia were clipped with the coastline digitized from the
1:1,000,000-scale map source. Antarctica was defined by the coastline as
portrayed in the ADD.”
The following is USGS’s (1997b) description of its final data assembly to make GTOPO30:
“The global product was assembled from the continental and regional DEMs.
Several areas of overlap due to different production stages of the project were
addressed and eliminated, most notably between the Africa and Eurasia data
sets. The global source map was generated from masks of source data coverage,
and was verified to register with the DEM precisely. Finally, the entire data
set was packaged into tiles for easier electronic distribution.”
Categories 2, 3, 5–7, 11, and 14–18 in the GLOBE source/lineage map were originally compiled
by USGS into GTOPO30. (GTOPO30’s source map does not differentiate lineage, thus does
Global Land One-kilometer Base Elevation
58
not differentiate its various methods of handling data from DTED-based sources.) NGDC
reassembled the USGS/GTOPO30 tiles before assembling GLOBE. In addition, it edited the
USGS/GTOPO30 source file to represent the various methods of resampling used in GTOPO30
(that were not all documented in USGS’s source file). This last editing is representational, to
help make users aware of these resampling techniques. The actual boundaries depicted between
resampling techniques are estimates, based on verbal descriptions by USGS scientists.
4. The MISR and GTOPO30 DEMs were made by their creators to meet their own objectives.
Finally, NGDC selected and merged available data into GLOBE. This effort used DEMs
generated by Zwally (and others)/NSIDC/JPL for Greenland. Many parts of GTOPO30 were
used, including the DEM contribution for New Zealand, the SCAR vector data, and the maps
cooperatively selected and converted to DEMs by GSI and USGS. Additional input data
came from AUSLIG, GSI, NIMA, and SGN. The merging process is described below.
Please note that peer review for this merging continues. Future versions of GLOBE will incorporate
peer review comments. If appropriate, substitutions of data will be made.
5.B.i. Quality Assessment
5.B.i.a. Japan
Data coverage for Japan was available from GSI, NIMA and USGS/GTOPO30. The peer review
Web site for GLOBE notes that the data are all of relatively high quality. However, inspection of the
data for Japan helped to confirm independent peer review comments that the NIMA (DTED Level 0)
“mean” values are sometimes lower than the “minima.” Actual data values for all candidates tended
to disagree by very little. Shaded relief, slope, and aspect images appear nearly identical, as a rule.
However, the histograms of the GSI data were notably smooth, lacking the spikes common in DEMs
generated from cartographic sources (and which had typical spike patterns in the GTOPO30 and
NIMA versions). This suggests that a common artifact in DEMs developed from cartographic sources
was addressed more thoroughly in the GSI DEM of Japan than in any other DEM from such sources
ever seen by ourselves. The result is a DEM that has the smoothest distribution of elevations, and the
least “binning” favoring contour values of source maps, of any candidate DEM. Thus, the GSI DEM
was selected for Japan.
5.B.i.b. Italy
Data coverage for Italy was available from SGN/NGDC, NIMA and USGS/GTOPO30. (The latter
candidate had high-resolution SGN source materials, reprocessed as described in Section 5.A.iv by
NGDC to 30".)
Again, data from all candidates were of relatively high quality. However, histograms of the SGN data
showed significantly less spiking than those for NIMA and GTOPO30. Similarly, slope, aspect, and
shaded relief analyses showed that the SGN data were of somewhat higher quality at higher elevations,
but of much higher quality at lower elevations. This probably reflects a more detailed scale of SGN’s
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source materials, with smaller contour intervals than may have been used by NIMA to make DTED
Level 1 data. In the areas of the SGN/NGDC DEM that contained holes (see Section 5.A.iv), DTED
Level 0 discrete values were inserted. Thus, the SGN/NGDC DEM was selected for Italy, supplemented
where it had holes by DTED Level 0 discrete values.
5.B.i.c. Australia
Data coverage for Australia was available from AUSLIG/NGDC, USGS/GTOPO30, and JPL. The
AUSLIG data (see Section 5.A.ii) contain considerably higher level of detail, so were selected for the
“Best Available Data” (B.A.D.) version.
However, this version contains data copyrighted by, and licensed for, GLOBE distribution from
AUSLIG. As this version may present some difficulties for some users, an unrestricted “Globally
Only Open-access Data” (G.O.O.D.) alternative from GTOPO30 (see Section 5.A.vii) is also available.
Although accuracy assessments by University College London suggested that the JPL version may
have slightly greater overall absolute accuracy, that version contained specific areas with considerable
artifacts. It is possible that future versions of GLOBE may contain mosaics of JPL and USGS data.
Note that the land areas covered in the B.A.D. and G.O.O.D. versions of GLOBE differ slightly. This
is because the AUSLIG data coverage extends slightly into areas considered oceans by World Vector
Shoreline, which defined the limits of contour-to-grid conversion in the USGS DEM. Thus the
AUSLIG/NGDC DEM for Australia exhibits slightly greater land area in some areas than does the
USGS DEM for Australia.
The process that modified the land mask for the AUSLIG-based data is described in Section 5.A.ii.
5.B.i.d. Greenland
Data coverage for Greenland was available from Zwally (and others)/NSIDC/JPL and DCW, with
very limited NIMA coverage. A review by J.-P. Muller of University College London determined
that the JPL version compared much more favorably with available point elevation control (Muller
and Mandanayake, 1998a; Muller and others, 1998b). NGDC’s assessment of the DEMs suggested
that the Zwally (and others)/NSIDC/JPL DEM was best in the interior and northerly coastal areas
characterized by permanent ice. DCW (or DTED where available) was preferred in southerly coastal
areas.
NGDC scientists inspected Zwally (and others)/NSIDC/JPL, DCW, and DTED DEMs, to determine
which sources were preferable for which areas. Using inspection, a two-degree wide zone for linear
blending was created. The two DEMs were used equally in the middle of the zone. Weighting was
adjusted 4 percent every 5 minutes throughout the zone.
In very limited areas, the DCW coverage extends oceanward from the mosaicked DTED and Zwally
(and others)/NSIDC/JPL data. This is because of different interpretations of coastlines between the
three candidate DEMs in this area. Such differences in interpretation of coastline are common. They
Global Land One-kilometer Base Elevation
60
are especially common in polar areas where the edge seasonal or “permanent” ice may be accepted
as coastline in some data sets when it overlaps coasts onto the ocean, whereas other data sets discount
such ice features and attempt to determine the “dry land” coastline below such ice. In such areas, the
DCW data were patched into GLOBE Version 1.0.
In other limited areas, the Zwally (and others)/NSIDC/JPL DEM extended oceanward of the limits
of DCW or DTED coverage. In these cases, the coastal mask used in GTOPO30 data was honored by
GLOBE, so any Zwally (and others)/NSIDC/JPL DEM coverage coincident with this ocean mask
was not used in GLOBE.
Note that several alternative candidate data sets are available for Greenland. These are still under
evaluation, with further development being pursued. This may (or may not) result in improved coverage
for Greenland in a future version of GLOBE.
5.B.i.e. Antarctica
Data coverage for Antarctica was available from SCAR/USGS, via USGS/GTOPO30, and several
other candidates. The SCAR/USGS data set was originally compiled from various sources by SCAR,
then converted to 30" DEM grid by USGS as described in Section 5.A.xi. The data from other
candidates were not ready for peer review in time for GLOBE Version 1.0.
Though the quality assessment noted that improved alternatives are under development (e.g. Muller
and Mandanayake, 1998a), there was no assurance that such data would soon be available for public
distribution.
Quality assessment of the candidates favored the SCAR/USGS model, but also found edge effects in
that model (see Section 5.A.xi for discussion). The SCAR/USGS DEM, as repaired by NGDC, was
selected for Antarctica.
5.B.i.f. Conterminous United States and Vicinity
Data coverage for the conterminous United States and some neighboring areas was available from
AMS/DMA/NIMA sources, with several lineages:
n One 30" version was contributed directly from NIMA to NGDC for GLOBE. This version
(DTED Level 0) includes spot, minimum, mean, and maximum 3" values for each 30" grid
cell. However, independent peer review led to the discovery that the “mean” values were
frequently lower than the “minimum” values, and that the spot values appeared to be the
most accurate representative elevation values. These data are the newest and sometimes
contain revisions to source data since DMA contributed data to NGDC and to USGS.
n A second version for the conterminous U.S. was previously reprocessed to 30" by DMA and
contributed to NGDC for public distribution. This version was contributed to NGDC before
DTED Level 0 (noted above) was designed, but after the 3" (noted below) data were contributed
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to USGS. Thus, this DMA/NGDC data set may have benefited from enhancements to the
topographic data since DMA’s contribution to USGS. Both discrete (spot, nearest-neighbor)
and average data were contributed to NGDC. As the other data in the region used nearest-
neighbor resampling, the spot version of the DMA/NGDC data were considered more
appropriate for use in GLOBE Version 1.0.
n A third version at 3" gridding for most of the U.S. except Hawaii was contributed by DMA to
USGS for public distribution. (USGS calls this version “USGS 3-arc-second DEMs.”) This
was a pioneering DEM, perhaps the first gridded DEM ever developed. USGS resampled
these 3" data to 30" for inclusion into GTOPO30, using a nearest-neighbor technique. DMA/
NGDC data may have received editorial improvements, while NIMA/DTED Level 0 data
clearly (according to peer review input) have many such enhancements.
Because of the lineage of enhancements, NIMA/DTED Level 0 were selected where available. Second
priority went to DMA/NGDC data. Where neither of these data were available, DMA/USGS data
were used.
In several cases in coastal areas, NIMA discrete (spot) grid cells had values of 0 (sea level) where
NGDC or USGS data had values above zero. Inspection of these areas led to the observation that the
single 3" value sampled to make DTED Level 0 discrete data may have been zero, but the samples
used to make the NGDC and/or USGS versions were non-zero. In such cases, NGDC or USGS non-
zero values were allowed to replace sea level DTED Level 0 discrete values. A mask was built to
prevent inland values of zero elevation from being overwritten by subsequent non-sea-level values.
Non-sea-level values were allowed to overwrite values of zero elevation in near-coastal areas.
Inspection of the three candidate data sets in near-coastal and inland areas suggested this as the most
appropriate procedure for this version of GLOBE. The order of priority was (1) DTED Level 0
discrete value, (2) NGDC value if DTED Level 0 discrete value was zero or ocean mask value, and
(3) USGS/GTOPO30 value if the previous two sources were both zero or ocean mask values.
5.B.i.g. DTED within 50° of the Equator
Besides the areas noted above, DEMs within 50° of the Equator were available from NIMA (via
NIMA/DTED Level 0) and Manaaki Whenua Landcare Research, Ltd. (LCR) (via USGS/GTOPO30).
The coverage for New Zealand from LCR was the only one available at that resolution for New
Zealand, so was used in GLOBE. For areas where NIMA/DTED Level 0 data were available, the
discrete (spot) values were determined by independent review to be the most consistent and
representative values. Thus these were selected, where available, outside of coverage of Japan (GSI)
and Italy (SGN).
5.B.i.h. DTED Poleward of 50° North and South Latitudes
Besides areas noted above, DEMs poleward of 50° North and South latitude were available from
NIMA, via NIMA/DTED Level 0 and USGS/GTOPO30. DTED Level 0 was decimated at consistent
1/10 ratio from the original spatial resolution of DTED Level 1. (See the table in Section 5.A.i.a for
Global Land One-kilometer Base Elevation
62
specifics.) Data used in GTOPO30 were resampled to a consistent 30" by 30" grid spacing. Thus the
latter carry greater resolution poleward of 50° and were selected for GLOBE Version 1.0.
5.B.i.i. DCW vs. Other Cartographic Sources
Several analyses of DCW-generated 30" DEMs were conducted by USGS and UCL (see Muller and
others, 1998c), including comparisons with higher-resolution DEMs, and with other DEM candidates
for GLOBE. These analyses tended to show that DCW produced a less-than-ideal DEM. This was
largely due to the large contour interval in the source Operational Navigational Charts (ONC). The
stylization of ONC contours also contributed to artifacts in derived DEMs. Nevertheless, DCW-
based DEMs were determined to be generally much more useful at 30" than regridded ETOPO5 or
TerrainBase data (whose source data have grid spacings as coarse as 10').
DCW lacks contours for many parts of the world. In some cases other DEMs were contributed to
GLOBE or GTOPO30. In other areas, GSI and USGS located cartographic sources that could be
used to supplement DCW.
For parts of Indonesia, Brazil and neighboring South American countries, GSI and USGS located
maps for GSI adaption to digital contours, and subsequent USGS contour-to-grid conversion to 30"
DEMs.
This effort was only done when DCW contours were lacking or troublesome. Thus, for every area
where other cartographic sources were used, those other sources were automatically preferred. DCW-
based DEMs are unavailable for such areas.
5.B.ii. Global Data Set Assembly
GLOBE’s final assembly was created in GRASS’ r.patch module. This module combines data of
various grid spacings and coverage areas into a resultant data set of defined coverage area and grid
spacing. GRASS lets one work within a defined mask. It first inserts the highest-priority data set into
the output grid, then replaces all remaining areas with a “0” value with values from the next-highest
priority data set, ad infinitum. Working masks can be changed at any point in the sequence; this
requires restarting r.patch.
The first task was to determine the priority of patching. The second task was to determine the mask(s)
to be applied at each stage of patching. As GRASS version 4.1x uses zero as its “no-data” mask, and
cannot distinguish between numerical zeros and areas of “no data,” one must design masks to
compensate for this characteristic of the software. Subsequent versions of GRASS, currently under
development, are not subject to this characteristic. However, GLOBE Version 1.0 was managed
under GRASS 4.1.4, which does have this characteristic.
The following patching sequence was used:
a. Insert Japan-GSI. (No mask applied during the patch.)
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b. Insert Italy-SGN. (Japan-GSI coverage mask applied, but this is trivial.)
c. Insert Australia-AUSLIG/NGDC to B.A.D. GLOBE. Insert Australia-DCW/USGS/
GTOPO30 to G.O.O.D. GLOBE. (Mask accounting for previous steps applied, but this is
trivial.)
d. Insert Antarctica-SCAR/USGS/GTOPO30 as repaired by NGDC. (Mask accounting for
previous steps applied, but this is trivial.)
e. Insert for conterminous U.S. and vicinity:
i. NIMA spot data. (Mask accounting for previous steps applied, but this is trivial.)
ii. DMA/NGDC data.(Mask accounting for previous steps applied, now nontrivial.
This mask prevents overwriting of inland areas at sea level, but allows non sea-level
values in DMA/NGDC data to overwrite sea-level values in NIMA spot data in coastal
areas.)
iii. DMA/USGS/GTOPO30 data. (Mask accounting for previous steps applied. This
mask acts as the previous mask, allowing coastal zeros to be overwritten by coastal
non-zeros.)
f. Insert NIMA spot data within 50° of the Equator. (Mask accounting for previous steps
applied.)
g. Insert NIMA/GTOPO30 data poleward of 50° of the Equator. (Mask accounting for
previous steps applied.)
h. Insert DEM for Greenland, including Zwally (and others)/NSIDC/JPL-DCW blend. (Mask
accounting for previous steps applied.)
i. Insert DEMs from cartographic sources. (Mask accounting for previous steps applied.
This allows DEMs from cartographic sources to line some coastal areas, such as limited
areas in Greenland.)
Plate 1 (page 19) is a histogram of elevation distributions in GLOBE. Prominent features in this
histogram can be traced to features within individual sources of data. Histograms of these data are
plotted in Plates 2–30 and discussed in Section 5.A. For example:
n Spiking is more prominent at elevations of 4000m and below, as few data from cartographic
sources appear to cover areas with elevations higher than 4000m.
n The abrupt falloff in values above 4000m visible in the Antarctic Digital Database (Plate 30)
is prominent in Plate 1.
n The bulge in elevation values around 5000m visible in DTED discrete coverage of Asia
(Plate 3) is visible in Plate 1.
n The bulge in elevation values around 2500–3000m visible in ADD (Plate 30), and Greenland
(Plates 20 and 21) is visible in Plate 1.
Global Land One-kilometer Base Elevation
64
Inspection of the resultant DEM shows a relatively good fit between pieces, though there seems to be
a modest disagreement between DCW-derived grids and DTED over vertical datum. In addition, the
forcing of 0 elevations to 1 in categories used in GTOPO30 may cause difficulties for some users.
However, discrepancies appear to be in this order of subtlety.
5.B.iii. Georeferencing of GLOBE
Individual source materials used by GLOBE have a variety of internal georeferencing schemes. This
may raise questions of how to georeference the entire GLOBE DEM in one’s application.
Each GLOBE grid cell is bounded by integer increments of 30 arc-seconds of latitude and longitude.
Feed this information through your software’s georeferencing conventions. For example:
n If your software uses the center of grid cells for reference, you probably would use 179
o
59'45"
West longitude, 89
o
59'45" North latitude as the center of the first grid of Tile A.
n If your software uses the outside edges of extreme cells for your reference, you may use
something like 50
o
N–90
o
N and 180
o
W–90
o
W as the edges of tile A.
n For more information, contact the support personnel for your software.
Grid cell edges, lon1, lon2, lat1, and lat2 are integer increments of 30”.
Internal georeferencing varies by source. (See Sections 5.A.i through
5.A.xi.)
Graphic describing georeferencing for the entire GLOBE grid.
5.B.iv. Comparison of GLOBE with Other Available DEMs
GLOBE has considerably higher resolution than earlier predecessors ETOPO5 and TerrainBase.
Although TerrainBase was originally considered a candidate for filling GLOBE with areas lacking
higher-resolution data, GLOBE ultimately found 30" data from other sources for all areas but Antarctica
and Greenland. (The converted SCAR data base, and several other candidates for supplementing
GLOBE coverage of Antarctica, are considered better than ETOPO5/TerrainBase; the Greenland
GEOSAT-based DEM was converted to 30" by JPL.) GLOBE is a likely source for updating the next
version of TerrainBase, which will be regularly updated until user interest indicates that it should be
discontinued.
The TerrainBase management philosophy of soliciting contributions, and proactively offering to
participate in the design and development of unrestricted regional DEMs for the global compilation,
will be continued in the GLOBE project. TerrainBase and GLOBE served as prototypes for each
other during TerrainBase’s design and development. TerrainBase’s efforts at data compilation led to
lat1
lat2
lon2
lon1
V
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the SGN DEM for Italy which has since been adapted to GLOBE.
JPL’s DEM at 30" was developed for internal support of NASA’s Multiangle Imaging Spectro-
Radiometer (MISR) mission. The project had permission to reprocess DTED Level 1 data to 30"
gridding, but not to share those data with the general public. In addition, JPL used contour-to-grid
techniques to convert DCW to 30" DEMs in many areas; but not to the level of effort of USGS’s
effort with GTOPO30. JPL’s effort was largely crafted to meet its mission. Nevertheless, J.-P. Muller’s
comparison of GTOPO30 and the MISR DEM favored the MISR version for Greenland. As that data
set was largely unrestricted, the GLOBE project has incorporated unrestricted coverage for the
Greenland Ice Sheet into GLOBE.
The USGS/GTOPO30 effort was also developed partially for NASA, for more general support of
NASA’s Earth Observing System science community. It worked extensively to develop DCW contour-
to-grid procedures. It also acquired and processed several gridded DEMs, and worked cooperatively
with GSI to adapt several printed topographic maps to DEMs. Much of its data were incorporated
into GLOBE.
The GLOBE project added several data sets, including the first public release from DTED, the
AUSLIG/NGDC DEM, and DEMs from GSI and SGN. GLOBE uses the DTED Level 0 discrete
values where available between 50
o
North and South latitudes, where GTOPO30 uses several
inconsistent sampling methods for different areas. The GLOBE project also added the public peer
review site, enhanced documentation, and enhanced features on its Web site. Periodic enhancements
to data and documentation are anticipated.
5.B.v. GLOBE’s Development as Additional DEMs Are Created
GLOBE plans to continue seeking additional data, continue enhancing data quality and documentation,
and continue maintaining GLOBE products until the U.S. Department of Defense/NASA Shuttle
Radar Topography Mapper (SRTM) mission or other projects produce DEMs that exceed GLOBE’s
standards and capabilities.
It is hopeful that the SRTM mission, currently scheduled for launch in late 1999, will achieve its
objective of a publicly unrestricted 3" DEM for 60° North to South latitudes by 2001–2002, possibly
supplemented by similar data for higher latitudes. It is also hopeful that at least some areas of the
world will see 1"-gridded data released to the public from SRTM and from other high-resolution
imaging satellites being developed by several companies.
However, while SRTM is currently funded, there is no guarantee of its successful completion. Beyond
completion of its DEM mapping task, SRTM data must receive a thorough quality assessment which
could be a worthwhile contribution provided by an independent effort like GLOBE’s.
GLOBE may be put to rest after the full global SRTM (with enhancements) 3" DEM is complete.
However, it is possible that GLOBE coverage may remain the best widely-accessible data for parts
of the world well after completion of the SRTM mission.
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66
6. Imperfections in Digital Elevation Data
As with all digital geospatial data sets, users of GLOBE must be aware of certain characteristics of
the data set (resolution, accuracy, methods of production and any resulting artifacts, etc.) in order to
better judge its suitability for a specific application. A characteristic of GLOBE that renders it
unsuitable for one application may have no relevance as a limiting factor for its use in a different
application. Because only the end user can judge the applicability of the data set, it is the responsibility
of the data producer to describe the characteristics of the data as fully as possible, so that an informed
decision can be made by the user.
6.A. Grid Spacing and Resolution
For any application, the horizontal grid spacing (which limits the resolution) and the vertical accuracy
of GLOBE must be considered. The 30 arc-second grid spacing equates to about 1 kilometer, although
that number decreases in the East/West (longitudinal) direction as latitude increases. The table below
lists the approximate distance covered by 30 arc-seconds at different latitudes. Thus, at high latitudes
there is an unavoidable redundancy of data in order to keep the 30 arc-second spacing consistent for
the global data set. This is particularly true for the geographic version of Antarctica where the ground
distance for 30 arc-seconds of longitude converges to zero at the South Pole.
Latitude Ground distance (meters)
(degrees) E/W N/S
Equator 928 921
10 914 922
20 872 923
30 804 924
40 712 925
50 598 927
60 465 929
70 318 930
74 256 930
78 193 930
82 133 931
86 64 931
89 16 931
90 0 931
Resolution is defined as the minimum distance between two objects that can be separated in the
image. Many people mistakenly equate “resolution” to “pixel” or grid cell size, when resolution is
actually approximately 2.83 times grid cell size. Thus, the numbers above should be multiplied by
2.83 to get an estimate of horizontal resolution.
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Users should maintain this distinction between grid spacing and resolution. Even though the global
data set has a consistent 30 arc-second grid spacing, not all topographic features will be resolved at
that spacing. The level of detail of the source data determines whether the 30 arc-second sampling
interval is truly appropriate for resolving the important topographic features represented in the source.
The variation in ground dimensions for one 30 arc-second cell should be especially considered for
any application that measures area of, or distance across, a group of cells. Derivative products, such
as slope maps, drainage basin areas, and stream channel length, will be more reliable if they are
calculated from a DEM that has been first projected from geographic coordinates to an equal area
projection, so that each cell, regardless of latitude, represents the same ground dimensions and area
as every other cell.
Certainly, a 30 arc-second grid spacing is appropriate for the areas derived from higher resolution
DEMs (DTED, Japan-GSI, Italy-SGN, and the New Zealand DEM), and 30 arc-seconds has been
shown to be suitable as the cell spacing for grids derived from DCW hypsography (Hutchinson,
1996; Shih and Chiu, 1996). However, coverage of DCW contours is not complete, and there are
areas for which elevations were interpolated based only on very sparse DCW point data and/or distant
contours.
Small areas of this nature are located in Africa, South America, and islands of southeast Asia, while
Australia (the G.O.O.D. version from DCW) contains larger such areas. Australia (the B.A.D. version
from AUSLIG sources) also has variable source point distribution, though distribution tends to be
higher in areas of higher relief, tending to lead to higher horizontal resolution where needed. The
quality of the contours from the Antarctic Digital Database for the interior of Antarctica does not
realistically support a 30 arc-second (or even 1-kilometer) grid spacing, although such data are provided
for completeness and consistency of the global product.
6.B. Topographic Detail and Accuracy
Differences in topographic detail among the sources are evident in GLOBE. This change in level of
topographic information is especially evident at the boundary between areas derived from DTED
and DCW in regions of higher relief. The mosaicking techniques that were used resulted in a smoothing
of the transition areas, but the change in detail between the two sources remains noticeable. Seams
within data from “a single source” are sometimes apparent. Examples include DMA/USGS data in
the Seward Peninsula of Alaska and DTED coverage near Cordoba and Mendoza, Argentina.
Even if the same topographic feature (ridge, stream valley, lake, etc.) is represented in the data
derived from the two sources, the elevations across the feature may change somewhat abruptly due to
the varying accuracy of the sources. Derived products (such as slope maps) for the source transition
areas also emphasize the differences in topographic information derived from the varying sources.
Users are reminded that the accuracy levels described above are estimates, and that the accuracy for
specific locations within the overall area derived from any one source can vary from the estimate. For
Global Land One-kilometer Base Elevation
68
instance, approximately half of the 1°x1° DTED cells (the production and distribution unit for full
resolution DTED) have an absolute vertical accuracy worse than the product specification of ± 30
meters at 90% confidence. Also, the actual accuracy for some areas derived from the vector contour
sources may be better or worse than the estimate. When the map source had multiple contour intervals,
the largest interval was used for a conservative estimate. In contrast, some areas may be worse than
the estimate because no contour coverage was available for those specific locations.
6.C. Production Artifacts
Artifacts due to the production method are apparent in some areas of GLOBE. While the magnitude
of the artifacts in a local area are usually well within the estimated accuracy for the source, they may
affect some applications of the DEM.
Some areas derived from DTED exhibit a striping artifact, most likely due to the production method
of the DTED (see Section 5.A.i.a for more information). The artifact is very evident in the full
resolution data, but remains noticeable even in the generalized 30 arc-second version. Generally, the
pattern is more noticeable in low relief areas, while in higher relief areas it is masked by the actual
terrain variation.
Another pattern seen in some areas derived from DTED is a blocky appearance, which is a reflection
of the 1° tiling structure of the full resolution DTED from source data with certain characteristics
(Section 5.A.i.a). These areas derived from contiguous DTED 1°x1° cells appear blocky because of
vertical offsets among the tiles in the original full resolution DTED.
The artifacts in the DTED areas may be visible or obscured, depending on the method used to display
the data. For instance, when viewing the DEMs as an image either in shades of gray or color, the
artifacts may be subdued or hidden, depending on the number of shades or colors used. If the data are
displayed as a shaded relief image, the appearance of the artifacts will vary depending on the direction
of illumination, vertical exaggeration applied, and the scale of the display. Generally, none of the
artifacts will be visible on a course-scale portrayal of the global data set.
Some production artifacts are also present in the areas derived from the vector sources. Small artificial
mounds and depressions may be present in localized areas, particularly where steep topography is
adjacent to relatively level areas, and the hypsography data are sparse. Additionally, a “stair step” (or
terracing) effect may be seen in profiles of some areas. Here the transition between contour line
elevations does not slope constantly across the area but instead is covered by a flat area with sharper
changes in slope at the locations of the contour lines. Histograms of elevations show sharp peaks at
elevations that are multiples of the source’s contour interval. This effect is common in DEMs produced
by gridding of contour data, in which the interpolation process favors elevations at or near the contour
values, thus leading to a greater frequency of those elevations. Every effort to reduce these effects has
been made by careful selection of parameters for the interpolation process. However, some level of
these conditions inevitably remain due to the nature of vector-to-raster surface generation.
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7. Accuracy
GLOBE’s accuracy can be subdivided into horizontal and vertical accuracy, and again into absolute
and relative accuracy.
7.A. Horizontal Accuracy
Horizontal accuracy can be affected by errors in horizontal positioning of features, or errors in recording
horizontal datum. Horizontal accuracy may differ between sources. In some cases, it may also differ
within sources, if multiple sources were used. For example, DTED Level 1 data contained data from
various cartographic sources, as well as from various types of imagery. If individual map sources had
errors in recorded horizontal datum, or had misplaced contour lines (as could happen during
compilation or in printing), the resultant DEM would be misplaced horizontally, in an undocumented
fashion. If individual sources of imagery had errors in image navigation, resultant DEMs could be
mislocated if these errors were not corrected during development of respective DEMs.
7.A.i. Data from Raster Data Sources
In most cases, data from DTED Level 1 3" source materials (source/lineage categories 2–7) can be
expected to have 15" or better horizontal accuracy. Thus, nearest-neighbor resamplings to 30" gridding
for the MISR DEM, GTOPO30, and GLOBE should remain within the appropriate 30" grid cell.
This would make no measurable horizontal error for such data.
In the case of DTED Level 0 discrete (spot) data (source/lineage category 1), the reference location
is at the southwestern corner of each 30" grid cell. Errors as small as 100m in horizontal datum might
misplace a DTED discrete value into an adjacent 30" grid cell, making for a maximum anticipated
absolute horizontal error of one 30" grid cell. Relative horizontal inaccuracy from such data could be
comparatively high—on the order of one grid cell relative error on (probably rare) occasions.
Source/lineage categories 9–11 probably have horizontal errors of less than 30" for almost all parts of
the world.
Data from satellite altimetry, such as were used for part of Greenland (source/lineage categories 12
and 13) may be mislocated due to inaccurate determination of the satellite’s location in space. As
these data were originally gridded at larger than 30" intervals, oversampling to 30" for the MISR
DEM might have permitted horizontal errors of more than 30" in source/lineage categories 12 and 13
in GLOBE. We currently have no formal estimate of the horizontal accuracy of such data, other than
to assign the GEOSAT gridded DEM grid cell size of 10km to the likely horizontal locational accuracy.
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70
7.A.ii. Data from Cartographic Sources
Topographic contour lines in maps at 1:1,000,000 scale used for DCW and source/lineage categories
15–17) can be stylized so as to be 30" (one GLOBE grid cell) off. The SCAR data base (source/
lineage category 18) could be mislocated by a greater amount, owing to the relatively pioneering
status of current mapping of Antarctica. However, errors can exceed such figures locally. For example,
the ONC for northern Greenland contains notices such as: “CAUTION: Arctic Institute of North
America Project Nord (Control Data Corp.) indicates position discrepancies in excess of 11 nautical
miles (Nov. 68).”
In addition, surface generation algorithms might impose horizontal errors at least 30" off in areas
without much control by contour lines. This is because interpolated surfaces may be misguided by
patterns in point or contour data sources, especially where such data are stylized or scarce.
Similarly, the AUSLIG/NGDC data (source/lineage category 8) may be shifted horizontally by the
interpolation process, in areas with relatively low density of source data. Due to the high density of
source data points, this problem should be unusual. Stylization of source maps should have little
effect on horizontal accuracy in GLOBE, as these have relatively high resolution.
7.B. Vertical Accuracy
The absolute vertical accuracy of GLOBE varies by location according to the source data. Generally,
areas derived from raster source data have higher accuracy than those derived from vector source
data. However, some data that were delivered to GLOBE (or to the MISR or GTOPO30 DEMs) as
rasters came from cartographic sources, thus complicating assessment of their accuracy.
7.B.i. Absolute Accuracy: Data from Raster Sources
Digital Terrain Elevation Data (DTED): The full resolution 3" DTED have a vertical accuracy of
± 30 meters (two-sigma) linear error at the 90 percent confidence level (Defense Mapping Agency,
1986), where they meet specifications. If the error distribution is assumed to be Gaussian with a
mean of zero, the statistical standard deviation of the errors is equivalent to the root mean square
error (RMSE). Under these assumptions, vertical accuracy expressed as ± 30 meters linear error at 90
percent can also be described as a RMSE of 18 meters.
The areas of GLOBE derived from DTED might be interpreted to retain (or slightly improve upon)
the level of vertical accuracy found in the source 3" data. This is because the representative value
computed during compositing to 30" is either a simple value (as in nearest-neighbor or spot sampling)
at the same vertical accuracy as the source data, or is a computation (as a mean or median) that
should reduce some of the random error in a sample of source 3" values.
A visual inspection of DMA’s (1995) map, Available DTED1 Cells by Accuracy Range, suggests that
about half of DTED coverage meets specifications, while the other half fails to meet horizontal,
vertical, or both horizontal and vertical specifications. About 25% of DTED has 30–50 meter vertical
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accuracy and 0–50 meter horizontal accuracy; about 15% has 0–50 meter vertical and 50–131 meter
horizontal accuracy. Ten percent has either (1) 50–9999 meter vertical and 0–131 meter horizontal
accuracy, or (2) 0–9999 meter vertical and 131–9999 meter horizontal accuracy. Specific accuracy
information for each 1°x1° DTED cell is contained in DTED Level 0 header information on NIMA’s
Web site.
Shaded-relief images produced from DTED sources show two fairly common shading patterns
suggestive of vertical errors:
1. Striping apparently caused by stereoprofiling techniques or use of satellite scanner imagery.
The amplitude of these errors is usually small, in the 0–20 meter range. These appear to be
within NIMA’s tolerances for DTED.
2. Blocking around the edges of individual 1
o
x1
o
DTED Level 1 tiles (DTED cells). These
appear to be edge effects due to subtle de-facto disagreements about (most likely) vertical or
(possibly) horizontal datum between DTED tiles. These also appear to be well within vertical
accuracy specifications set by NIMA for DTED for their respective DTED tiles.
Note that NIMA allows for vertical errors as great as 9999 meters, for some areas. This appears to be
an extremely conservative figure.
Other Raster Data Sources: Data for Italy, Japan, and New Zealand were supplied as raster data.
However, their documentation notes that they were derived from cartographic sources. These are
discussed below. Zwally (and others)/NSIDC/JPL data for Greenland were derived from satellite
altimetry. Assessment of vertical accuracy of this data set is not yet complete.
7.B.ii. Absolute Accuracy: Data from Cartographic Sources
Digital Chart of the World (DCW): The absolute vertical accuracy of the DCW, the vector source
with the largest area of coverage, is stated in its product specification as ± 650 meters linear error at
the 90% confidence level (Defense Mapping Agency, 1990). USGS’s (1997b) experience while
converting DCW to grids has shown that the grids derived from DCW data should (in many areas) be
much more accurate than the 650-meter specification.
To better characterize the accuracy of areas derived from DCW vector hypsography, USGS compared
its DCW grid to 30 arc-second DTED, which had been aggregated by averaging in selected areas of
overlap with DCW coverage. By aggregating, the comparison could be done at the 30 arc-second cell
size of the DCW grid. The comparison was done for portions of southern Europe and the Mideast,
and all of Africa. Those areas of the DCW grid for which supplemental DTED point control had been
included in the gridding process were eliminated from the comparison.
If the averaged DTED are thought of as the reference data set, the RMSE of the DCW grid is 95
meters. To get an idea of the overall absolute accuracy of the DCW grid, the relative error between
the DCW and DTED can be combined with the known error of the DTED itself in a sum of squares.
The root of that sum of squares is 97 meters. Using the assumptions about the error distribution cited
Global Land One-kilometer Base Elevation
72
above, a RMSE of 97 meters can be expressed as ± 160 meters linear error at 90 percent confidence.
This number compares favorably with an expected vertical accuracy (linear error at 90 percent) of
one-half of the primary contour interval of 1,000 feet (305 meters) for the topographic maps on
which the DCW is based (USGS, 1997b).
AUSLIG Source Data: The accuracy of AUSLIG spot elevations in its source relief layer varies
with the type of source material from which they were captured. AUSLIG provided the following
table, giving estimates of vertical accuracy applicable to each source of point determination in terms
of its standard deviation in meters:
Spot height 5
Spot height inside depression contour 5
Spot height on sand ridge 5
Point captured from 20m contour 10
Point captured from 40m contour 20
Waterline (edge of sea) 25
NGDC’s estimate of 10m linear error at the 90% confidence level from histogram analysis can be
considered as an overall empirical estimate for the DEM derived from these sources, weighted by the
volume of data from the various sources. The estimate was derived from the dominant implied contour
interval in the grid of 20m, plus the dense coverage of source data compared to the 30” output grid.
Other Sources: The accuracy of the areas of GLOBE based on the other sources can only be estimated
based on that which is known about each source. Using certain assumptions, the vertical accuracy of
each source (and the derived 30 arc-second grid) can be estimated from the contour interval. One
assumption is that the original map sources meet the commonly used accuracy standard which states
that 90% of the map elevations are within ± 1/2 of the contour interval. It is unknown if any of these
maps actually meet this standard. Also, map digitizing and elevation surface interpolation errors are
unknown and therefore not included. However, histogram analysis of DEMs derived from cartographic
sources of undocumented contour interval can often be used to estimate contour intervals from those
original cartographic sources.
Table 2 (next page) lists the estimated absolute vertical accuracy for the areas of GLOBE derived
from each source, with the method of estimating the accuracy also identified. The RMSE numbers
were calculated using the assumptions about the error distribution cited above (a Gaussian distribution
with a mean of zero).
7.B.iii. Relative Accuracy
Local differences among DEM grid cells are often analyzed to calculate slope and other land surface
parameters. The relative vertical accuracy (or point-to-point accuracy on the surface of the elevation
model), rather than the absolute accuracy, determines the quality of such parameters derived from
local differencing operations. Although not specified for this data set, for many areas the relative
accuracy is probably better than the estimated absolute accuracy.
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Table 2. Estimated Absolute Vertical Accuracy for Areas of GLOBE
Vertical accuracy (meters)
Source L.E. at 90% RMSE Estimation method
DEM for Japan 10 6 estimated from histogram analysis of DEM*
DEM for Australia 10 6 estimated from histogram analysis of DEM
DEM for Italy 13 8 estimated from 25-meter contour interval**
DEM for
New Zealand 15 9 estimated from 100-foot contour interval
DTED 30–200 18–120 product specification for lower figure; higher figure
estimated from DMA DTED coverage map
categorizing horizontal and vertical accuracy by
location
Maps for Brazil 50 30 estimated from 100-meter contour interval
DEM for Greenland 150 91 estimated from histogram analysis of DEM
DCW 160 97 calculated vs. DTED
Maps for Asia
and S. America 250 152 estimated from 500-meter contour interval
Map for Peru 500 304 estimated from 1000-meter contour interval
SCAR/USGS 500 304 estimated from histogram analysis of DEM
* Here is a description of our method of estimating vertical accuracy from histogram analysis of the
DEM. Since traditional contour map production goals include vertical accuracy of 1/2 of the contour
interval, the estimates above by USGS for contour maps equate 1/2 of the source map’s contour interval
to vertical accuracy. Histogram analyses of DEMs can often determine the likely contour values of
source maps. These interpreted contour intervals were halved to estimate vertical accuracy of DEMs.
In many cases, more than one contour interval appears to exist in DEMs, perhaps because the DEMs
were produced from various types of maps, or perhaps because of supplemental contour intervals. In
such cases, vertical accuracy was estimated conservatively.
** Just outside of Italy, but included in the Italian DEM, some sources had somewhat coarser contour
intervals. In addition, histogram analyses within Italy suggests that different supplemental contour intervals
were used (to 5 meters in low-gradient areas (Salvi, 1995)), and that some contour lines were decimated
in mountainous terrain, especially in northern Italy. Nevertheless, the estimates noted above are probably
reasonably accurate.
7.B.iv. Summary: How to Use These Assessments
If you are developing critical applications, the accuracy figures estimated here should only be a
starting point for your own assessments. For example, areas of rugged topography can be expected to
have different (probably coarser) absolute and relative accuracies than areas of subdued topography.
Also, mixtures of map and imagery scales (and types) may have been used in developing some
DEMs. In the United States, for example, areas in the mountainous West may have contour intervals
of about 60m (200ft), whereas in parts of North Dakota, 2m (5ft) supplemental contours exist in
places. The figures in Table 2 are an attempt to provide information, and are certainly not a commitment
to such levels of accuracy anywhere in the data base.
Global Land One-kilometer Base Elevation
74
7.C. Additional Accuracy Assessments by Peer Reviewers
University College London: J.-P. Muller of UCL performed accuracy assessments of GTOPO30
and the JPL/MISR DEMs, as well as the AUSLIG/NGDC DEM (Muller and others, 1998a, 1998b,
1998c). This was done by compiling a large number of point elevation values, such as from the
commercial Jeppesen airport data base, and various geophysical data bases from NGDC, such as the
elevations of gravity observation stations. He found that the JPL/MISR DEM was slightly more
accurate than GTOPO30, with Australia and Greenland particularly better. However, the AUSLIG/
NGDC DEM was preferred over the other two available compilations in Australia.
One outcome of this study was the concern over the general quality control of the point elevation data
used in the comparisons. One airport elevation appeared to be several thousand meters off and other
values seemed unreasonable. Muller noted that “what constitutes the control” and “what constitutes
the data set being tested against the control” was unclear. Muller used statistical techniques to reject
point data that disagreed with the DEMs by more than 300m, based on the estimated “worst case”
RMSE shown in Table 2 (previous page). This served as an attempt to remove point elevation values
with significant unknown errors that might have crept into point data bases without quality control.
J.-P. Muller (1997; Muller and others, 1998b) used a global compilation of ERS-1 (Earth Resources
Satellite) radar altimetry data at 5’ (Bamber and others, 1997; Bamber and Muller, 1999) to compare
with other DEMs. The MISR DEM was slightly higher quality than GTOPO30, and the AUSLIG/
NGDC DEM was best for Australia by a factor of 2 compared to the other options.
National Oceanic and Atmospheric Administration: Dru Smith of NOAA’s National Ocean Service
performed comparisons between full-resolution DTED Level 1 data, other DEMs and geodetic models,
and DTED Level 0 means, maxima, minima, and discrete (spot) values. He found that the DTED
Level 0 mean values tended to be considerably lower than corresponding derivations made directly
from DTED Level 1 data. They also were lower than other DEMs and geodetic models available to
him. He was concerned that DTED Level 0 might have had a production bug. However, he found the
DTED Level 0 discrete values to be reasonable.
De Montfort University: P.A.M. Berry of De Montfort University (United Kingdom) compared
ERS-1 and ERS-2 altimetry with DTED Level 0 means and discrete values. The satellite altimetry
should have a longer spatial wavelength view of topography than DTED Level 1, though perhaps
shorter wavelength than DTED Level 0. Initial comparisons with DTED Level 0 means also noted a
significant discrepancy with ERS-1 and ERS-2 altimetry-derived elevations. DTED Level 0 means
seemed significantly lower than ERS-derived elevations produced by Berry. Later comparisons
between ERS-derived elevations and DTED Level 0 discrete values in the central United States
suggested much better overall agreement. Berry plans further assessments, including the development
of a map showing differences in the geographic distribution of GLOBE and her ERS-derived elevations.
Geographical Survey Institute: Hiroshi Murakami of the Geographical Survey Institute of Japan
compared DEMs of Japan produced by GSI with others produced by USGS from DCW. This study
suggested that DCW for Japan did not use Mean Sea Level as vertical datum, but rather had used the
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Japanese national datum. In short, it appeared that DCW had been mislabeled as to vertical datum for
Japan. This mislabeling could have been caused by inaccurate or inaccurately interpreted source
material documentation for the Operational Navigation Charts upon which DCW was based.
Use of These Studies in GLOBE: The studies by Muller helped in the selection of candidates for
GLOBE. The independent studies by Smith and by Berry helped NGDC select the DTED Level 0
discrete values as preferable for GLOBE, where available between 50
o
North and South latitude.
These values might also have been selected where available poleward of 50
o
latitude. However, their
lower horizontal resolution made the GTOPO30 versions preferable at such higher latitudes, as noted
in Section 5.B.i.h. The study by Murakami suggests modest caution when using elevations derived
from DCW.
7.D. Additional Comments on Accuracy
Note that various methods for measuring the terrain surface do not necessarily measure the
same objective. In-situ surveys (such as Global Positioning System or cadastral surveys) tend to
measure at a location above the ground surface, then compute the ground elevation below the “known”
ground clearance of the measurement. Stereo-optical imagery may measure the top of tree canopy—
which may or may not be converted to the elevation of the ground surface when the DEM is made.
This could be considered an issue of “attribute accuracy.” That is, are DEMs measuring what they
purport to measure? In most cases, the source data sets for GLOBE have not been able to address this
issue.
In addition, misrepresentations or errors in vertical datum could lead to 100+m errors in a DEM. This
may happen when information is missing from a map and an analyst makes an incorrect assumption
about the map. For example, the analyst may assume a particular ellipse in reprojecting data, when
another ellipse, or a sphere, had been used but not documented (or incorrectly documented).
Global Land One-kilometer Base Elevation
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8. Visualizations of GLOBE and Ancillary Data
8.A. Visualizations of GLOBE
The GLOBE Web site contains a Gallery of GLOBE Images at http://www.ngdc.noaa.gov/seg/topo/
globegal.shtml At the time of writing this document, the Gallery contains 5 arc-minute colored views
of the world and (separately) for each continent. It also includes shaded-relief images, and shaded-
relief images with earthquake hypocenters superimposed, for the same areas as the collection of
colored views. In addition, selected smaller areas are shown as full-resolution views, of similar type.
These images can be used to illustrate the character of GLOBE data (see also Hastings and Dunbar,
1998). They can also be used as base map illustrations, for anyone seeking digital images of any part
of the land surface.
8.B. Ancillary Data
The GLOBE Task Team originally expressed a desire to include “ancillary” data with the GLOBE
DEM. Original discussions centered around a registered, full-resolution source file, ocean mask,
slope, aspect, shaded relief, bathymetry, and possibly other data.
ETOPO5 included bathymetry, to make the first integrated global surface relief model. TerrainBase
used the bathymetric data from ETOPO5 to do the same. The GLOBE Task Team decided to forego
resampling these data and to exclude bathymetric data until better bathymetric data might appear.
8.B.i. Source/Lineage File (with Contained Ocean Mask)
A source/lineage file accompanies GLOBE Version 1.0. It is tiled in the same manner as the DEM.
Its file naming convention is “?10S”, where “?” is the tile letter ranging from A to P (see diagram in
Section 11.A).
The source/lineage file not only identifies the original source data set, but also certain important
details of processing used to make the 30" DEM. In some cases, it goes back earlier in the history of
a data set than source maps in other compilations (for example, noting that NIMA was the designer
of DCW, and that DMA originated certain DEMs distributed by NGDC and USGS). In other cases, it
notes subsequent processing that might be important, such as who might have adapted printed maps
to digital format, and who might have converted the digital vector lines to 30" raster grids.
The legend for the source/lineage map of GLOBE Version 1.0 is given in Section 11.E. Refer to the
back cover of this publication for a visual representation of the source/lineage map. For a higher
resolution image, go to the online GLOBE documentation at http://www.ngdc.noaa.gov/seg/topo/
report/.
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8.B.ii. Slope and Aspect Data (Why Aren’t They Provided?)
Although the GLOBE Task Team originally hoped to have slope and aspect data as ancillary data
sets, we currently consider the data at too early a stage of development to justify this. Users may
compute their own slope and aspect data, with the caveat that considerable care should go into the
derivation of such products. The DEMs still contain significant artifacts. Such artifacts are within
individual DEMs from individual sources/lineages. There are also discontinuities or steep gradients
at seams between data sources/lineages (caused by or incidental to the mosaicking process). Until
additional artifact removal is performed, the GLOBE Task Team believes that users be fully responsible
for the results of their own slope and aspect maps.
Global Land One-kilometer Base Elevation
78
9. Upcoming Improvements
We anticipate additional improvements for GLOBE. Here are some of the possibilities.
9.A. Integration with Other Data
NGDC has access to two new bathymetric models of higher resolution than the Digital Bathymetric
Data Base 5-minute (DBDB5) that was used in ETOPO5 and TerrainBase. Neither is quite ready for
release. When a digital bathymetric model has been released that is compatible with the GLOBE
DEM, we anticipate combining it with GLOBE.
There are two options for incorporating elevations and bathymetry:
1. Blend the two data sets together. In this option, all 16 GLOBE compressed tiles on the GLOBE
FTP and Web site will contain both elevations and bathymetry. Each tile will be much larger
than at present.
2. Have two versions of GLOBE: (1) a dry GLOBE having only land elevations, and (2) a wet/
dry GLOBE having both elevations and bathymetry.
Comments on these options would be appreciated. Our address and email contact information is
given in Section 1.
GLOBE Version 1.0 makes useful and fascinating reference data for analysis and presentation of
other data. For example, Stable Lights data sets from the Defense Meteorological Satellite Program’s
Operational Linescan System (OLS) (http://www.ngdc.noaa.gov/dmsp/dmsp.html) make dramatic
illustrations of human impact on the global environment, when plotted on base map color or shaded-
relief illustrations of GLOBE 1.0 data. The Gallery of GLOBE Images on the GLOBE Web site
contains examples of such data integration (http://www.ngdc.noaa.gov/seg/topo/globegal.shtml).
9.B. Additional Contributions of Land Elevation Data
Several elevation models have been made available to the GLOBE Task Team. Others are still being
discussed with their developers. We hope to add updates periodically. If you have DEMs that could
be adapted for GLOBE, we would appreciate your contributions. Contact information is given in
Section 1.
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10. Data Distribution
? GLOBE data are distributed at no cost from the GLOBE Web site (http://www.ngdc.noaa.gov/
mgg/topo/globe.html). Follow the link to “Get GLOBE Data.” You can get the individual
files, or select your own customized area for downloading.
? GLOBE data are also distributed no cost from NGDC’s anonymous FTP site:
FTP: ftp.ngdc.noaa.gov
USERID: anonymous
PASSWORD: [your email address]
: dir
: cd GLOBE_DEM/data/elev
: binary
: get [filename] or mget [filespecpattern]
: bye
The GLOBE source data are on the ftp site in the GLOBE_DEM/data/source directory.
These files are compressed with the GZIP utility. GZIP is widely used freeware, available for
most computer platforms. Go to http://www.gzip.org to download the version you need to
uncompress the data.
? The data are also available at modest cost-of-reproduction on CD-ROMs. If you are interested
in all GLOBE data, or don’t have fast Internet access, this may be the best source of the data.
Contact:
GLOBE DEM Project (E/GC3)
NOAA/National Geophysical Data Center
325 Broadway
Boulder CO 80305
Tel: 303-497-6277
Fax: 303-497-6513
Email: [email protected] (ordering information)
Possibly in the future, GLOBE data and documentation (including updates) may be distributed by
other organizations. Check the GLOBE DEM project’s Web site for possible developments of this
type.
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11. Data Format and Importing GLOBE Data
11.A. Data and Source File-Naming Convention
To facilitate handling, GLOBE has been divided into 16 smaller pieces, or tiles.
One option for file naming would have been to include latitudes and longitudes in each tile. However,
we wanted to include the version number of each data file. We also wanted to identify the G.O.O.D.
versions of GLOBE (unrestricted data) and B.A.D. versions (best available data, but with noted
restrictions). Both may exist for any given tile. In addition, we wanted to allow for the GZIP process
which takes two characters from DOS (traditional PC 8.3 character) file names.
Finally, we wanted to be prepared for the Spatial Data Transfer Standard (SDTS), a set of standards
designed for improved transfer of spatial data between computer systems. (Currently a developing
standard in the U.S., it is being considered by the International Standards Organization for worldwide
use.) SDTS only allows the data developer to use the first four characters of a file name. The other
characters are reserved for naming the SDTS “modules” (that is, the transfer files).
In order to be SDTS compliant, we restricted the tile name to four characters. The file naming
convention for the data and source files is as follows:
n First, a letter that fits the following tiling diagram:
180
o
W90
o
W0
o
90
o
E 180
o
E
North Pole 90
o
N
ABCD
50
o
N
EFGH
Equator 0
o
IJKL
50
o
S
MNOP
South Pole 90
o
S
n Second, the 2-digit version number. This refers to the version of the tile. For example, if Tile
A of GLOBE Version 1.0 is revised with new or corrected data, that first revision would
create Version 1.1 for that tile, which would then be named A11G. A major revision of
GLOBE (for example, the addition of bathymetric data to all tiles) might create GLOBE
Version 2.0 (and the A tile would have file name A20G until revised again).
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n Third, the data file naming convention (to the left of the dot in the file name):
G G.O.O.D. GLOBE data (unrestricted GLOBE data)
B B.A.D. GLOBE data (restricted GLOBE data)
S Source/lineage data (for G.O.O.D. GLOBE data)
T Source/lineage data (for B.A.D. GLOBE data)
n Fourth, the file extensions (to the right of the dot) identifying data format.
(no extension) uncompressed data or source/lineage file (from CD-ROMs containing
uncompressed data)
.gz gzip-compressed data or source/lineage file (from the Web site or source
file directory on the CD-ROM containing compressed data)
Note that all of the filenames on the CD-ROMs are stored in lowercase.
11.B. Metadata File-Naming Convention and Directory Structure
Metadata, including headers and associated files, are also found on GLOBE Volume 1 and on the
GLOBE Web site, according to the directory structure listed below. The prefixes of all the metadata
file names are the same as the associated data or source file. The file extensions, listed in parentheses
next to he directory name, vary according to the type of file. As an example, “a10g.clr” would be tile
A, version number 1.0, G.O.O.D. data, Arc/INFO (and ArcView) palette file. The file would be
found in directory /data/elevation/esri/clr. All of the filenames on the CD-ROM are stored in lowercase.
\data, raster data directory
n elevation, Global Land One-km Base Elevation Data
esri, ESRI support files
• clr, Palette files (.clr extension)
• hdr, Header files (.hdr extension)
geovu, GeoVu support files
• fmt, Format files (.fmt extension)
• hdr, Header files (.hdr extension)
• lst, Histogram files (.lst extension)
• pal, Palette files (.lst extension)
grass, GRASS support files
• cellhd, Header files (no extension)
• colr, Palette files (no extension)
• grasstar, UNIX tar file containing GRASS database (.tar extension)
idrisi, Idrisi support files
• doc, Header files (.doc extension)
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82
• pal, Palette files (.pal extension)
• smp, Palette files (.smp extension)
n source, Global Land One-km Base Source Data
esri, ESRI support files
• clr, Palette files (.clr extension)
• hdr, Header files (.hdr extension)
geovu, GeoVu support files
• fmt, Format files (.fmt extension)
• hdr, Header files (.hdr extension)
• lst, Histogram files (.lst extension)
• pal, Palette files (.lst extension)
grass, GRASS support files
• cellhd, Header files (no extension)
• colr, Palette files (no extension)
• grasstar, UNIX tar file containing GRASS database (.tar extension)
idrisi, Idrisi support files
• doc, Header files (.doc extension)
• pal, Palette files (.pal extension)
• smp, Palette files (.smp extension)
11.C. Elevation Data File Sizes, Regional Extent, and Statistics
Table 3 (next page) lists the name, latitude and longitude extent, elevation statistics, and file sizes for
each tile. There is no overlap among the tiles; the global data set may be assembled by abutting the
adjacent tiles.
11.D. Digital Elevation Data File Format
Files ?10G and ?10B (“?” is the wildcard notation for tile letters “A” through “P”) are provided as
16-bit signed integer data in a simple binary raster. There are no header or trailer bytes embedded in
the image. The data are stored in row major order (all the data for row 1, followed by all the data for
row 2, etc.). All files have 10800 columns, and either 4800 or 6000 rows (see Table 3, next page).
The following diagram depicts the organization of the files:
bytes1/2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . bytes21599/21600
bytes21601/21602 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . bytes43199/43200
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
etc.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .(last byte-1)/(last byte)
(text continues on page 84)
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Table 3. Tile Definitions
Latitude Longitude Elevation Data Grid
Tile Min. Max. Min. Max. Min.* Max. Columns Rows
A10G 50 90 -180 -90 1 6098 10800 4800
B10G 50 90 -90 0 1 3940 10800 4800
C10G 50 90 0 90 -30 4010 10800 4800
D10G 50 90 90 180 1 4588 10800 4800
E10G 0 50 -180 -90 -84 5443 10800 6000
F10G 0 50 -90 0 -40 6085 10800 6000
G10G 0 50 0 90 -407 8752 10800 6000
H10G 0 50 90 180 -63 7491 10800 6000
I10G -50 0 -180 -90 1 2732 10800 6000
J10G -50 0 -90 0 -127 6798 10800 6000
K10G -50 0 0 90 1 5825 10800 6000
L10G -50 0 90 180 1 5179 10800 6000
L10B** -50 0 90 180 -34 5179 10800 6000
M10G -90 -50 -180 -90 1 4009 10800 4800
N10G -90 -50 -90 0 1 4743 10800 4800
O10G -90 -50 0 90 1 4039 10800 4800
P10G -90 -50 90 180 1 4363 10800 4800
DEM Source/Lineage
Tile
Uncompressed GZIP-Compressed Uncompressed GZIP-Compressed
A10G 103,680,000 20,396,907 51,840,000 257,343
B10G “ 18,034,782 “ 340,035
C10G “ 24,837,828 “ 210,981
D10G “ 32,145,400 “ 127,663
E10G 129,600,000 17,229,934 64,800,000 142,904
F10G “ 19,044,848 “ 295,485
G10G “ 59,373,436 “ 379,860
H10G “ 27,920,006 “ 310,809
I10G “ 165,724 “ 71,873
J10G “ 21,275,017 “ 195,611
K10G “ 16,211,780 “ 159,950
L10G “ 11,642,180 “ 250,180
L10B* “ 14,374,075 “ 237,682
M10G 103,680,000 6,145,510 51,840,000 66,737
N10G “ 8,521,837 “ 109,433
O10G “ 9,071,480 “ 59,916
P10G “ 9,247,144 “ 67,790
* Note: This “minimum” shows the minimum elevation on land. Every tile contains values of -500 for
oceans, with no values between -500 and the minimum value for land noted here.
** Note: This tile contains the AUSLIG/NGDC DEM, and is the only GLOBE Version 1.0 tile containing
enhanced/restricted
B.A.D.
data.
Also NOTE: If using a UNIX workstation, Apple Macintosh or some other computer, your file names may
appear in lower case after reading files from the CD-ROMs or Web site.
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84
The data are in little-endian byte order (that is, for IBM-compatible PCs, Digital Equipment VAXes,
etc.). UNIX workstations using big-endian byte order can swap bytes using the command:
dd if=inputfilename of=outputfilename conv=swab
where “inputfilename” and “outputfilename” are replaced with the user’s selection of input and
output file names. Alternatively, NGDC’s public domain GeoVu software, which runs on IBM-
compatible PCs, Sun and Silicon Graphics UNIX workstations, and Apple Macintoshes, may be
used for this and other purposes.
11.E. Source/Lineage Map
The “?10S” files (and single “L10T” file) are a tiled source map; these files also contain lineage
information denoting post-source processing. Each file is a simple 8-bit (byte) binary image which
has values that indicate the source used to derive the elevation for every cell in the DEM, plus the
subsequent lineage of processing used to derive the DEM. The source/lineage map is the same
resolution and has the same dimensions and coordinate system as the DEM. Like the DEM, it has no
header or trailer bytes and is stored in row major order. These codes are used in the source map
image:
Code Source/Lineage (with section of this document that describes source/lineage)
0 Ocean.
1 DTED Level 0 discrete (spot) 30" DEM, sampled from the southwestern corner of the 30"
GLOBE grid cell. (More information in Section 5.A.i.)
2 DTED-based 30" median DEM from USGS/GTOPO30. (More information in Section 5.A.i.)
3 DTED-based nearest-neighbor (to center of 30" GLOBE grid cell) DEM from USGS/GTOPO30.
(More information in Section 5.A.i.)
4 DTED resampled to 30" by NIMA, provided to NGDC for public distribution in the 1980s. Spot
(nearest-neighbor) version used. (More information in Section 5.A.i.)
5 DTED provided to USGS for public distribution in the 1970s, regridded to 30" by nearest-
neighbor techniques by USGS. (More information in Section 5.A.i.)
6 DTED-based 30" “breakline” DEM from USGS/GTOPO30. (More information in Section 5.A.i.)
7 DTED-based DEM. Linear blending between classes 2 and 6 at their suture. (More information
in Section 5.A.i.)
8 DEM for Australia. AUSLIG point elevation data base for Australia, converted to 30" DEM by
NGDC (copyright 1998 by AUSLIG, licensed to NGDC for distribution with GLOBE). (More
information in Section 5.A.ii.)
9 DEM of Japan, from GSI. (More information in Section 5.A.iii.)
10 DEM for Italy at high resolution from SGN, converted to 30" gridding by NGDC (for SGN).
(More information in Section 5.A.iv.)
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11 DEM of New Zealand at 500m gridding by LCR, reprojected to 30" by USGS. (More information
in Section 5.A.v.)
12 DEM of Greenland at 90" by Zwally (and others)/NSIDC, converted to 30" by JPL. (More
information in Section 5.A.vi.)
13 Zwally (and others)/NSIDC/JPL and DCW blended DEM. Linear blending between classes 12
and 14 at their suture. (More information in Sections 5.A.vi. and 5.B.i.d.)
14 Digital Chart of the World. Developed by DMA from 1:1,000,000-scale maps, converted to 30"
grid by USGS. (More information in Section 5.A.vii.)
15 Maps for parts of southeast Asia and South America at 1:1,000,000 scale by AMS, digitized by
GSI, gridded at 30" by USGS. (More information in Section 5.A.viii.)
16 Maps for part of Brazil. Produced at 1:1,000,000 scale by the Fundacao Instituto Brasiliero de
Geografia e Estatistica of Brazil as part of the International Map of the World
series, adapted
to digital vectors by GSI, gridded at 30" by USGS. (More information in Section 5.A.ix.)
17 Map for part of Peru. Produced at 1:1,000,000 scale by the Ministerio de Guerra of Peru,
adapted to digital vectors by GSI, gridded at 30" by USGS. (More information in Section 5.A.x.)
18 SCAR Antarctic Digital Database, converted to 30" DEM by USGS, subsequently repaired by
NGDC. (More information in Section 5.A.xi.)
The cells with code 0 (ocean) in the source map can be used as an ocean mask. The ocean cells match
exactly all the cells masked as “no data” in the DEM with a value of -500. Likewise, the cells with
codes 1–18 together constitute a global land mask. Every cell in the DEM with an elevation has a
corresponding cell in the source map with a code in the range 1–18.
Refer to the back cover of this publication for a visual representation of the source/lineage map. For
a higher resolution image, go to the online GLOBE documentation at http://www.ngdc.noaa.gov/
seg/topo/report/.
11.F. Header Files and Associated Files
GLOBE’s Web site and CD-ROM version contain header files for NGDC’s GeoVu, GRASS, Idrisi,
Arc/INFO, and ArcView formats, plus metadata in the formats of the Global Change Master Directory
.dif, and Federal Geographic Data Committee (FGDC). Each header is a separate file. The GeoVu,
.dif, and FGDC files describe the entire data base, and have their own naming conventions. The other
headers are different for each tile, and have the same naming convention as described in Sections
11.A and B. The FGDC metadata information for GLOBE Version 1.0 is contained in Appendix C.
The Global Change Master Directory .dif file is also given in Appendix C.
11.F.i. Information about GeoVu Headers and Associated Files
Section 11.G.iv describes how to import GLOBE data into GeoVu. All GeoVu header files have a
.hdr extension. On the next page is the GeoVu header file a10g.hdr, as an example:
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file_tile = Tile A Elevation
number_of_display_colors = 256
palette = TOPO_LAND_256
data_type = image
data_byte_order = little_endian
upper_map_y = 90.0
lower_map_y = 50.0
left_map_x = -180.0
right_map_x = -90.0
number_of_rows = 4800
number_of_columns = 10800
grid_size(x) = 0.00833333
grid_size(y) = 0.00833333
grid_unit = degrees
grid_origin = upperleft_x
grid_cell_registration = upperleft
map_projection = lat/lon
elevation_unit = Meter
missing_flag = -500
elevation_max = 8752
elevation_min = -432
comment1 = actual elevation max = 6098
comment2 = actual elevation min = 1
Note that all of the GeoVu elevation header files have the same maximum elevation of 8752m and
minimum elevation of -432m. The actual maximum and minimum elevations for the file are also
listed as comments at the end of the header file. This was done to standardize the display colors for
all 16 elevation files.
The GeoVu header files are stored in the /data/elev/geovu/hdr and /data/source/geovu/hdr directories
of GLOBE Volume 1 and the GLOBE Web site.
Format files are also required for accessing the data with GeoVu. GeoVu format files have a .fmt
extension. These files are stored in the /data/elev/geovu/fmt and /data/source/geovu/fmt directories.
If you are accessing the data from the CD-ROMs, you will need the GeoVu menu files. They are
stored in the directory containing the GeoVu installation files for your particular platform. For example,
the menu files for the PC are found in the software/geovu/pc directory.
If you are accessing the data from the CD-ROMs using a GeoVu menu file, you do not need to copy
the header or format files onto your local machine. If you downloaded the data from the GLOBE Web
site, therefore are not using a GeoVu menu file, you must copy the header and format files to the
same directory as the data file.
Color palette files are provided for viewing the data in GeoVu. The files are stored in the /data/elev/
geovu/pal and /data/source/geovu/pal directories. If you are accessing the data from the CD-ROMs
using a GeoVu menu file, you need to copy the globe1.lst palette file from GLOBE Volume 1 to the
GeoVu directory on your local machine.
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If you downloaded the data from the GLOBE Web site, therefore are not using a GeoVu menu file,
you need to copy the geopal.lst to the GeoVu directory on your local machine. This file supersedes
the geopal.lst that is included with the GeoVu installation files.
11.F.ii. Information about Idrisi Headers and Associated Files
Section 11.G.v describes how to import the data into the Idrisi geographic information system.
Listed below is the Idrisi 4.x and Idrisi-for-Windows header file a10g.doc. Idrisi normally requires
its header files to have a .doc file extension, unless you have modified this information in your
Idrisi.env file.
file title : Tile A Elevation
data type : integer
file type : binary
columns : 10800
rows : 4800
ref. system : lat/long
ref. units : deg
unit dist. : 0.0083333
min. X : -180.0000000
max. X : -90.0000000
min. Y : 50.0000000
max. Y : 90.0000000
pos’n error : unknown
resolution : unknown
min. value : 1
max. value : 6098
value units : meters
value error : unknown
flag value : -500
flag def’n : none
legend cats : 0
The Idrisi header files are stored in the /data/elev/idrisi/doc and /data/source/idrisi/doc directories of
GLOBE Volume 1 and the GLOBE Web site.
Color palette files are provided for viewing the data in Idrisi. Palette files with .pal extensions are
ASCII files which may be used in Idrisi-for-DOS or Idrisi-for Windows. They are stored in the /data/
elev/idrisi/pal and /data/source/idrisi/pal directories.
Palette files with .smp extensions are binary files usable only in Idrisi-for-Windows. They are stored
in the /data/elev/idrisi/smp and /data/source/idrisi/smp directories.
Idrisi header and palette files should be placed in the same directory as the binary data.
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11.F.iii. Information about GRASS Headers and Associated Files
Section 11.G.vi describes how to import GLOBE data into GRASS.
Listed below is an example of a GRASS header file (a10g):
proj: 3
zone: 0
north: 90N
south: 50N
east: 90W
west: 180W
cols: 10800
rows: 4800
e-w resol: 0:00:30
n-s resol: 0:00:30
format: 1
compressed: 0
The GRASS header files are stored in the /data/elev/grass/cellhd and /data/source/grass/cellhd
directories of GLOBE Volume 1 and GLOBE Web site.
Color palette files are provided for viewing the data in GRASS. These files are stored in the /data/
elev/grass/colr and /data/source/grass/colr directories.
In GRASS, the header files should be placed in your “cellhd” directory (parallel to the “cell” directory
containing the data). The palette files should be placed in your “colr” directory (parallel to the “cell”
directory containing the data).
In addition, a fuller GRASS directory structure (containing cellhd, colr, and associated files) is available
to facilitate use of GLOBE data in GRASS (see Section 11.G.vi). That directory structure is stored in
the identical /data/elev/grass/grasstar/ and /data/source/grass/grasstar/ files on GLOBE Volume 1
and the GLOBE Web site.
The process for importing GLOBE data into GRASS, described in Section 11.G.vi, can be automated
by scripting the procedure. A sample script is provided in the /data/elev/grass/script directory.
11.F.iv. Information about Arc/INFO (and ArcView) Headers and Associated Files
Section 11.G.viii describes how to import GLOBE data into Arc/INFO. Section 11.G.ix describes
how to import GLOBE data into ArcView.
The Arc/INFO (and ArcView) header file a10g.hdr is shown on the next page. Note: Arc/INFO and
ArcView use the same header and palette files.
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BYTEORDER I
LAYOUT BIL
NROWS 4800
NCOLS 10800
NBANDS 1
NBITS 16
BANDROWBYTES 21600
TOTALROWBYTES 21600
BANDGAPBYTES 0
NODATA -500
ULXMAP -179.995833333
ULYMAP 89.995833333
XDIM 0.00833333
YDIM 0.0083333
The Arc/INFO (and ArcView) header files are stored in the /data/elev/esri/hdr and /data/source/esri/
hdr directories of GLOBE Volume 1 and GLOBE Web site.
Color palette files are provided for viewing the data in Arc/INFO and ArcView. ArcView palette files
have a .clr extension. In Arc/INFO one specifies the name of a palette file. The same palette files can
be used in both ESRI products. The color palette files are stored in the /data/elev/esri/clr and /data/
source/esri/clr directories.
The Arc/INFO (and ArcView) header and palette files should be placed in the same directory as the
binary data file.
11.G. Obtaining and Importing GLOBE Data
11.G.i. Obtaining the Data
See Section 10.
11.G.ii. GUNZIP the Compressed Data from the Web Site
Any data with a .gz extension must be uncompressed with GUNZIP. The command syntax may be
one of these:
gunzip inputfilename
gzip -d inputfilename
This will uncompress the data, remove the .gz file extension, and delete the compressed .gz file. Note
that you must have enough hard disk space to uncompress a file. Compressed and uncompressed file
sizes are given in Table 3 (page 83). If you are not familiar with GUNZIP, go to http://www.gzip.org.
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11.G.iii. Which Computer Are You Using?
Because the DEM data are stored in a 16-bit binary format, users must be aware of how the bytes are
addressed on their computers. The DEM data are provided in IBM PC-compatible byte order, which
stores the least significant byte first (“little endian”). Systems such as Digital Equipment VAXes and
Alpha workstations, as well as computers using most Intel-compatible central processing units (CPUs)
use this byte-ordering scheme.
For Apple Macintosh computers and most popular UNIX workstations, the typical byte order is most
significant byte first (“big endian”). Some UNIX GIS applications provide an option to swap the
bytes when importing the data (e.g. ERDAS/IMAGINE) or the information can be specified in header
files (e.g. Arc/INFO and ArcView). If the application does not provide this option (e.g. GRASS),
users with systems that use big-endian byte ordering have to “swap bytes” of the DEM data. This is
easily done on most UNIX workstations, using the
dd command. Check how this command works on
your UNIX workstation, probably by running the command man dd. Typically, the command is
executed as follows:
dd if=inputfilename of=outputfilename conv=swab
11.G.iv. Importing into NGDC’s GeoVu
The CD-ROM version of GLOBE data, as well as data obtained from the GLOBE Web site, are
accessible with NGDC’s GeoVu utility. This utility may be useful for browsing, viewing, subsetting,
and reformatting the data. Software and documentation are provided for Apple Macintosh, IBM-
compatible PCs, and Sun and Silicon Graphics UNIX workstations.
11.G.iv.a. Accessing GLOBE Data on the CD-ROM
GeoVu can be found in the /software/geovu directory of GLOBE Volume 1.
You may want to print documentation found in the software/geovu/documnt directory. Read the
readme.1st file in the directory for an overview of the documentation enclosed in that directory. Then
go to the directory designated for your computer system of choice (for example, PC). In that computer
system-related directory, read the readme.1st file, and follow its directions for installing and running
GeoVu. This information is also provided on NGDC’s GeoVu Web site at http://www.ngdc.noaa.gov/
seg/geovu/geovu.shtml.
Importing and displaying the northwestern tile (a10g) with GeoVu is presented as an example.
n First, install GeoVu. Next, copy the GLOBE GeoVu color palette file (globe1.lst) and GeoVu
menu files (globe1_1.men, globe1_2.men, globe1_3.men, and globe 1_4.men) to your GeoVu
directory. The color palette and menu files (described in Section 11.F.i) are found in the
directory containing the GeoVu installation files for your particular platform. For example,
the palette and menu files for the PC are found in the software/geovu/pc directory.
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n Insert GLOBE Volume 1 into the appropriate CD-ROM drive.
n Start GeoVu. From the GeoVu screen, select File/Set Data. In the Main List of Data Sources
screen that appears, highlight GLOBE 1.0 1999, Northern Hemisphere, 1 of 4 and enter
the CD-Drive letter and click >>Next.
n An introduction screen will then appear. After reading the information, click >>Next. In the
Main Menu that appears, highlight Data: Tile A(50-90N, 90-180W) and click OK to display
the file with the default options.
n In addition to displaying the file with the defaults, you can also specify a subset of the region
and/or select a different color palette. The option to write to disk is also provided. To specify
a subset of the region, select Search/Create. A Data Source Selections screen will appear.
Highlight Tile A Elevation and click OK. An Image Search Parameters screen will appear.
Click on Set Search Parameters Limits to change the region. Click OK to display the subset
of the tile.
11.G.iv.b. Accessing GLOBE Data Obtained from the GLOBE Web Site
The GLOBE Web site contains links to GeoVu support files for online GLOBE data, as well as to
GeoVu software. NGDC’s GeoVu Home Page is at http://www.ngdc.noaa.gov/seg/geovu/geovu.shtml.
To access a GLOBE data tile with GeoVu, you will need a header file, a format file, and a color
palette file (described in Section 11.F.i). All of these associated GeoVu files are available on the
GLOBE Web site.
Importing and displaying the northwestern tile (a10g) with GeoVu is presented as an example.
n First, install GeoVu. Next, copy the geopal.lst file from the GLOBE Web site to your GeoVu
directory. This file supersedes the geopal.last file included in the GeoVu installation files.
n Download the GLOBE data and the associated header and format files to the same directory
(a different directory from the GeoVu directory). For example, copy the a10g data tile,
a10g.fmt, and a10g.hdr to the same directory.
n Rename the data file, a10g, to a10g.bin.
n To display the file a10g.bin, start GeoVu. From the GeoVu screen, select File/Set Data/
Other Disk Files and then click OK. A dialog box will appear that allows you to navigate to
the a10g.bin file. After selecting the a10g.bin file, select Search/Create. An Image Search
Parameters screen will appear. Click OK to display the file with the default options. In addition
to displaying the file with the defaults, you can also specify a subset of the region and/or
select a different color palette. The option to write to disk is also provided.
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11.G.v. Importing into Clark University’s Idrisi
Users of Idrisi may import the DEM and source/lineage files (GUNZIP decompressed) using the
following procedure. Importing the northwestern tile of GLOBE (file a10g) into Idrisi is presented as
an example.
n Copy the a10g.doc (IDRISI DOC file described in Section 11.F.ii), globedat.smp (IDRISI
color palette file described in Section 11.F.ii), and a10g (elevation data) files into same disk
location. Rename the file a10g to a10g.img.
n Start Idrisi for Windows. Click on display and enter a10g. Under Palette Options click on
User Defined and enter globd256 (or double click and select this palette). Confirm that the
Autoscale image for display option has been activated (this should happen by default for
integer data). Click OK to get the display.
n To standardize the display colors, the number 8752 must be substituted for the actual maximum
elevation for a tile in its .doc file. This may be done by hand editing the a10g.doc file, or by
running Document. On the top line of Idrisi for Windows, click on File, then on Document.
Enter a10g and click OK. Replace the actual maximum value for the file with 8752. Click
OK.
n Display the data as shown above. This will autoscale the display colors uniformly for all data
sets. The zero and negative values are all displayed as black, but if queried, the correct value
is displayed.
n To replace 8752 with the actual maximum value for the file, run Document on the a10g file.
Next to the window for maximum value click on the button to Calculate. This puts the actual
maximum and minimum back in their appropriate boxes.
The files can also be imported by running Document, specifying the data type (integer for DEMs,
byte for source/lineage files), grid cell size of 0.00833333, and coordinate range for the specific
GLOBE tile. You can have Idrisi automatically find the maximum and minimum values for the
DEMs, or you can enter the values from Table 3 (page 83) to avoid waiting for Idrisi to check each
large file for maximum and minimum value.
Idrisi for DOS color palette files are also available: globd16.pal is for the COLOR module; glob256.pal
is for the COLOR85 module. See documentation for Idrisi versions 3.x or 4.x regarding the use of
user-defined palettes in these modules.
11.G.vi. Importing into the U.S. Army Corps of Engineers’ GRASS
Two procedures are presented for importing the DEM and source/lineage files (GUNZIP
decompressed) into GRASS: (1) importing GLOBE data using a sample GRASS data base, and (2)
importing GLOBE data into your own GRASS data base.
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11.G.vi.a. Importing GLOBE Data Using a Sample GRASS Data Base
For convenience, a sample GRASS data base for GLOBE is provided. This data base is in a global
30" latitude-longitude “projection.” It contains GRASS cell header (cellhd), cell miscellaneous
(cell_misc), and color (colr) directories and files for GLOBE data and source tiles. It also contains an
empty cell directory, into which GLOBE tiles may be placed.
n Copy the grasglob.tar file from /data/elev/grass/grasstar/ or data/elev/grass/grasstar/ (the files
are identical) to a directory on your Unix workstation. To “un-tar” the file, run the following
command (or similar for your environment):
tar -xvf grass.tar
n Copy data from the GLOBE Web site or CD-ROMs into the grass/user/cell directory. You
may wish to “mv” the directory structure so that the “user” becomes your login name, thus
making a grass/yourlogin/cell directory. Go to that directory.
n GUNZIP any data files containing a .gz extension (see Section 11.G.ii).
n To keep track of your files, rename all data tiles with a .pc extension. For example, “mv a10g
a10g.pc”.
n Byte-swap the data for most Unix workstations.
dd if=a10g.pc of=a10g.ux conv=swab
n Delete the a10g.pc file. For example, “rm a10g.pc”.
n Start GRASS. Make sure that there is no mask, by interactively executing the r.mask command
and removing the current mask (if any).
n Set the GRASS region to the region of the data file by executing the following GRASS
command:
g.region rast=a10g.ux
n GRASS’ multibyte format handles signed integers differently from traditional 16-bit integers
used in GLOBE. Therefore, if you are importing a DEM file such as the a10g.file, the following
command must be executed:
r.mapcalc ‘a10g=if(a10g.ux-32768,a10g.ux-65536,a10g.ux,a10g.ux)’
where a10g is the final name for this GLOBE DEM file. This step is not necessary when
importing source/lineage files.
n If you are importing a DEM file such as the a10g file, remove the temporary file by executing
the following GRASS command:
g.remove a10g.ux
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n If you are importing a source/lineage file such as the a10s file, uncompress the files (which
are compressed on the CDs and the Web site) in your grass/yourlogin/cell directory using one
of the following:
unzip a10s.gz
gzip -d a10s.gz
where a10s is the final name for this GLOBE source/lineage file.
n You may want to GRASS-compress the DEM and source/lineage files to reduce the sizes of
the files. To shrink the file without changing its name, execute the following GRASS command:
r.compress a10g
r.compress a10s
n You can now display the a10g and a10s files using the GRASS color palette files provided.
n NOTE: You can automate the ingest of many GLOBE DEM files by scripting this procedure.
Sample scripts are provided in the /data/elev/grass/script/ and /data/source/grass/script/
directories.
11.G.vi.b. Importing GLOBE Data Into Your Own GRASS Data Base
n Copy the a10g.ux and a10s GRASS cell header files (described in Section 11.F.iii) into your
GRASS cellhd directory. Also copy the a10g and a10s color palette files (described in Section
11.F.iii) into your GRASS colr directory.
n Follow the same procedures described in the previous section except omit the first step (un-
tarring the grasglob.tar file).
11.G.vii. Importing into ERDAS
Users of ERDAS may import the DEM files (GUNZIP decompressed) using the following procedure.
Importing the northwestern (file a10g) tile of GLOBE into ERDAS is presented as an example.
n Start ERDAS. Click on the Import button. In the Import/Export template that appears, select
Generic Binary for Type and the appropriate response for Media. Enter a10g as the input
filename. The default output filename is a10g.img. Click OK and Close.
n The Import Generic Binary Data template is displayed next. Enter 10800 for the number of
columns and 4800 for the number of rows. (The number of columns is always 10800. The
number of rows is 4800 for tiles that cover 50
o
to 90
o
N or 50
o
to 90
o
S latitude and 6000 for
tiles that cover 0
o
to 50
o
N or 0
o
to 50
o
S latitude.) For Data Type use Unsigned 8 bit (the
default) if importing a source/lineage file, and Signed 16 bit if importing a GLOBE DEM
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file. The data format type is BIL. If you are running UNIX ERDAS, click on Swap Bytes and
click OK to begin the import. When the import is complete, click OK again. Close the Import/
Export template window.
n Select Image Information from the Tools pulldown menu. The ImageInfo template is then
displayed. Click Open from the File pulldown menu and select a10g.img and click OK.
Select Change Map Model from the Edit pulldown menu. Enter the appropriate x (longitude)
and y (latitude) coordinates for the imported data set; for tile a10g the x coordinate is -180
and the y coordinate is 90. This information is found in Table 3 (page 83). Next, enter
0.00833333 for x and y pixel sizes. Set the Projection to Geographic (lat/lon). The Units
should automatically change to Degrees. Click OK. When a confirmation window pops up,
click OK again. Leave the ImageInfo window open.
n In the ImageInfo template, select Compute Statistics from the Edit pulldown menu. The
Statistics Generation Option template is then displayed. Change the Skip Factor to 1 and the
Skip Factor Y to 1. Change the Bin Function to Linear. Then click OK. After the statistics
are computed, confirm that the information in the ImageInfo window is correct and close the
window.
Your data should now be in ERDAS, in latitude/longitude projection. The file can be displayed as a
raster layer. Some ERDAS processes (such as computing shaded relief images) may want you to
reproject the data, or at least signify to ERDAS that the data are in a projection other than Geographic.
ERDAS adds header and footer information to GLOBE’s binary raster grids as part of the procedure
described above for importing new files. Earlier versions of ERDAS performed this task with the
functions FIXHEAD and BSTATS. FIXHEAD details the numbers of columns and rows,
georeferencing, number of bytes, etc. This information is provided in Table 3 (page 83). BSTATS is
run after FIXHEAD, appending statistical information to the end of the file.
11.G.viii. Importing into ESRI’s Arc/INFO
Users of Arc/INFO can import GLOBE DEM and source/lineage files (GUNZIP decompressed) by
converting the DEM to an Arc/INFO grid with the command IMAGEGRID. Importing the
northwestern (file a10g) tile of GLOBE into Arc/INFO is presented as an example.
n Copy a10g.hdr (Arc/INFO header file described in Section 11.F.iv), a10g.clr (Arc/INFO
color palette file described in Section 11.F.iv), and a10g (elevation data) files into your Arc/
INFO workspace. Rename the file a10g to a10g.bil. You should now have the following files
in your ArcInfo working directory: a10g.bil, a10g.hdr, and a10g.clr.
n Next, from within Arc/INFO run IMAGEGRID:
IMAGEGRID a10g.bil a10gaig
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n To add projection information to a10gaig, at the Arc prompt type the following:
projectdefine grid a10gaig
This begins an interactive dialog for entering projection information for the data set. At the
Project prompt, enter the following information. The word “parameters” completes the
projection definition.
projection geographic
units dd
datum wgs84
zunits meters
parameters
n IMAGEGRID does not support conversion of signed image data, therefore the negative 16-
bit DEM values will not be interpreted correctly. After running IMAGEGRID and adding the
projection information, this can be fixed by using the following formula in GRID:
a10gconv = con(a10gaig >= 32768, a10gaig - 65536, a10gaig)
where a10gaig is the file created by IMAGEGRID, and a10gconv is the converted signed
integer grid. The converted grid will then have the negative values properly represented, and
the statistics of the grid should match those listed in Table 3 (page 83). This process creates
a georeferenced Arc/INFO GRID file called a10gconv. You can use the resultant GRID file
in Arc/INFO’s GRID module. This step is not necessary when importing source/lineage files.
n If desired, the -500 ocean mask values in the grid could then be set to NODATA with the
SETNULL function in GRID:
a10gnull = setnull(a10gconv == -500, a10gconv)
n To display the file with the color palette provided, copy the a10g.clr file (color palette file) to
your Arc/INFO workspace. Then use the following commands in ARCPLOT:
display 9999
mape a10gnull
gridpaint a10gnull # # # a10g.clr
The zero and negative values are all displayed as black.
11.G.ix. Importing into ESRI’s ArcView
An Arc/INFO coverage created using the procedure described in Section 11.G.viii can be displayed
in ArcView. In addition, the GLOBE data and source/lineage files (GUNZIP decompressed) can be
displayed after renaming the file by adding a .bil extension. Importing the northwestern tile of GLOBE
(file a10g) in ArcView is presented as an example.
n Copy the a10g.hdr (Arc/INFO header file described in Section 11.F.iv), a10g.clr (Arc/INFO
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palette file described in Section 11.F.iv), and a10g (elevation data) files into your ArcView
working directory. Rename the file a10g to a10g.bil. You should now have the following
files in your ArcView working directory: a10g.bil, a10g.hdr, and a10g.clr.
n Start ArcView. You should either open an existing project with a view in a geographic (latitude-
longitude) projection, which covers the area(s) you want to work with; or start a new view. If
you start a new view, choose Properties from the View pulldown menu. In the View Properties
window, click on the Projection button and select Projections of the World as the Category
and Geographic as the Type. Click OK in the View Projections window. In the View Properties
window select Kilometers or Miles as the Distance Units. Click OK.
n Add the a10g.bil file to the View as an Image Data Source theme. After you add the a10g.bil
image, your project should show the data file in your legend. To display the a10g.bil theme in
the View window, click on the raised box to the left of the theme name (a10g.bil) to make a
check mark. Un-“check” all other data that you may have in this project.
ArcView does not correctly interpret negative values. Therefore, the zero and negative values are all
displayed as black. The values in the image displayed cannot be queried with ArcView, unless you
have the ArcView extension Spatial Analyst.
11.G.x. Importing into Adobe Photoshop
Users of Photoshop can display GLOBE DEM and source/lineage files (GUNZIP decompressed)
after renaming the file by adding a .raw extension. Importing the northwestern tile of GLOBE (file
a10g) into Photoshop is presented as an example.
n Copy the a10g (elevation data) files onto your hard drive. Rename the file a10g to a10g.raw.
n Start Photoshop. Select Open from the File pulldown menu and select Raw for Files of Type.
Find the file on your disk and highlight it. Click OK. The Raw Options window is then
displayed. Enter 10800 for Width and 4800 for Height. Under Channels, make sure that the
Count is 1. For Depth select 16 bits. For Byte Order select IBM PC. For Header keep 0
bytes. Click OK to open and display the image (which will probably initially display in black
and white).
Note: The width is 10800 for all tiles, but the height is 4800 for tiles that cover 50
o
to 90
o
N or 50
o
to
90
o
S latitude and 6000 for tiles that cover 0
o
to 50
o
N or 0
o
to 50
o
S latitude. This information is also
found in Table 3 (page 83).
Photoshop Version 4 imports 16-bit data, but does not allow you to work with the data until saved to
an 8-bit version. Photoshop Version 5 handles 16-bit data directly, but in a limited way. You will
probably have to save the data to an 8-bit version before you can do much with the data in Photoshop
Versions 4 or 5.
Global Land One-kilometer Base Elevation
98
11.G.xi. Importing into Other Software Packages
Sections 11.G.iv through 11.G.x give specific examples for representative geographic information
systems, image processing systems, and a graphics program. If you are using a different application,
we hope that:
n The examples may still give you an idea of how to import GLOBE data into your particular
application.
n The header files for the given examples may be useful for importing into your application.
For example, some applications use GRASS, Idrisi, or other headers to help import GLOBE
data.
Although we cannot describe how to ingest GLOBE data into every available GIS, we are happy to
post methods for ingestion into other software packages if you submit them to us (with your name,
postal address, and email address and/or fax number). We regret that we will not be able to support
users of other systems which we may not have. However, the support personnel for your particular
software package should be able to help you, as the structure of GLOBE data is typical of many raster
gridded data.
11.H. Projection Information
Listed below is the projection information for each data file in GLOBE:
Projection Geographic (latitude/longitude)
Datum WGS84
Zunits Meters above mean sea level
Hunits 30 arc-seconds of latitude and longitude
Spheroid WGS84
Xshift 0.0000000000
Yshift 0.0000000000
Cell Referencing Each cell is nominally bound by 30" intervals of latitude
and longitude, beginning with any whole degree (e.g.
0.0000 degrees)
Parameters NONE other than those above
11.I. Georeferencing in GLOBE
See Section 5.B.iii. Georeferencing conventions of several software packages are shown in Sections
11.F.i through 11.F.iv, and 11.H.
Documentation Version 1.0
99
12. Disclaimers
Any use of trade, product, or firm names is for descriptive purposes only and does not imply
endorsement by the U.S. Government nor the GLOBE Task Team.
The user accepts full responsibility for use or misuse of these data. Please read the following
warnings, extracted from elsewhere in this document (Section 1):
Note that GLOBE Version 1.0, like other digital topographic data, are insufficiently
accurate over their full global extent to be taken too literally for mission-critical
applications. They must always be interpreted with extreme caution. They should not
be used exclusively in mission-critical or life-critical applications.
The following passage was provided by NIMA:
“The data contained in DTED Level 0 is a derivative set only, and does not represent
the entire Department of Defense archive of terrain data. In making these data available
to the general public, NIMA in no way alters the controlled status of the remaining
archives. Technical support or general assistance with respect to DTED Level 0 is
available only to U.S. Government users. NIMA requests that products developed
using DTED Level 0 credit the source with the following statement: “This product
was developed using DTED Level 0, a product of the National Imagery and Mapping
Agency.”
Warranty Disclaimers and Requirements:
a. Under 10 U.S.C. 456, no civil action may be brought against the United States on
the basis of the content of data prepared or disseminated by either the former Defense
Mapping Agency (DMA) or NIMA.
b. DTED Level 0 was developed to meet only the internal requirements of the DOD.
DTED Level 0 is provided “as is,” and no warranty, express or implied, including but
not limited to the implied warranties of merchantability and fitness for particular
purpose or arising by statute or otherwise in law or from a course of dealing or usage
in trade, is made by NIMA as to the accuracy and functioning of the product.
c. Neither NIMA nor its personnel will be liable for any claims, losses, or damages
arising from or connected with the use of DTED Level 0. The user agrees to hold
harmless the U.S. National Imagery and Mapping Agency. The user’s sole and
exclusive remedy is to stop using DTED Level 0.
d. For any products developed using DTED Level 0, NIMA requires a disclaimer
that use of DTED Level 0 does not indicate endorsement or approval of those products
by either the Secretary of Defense, the former Defense Mapping Agency, or the
National Imagery and Mapping Agency. Pursuant to the United States Code, 10 U.S.C.
Global Land One-kilometer Base Elevation
100
445, the name of the Defense Mapping Agency, the initials “DMA,” the seal of the
Defense Mapping Agency, the name of the National Imagery and Mapping Agency,
the initials “NIMA,” the seal of the National Imagery and Mapping Agency, or any
colorable imitation thereof shall not be used to imply approval, endorsement, or
authorization of a product without prior written permission from the U.S. Secretary
of Defense.”
The following passage was posted on USGS’s GTOPO30 Web site:
“Please note that some U.S. Geological Survey (USGS) information contained in
this data set and documentation may be preliminary in nature and presented prior to
final review and approval by the Director of the USGS. This information is provided
with the understanding that it is not guaranteed to be correct or complete and
conclusions drawn from such information are the sole responsibility of the user.”
The above-noted disclaimers are applicable, as adapted by including the appropriate data source(s)
and processor(s) to all portions of GLOBE, from all sources. In addition, they are applicable to the
entire GLOBE data set, associated data files (such as source/lineage data), and documentation.
The following passage applies to the AUSLIG/NGDC DEM for Australia:
“The AUSLIG/NGDC DEM for Australia [see Section 5.A.ii for extent of these data]
is Commonwealth Copyright, AUSLIG, Australia’s national mapping agency (1998).
All rights reserved. These data have been reproduced with the permission of the
General Manager, Australian Surveying and Land Information Group, Department
of Industry, Science and Tourism, Canberra, ACT.
The Commonwealth of Australia is the owner of the data.
The data are licensed to NOAA/NGDC for distribution with GLOBE.
AUSLIG is the custodian of the copyright of the maps and data products it produces
on behalf of the Australian Government, ie. the Commonwealth. This custodianship
has been devolved to AUSLIG by the Australian Government Publishing Service.
AUSLIG has a statutory responsibility to administer the Commonwealth Copyright
of all its products. AUSLIG does not give away copyright. Rather it grants a right to
use its products as specified in any application to use its products, ie., a license.
AUSLIG encourages the widest possible use of any material over which it administers
copyright within the provisions of the Copyright Act. We undertake to give prompt
consideration to all requests for use of AUSLIG copyright material.
No AUSLIG material may be copied, traced, digitized, stored on a computer system
or transmitted in any form, or by any means, whether electronic, mechanical,
photocopying, recording or otherwise, or translated into another language, until an
application has been made and permission has been received.”
Documentation Version 1.0
101
Note: This means that you may use the AUSLIG-copyright data internally, but may not copy or
redistribute those data without permission from AUSLIG. AUSLIG invites requests for permission
to use/license the data for redistribution as it wants to encourage the use of the data.
NOAA’s standard disclaimer reads as follows:
“While every effort has been made to ensure that these data are accurate and reliable
within the limits of the current state of the art, NOAA cannot assume liability for any
damages caused by any inaccuracies in the data or as a result of the failure of the data
to function on a particular system. NOAA makes no warranty, expressed or implied,
nor does the fact of distribution constitute such a warranty. The user must be cautious
when using these data. None of the data represented here are perfect. As in many
complex scientific endeavors, error can be expected.”
Also, see Sections 6 and 7.
Global Land One-kilometer Base Elevation
102
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Milionesimo. Instituto Brasiliero de Geografia e Estatistica, Rio de Janeiro, Brazil. (Physical, including
topographic, maps of the world on a scale of 1:1,000,000; sheets covering Brazil.)
Instituto Brasiliero de Geografia e Estatistica, Geographical Survey Institute, and U.S. Geological
Survey, 1997. 30"-gridded DEMs from IBGE Maps. U.S. Geological Survey, EROS Data Center,
Sioux Falls, South Dakota.
Jet Propulsion Laboratory, 1998. DEM Auxiliary Datasets Preparation Plan: Digital Elevation
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Manaaki Whenua Landcare Research, 1996. 500-metre Digital Elevation Model for New Zealand.
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Imagery and Mapping Agency, Fairfax, Virginia. (Partly in GLOBE Task Team and others, 1999.)
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Center, 1997. 30"-gridded DEM from DTED, Precursors, and Derivatives. National Oceanic and
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National Snow and Ice Data Center and Jet Propulsion Laboratory, 1995. 30 Arc-Second Digital
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Global Land One-kilometer Base Elevation
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Appendix A.
Participants in the GLOBE Project and Acknowledgments
The GLOBE Task Team includes these agencies:
n Australian Department of Industry, Science and Tourism
Australian Surveying and Land Information Group (AUSLIG)
Scrivener Building, Dunlop Court
Fern Hill Park
Bruce, ACT 2617
Australia
http://www.auslig.gov.au
Peter Holland, General Manager
Telephone: +61 2 6201 4265
Fax: +61 2 6201 4368
Email: [email protected].au
John Payne, Director, Product Development
Email: [email protected].au
n Deutsches Zentrum für Luft- und Raumfahrt (DLR—German Aerospace Center)
German Remote Sensing Data Center (DFD)
DLR Oberpfaffenhofen
D-82234 Wessling
Germany
http://www.dfd.dlr.de
Gunter Schreier, Head of DFD
(also Head, Data Subgroup of CEOS-WGISS)
Telephone: +49-8153-28-1313
Email: gunter.schreier@dlr.de
Achim Roth
Email: achim.roth@dlr.de
Walter Knoepfle
Email: walter.knopf@dlr.de
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109
n Geographical Survey Institute
Cartographic Department
Map Information Division
Kitasato-1, Tsukuba-shi, Ibaraki-ken
305-D811
Japan
http://www.GSI-mc.go.jp
Hiromichi Maruyama, Director for Environmental Geographic Information
Department of Geography
Email: [email protected]
Hiroshi Masaharu, Head of the Third Division
Department of Geography
Telephone: +81-298-64-2942
Fax: +81-298-64-2655
Email: [email protected]
n National Aeronautics and Space Administration
California Institute of Technology
Jet Propulsion Laboratory
Science Data Processing Systems (Section 388)
Cartographic Applications Group
Mail Stop 168/527
4800 Oak Grove Drive
Pasadena, California 91109-8099
U.S.A.
Nevin A. Bryant, Group Supervisor
Telephone: +1-818-354-7236
Fax: +1-818-354-8982
Email: [email protected]
Thomas L. Logan, GIS Group Leader
Telephone: +1-818-354-4032
Fax: +1-818-354-8982
Email: [email protected]
n University College London
Department of Geomatic Engineering
Gower Street
London WC1E 6BT
United Kingdom
http://www.ge.ucl.ac.uk/staff/jpmuller.html
J.-P. Muller, Professor
Telephone: +44-171-380-7227
Email: [email protected]
Global Land One-kilometer Base Elevation
110
? U.S. Department of Commerce
National Oceanic and Atmospheric Administration
National Environmental Satellite, Data, and Information Service
National Geophysical Data Center
325 Broadway
Boulder, Colorado 80305
U.S.A.
http://www.ngdc.noaa.gov
David A. Hastings, Secretary of GLOBE
Fax: +1-303-497-6513
Paula K. Dunbar, Manager of Topographic Data
Telephone: +1-303-497-6084
Email: [email protected]
? U.S. Department of Defense
National Imagery and Mapping Agency
NIMA Bethesda (MS: D80) (Office ES)
4600 Sangamore Road
Bethesda, Maryland 20806-5003
U.S.A.
http://www.nima.mil
Gerald M. Elphingstone, Technical Advisor in Digital Photogrammetry
Thomas M. Carson, Shuttle Radar Topography Mapper Program
Email: [email protected]
The U.S. Geological Survey frequently participated in GLOBE meetings, and hosted one GLOBE
meeting, but does not consider itself a member of the GLOBE Task Team.
GLOBE has been affiliated with the following international efforts:
? Committee on Earth Observation Satellites (CEOS)
Working Group on Information Systems and Services (WGISS)
Data Subgroup
(The GLOBE Task Team reports to the CEOS-WGISS Data Subgroup)
? International Council of Scientific Unions (ICSU)
International Geosphere-Biosphere Programme (IGBP)
Data and Information System (IGBP-DIS)
(GLOBE is a part of Focus I of IGBP-DIS)
? International Society of Photogrammetry and Remote Sensing
Commission IV: Mapping and GIS
Working Group IV/6: Global Databases Supporting Environmental Monitoring
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Acknowledgments:
Some of this text is taken verbatim (or with modest modification) from USGS (1997b), especially
some of the descriptions of USGS procedures in developing USGS/GTOPO30. Other text is based
on TerrainBase documentation (Row and others, 1995). In addition, this project is indebted to its six
previous and concurrent efforts at developing global digital elevation data sets:
1. ETOPO5 (1984–1985), developed by Margo Edwards of Washington University (St. Louis)
for NGDC
2. ELEVBATHY (1984–1985), developed by David Hastings at the EROS Data Center for
NASA MAGSAT data analysis
3. TerrainBase (1991–1994), developed by Lee Row and David Hastings at NGDC
4. JPL/MISR DEM (1994–1995), developed by Nevin Bryant, Richard Fretz, Niles Ritter and
Rafael Alanis of the Cartographic Applications Group at JPL for the MISR mission
5. GTOPO30 (1993–1997), developed by a team led by Susan Greenlee at the EROS Data
Center
6. DTED Level 1, under development for many years at the National Imagery and Mapping
Agency, formerly the Defense Mapping Agency; and DTED Level 0 (1994–1996), initially
designed in conjunction with the GLOBE Task Team, later released to the public as well as to
GLOBE
The histograms shown in Plates 1–30 (pages 19–34) were developed with the Generic Mapping Tool
(GMT), by Paul Wessell and Walter Smith (http://www.soest.Hawaii.edu/gmt/). The figure showing
coverage of the AUSLIG/NGDC DEM for Australia (page 38) was developed in the Geographic
Resources Analysis Support System (GRASS) GIS (http://www.baylor.edu/~grass and http://
sunsite.unc.edu/LDP/HOWTO/mini/GIS-GRASS.html).
Global Land One-kilometer Base Elevation
112
Appendix B. Glossary of Acronyms
ADD Antarctic Digital Database (of SCAR)
AGIP Azienda Generale Italiana Petroli (an Italian petroleum company)
AMS Army Map Service, 1946–1968
ANUDEM Australian National University digital elevation modeling software package
AUSLIG Australian Surveying and Land Information Group
B.A.D. Best Available Data (better than G.O.O.D. GLOBE data, but with noted restrictions)
BSTATS An ERDAS function
CALTECH California Institute of Technology
CEOS Committee on Earth Observation Satellites
DCW Digital Chart of the World
DEM Digital elevation model. This is used in the generic sense of a raster data set attempting
to represent the elevation of the dry land surface. It does not imply any particular data
format or collection methodology. It also does not include other forms of digital
elevation data, such as digitized points or contours.
DFD Deutsches Fernerkundungsdatenzentrum (German Remote Sensing Data Center)
DIS Data and Information System
DLR Deutsches Zentrum für Luft- und Raumfahrt (German Aerospace Center)
DMA Defense Mapping Agency, 1972–1996
DOD U.S. Department of Defense
DTED Digital Terrain Elevation Data (NIMA DEMs)
EDC EROS Data Center
EOS Earth Observing System (a NASA program)
EPA Environmental Protection Agency
ERDAS Earth Resources Data Analysis System (a software package)
EROS Earth Resources Observation Systems
ERS Earth Resources Satellite (European Space Agency satellite series)
ESRI Environmental Science Research Institute, Inc.
ETOPO5 5-minute global DEM (the first global DEM, which also included bathymetry)
FGDC Federal Geographic Data Committee
FIXHEAD An ERDAS function
FTP File Transfer Protocol
GIS Geographic information system
GLOBE Global Land One-kilometer Base Elevation project
GMT Generic Mapping Tool
GNGTS Gruppo Nazionale di Geofisica della Terra Solida (Italy)
G.O.O.D. Globally Only Open-access Data (unrestricted GLOBE data)
GRASS Geographic Resources Analysis Support System GIS
GSFC Goddard Space Flight Center
GSI Geographical Survey Institute, Japan
GTOPO30 USGS’s name for its global 30" DEM
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113
GZIP A software utility
IBGE Instituto Brasiliero de Geografia e Estatistica
ICSU International Council of Scientific Unions
IGBP International Geosphere-Biosphere Programme
IMW International Map of the World
ISPRS International Society of Photogrammetry and Remote Sensing
JPL Jet Propulsion Laboratory (a NASA research center administered by the California
Institute of Technology)
LCR Manaaki Whenua Landcare Research, Ltd., New Zealand
MISR Multiangle Imaging SpectroRadiometer
MPI Ministerio della Publica Instruziane (Italian Ministry of Public Instruction)
NASA National Aeronautics and Space Administration
NESDIS National Environmental Satellite, Data, and Information Service
NGDC National Geophysical Data Center
NIMA National Imagery and Mapping Agency
NOAA National Oceanic and Atmospheric Administration
NSIDC National Snow and Ice Data Center
ONC Operational Navigation Chart
OLS Operational Linescan System
RMSE Root-mean-square error
SCAR Scientific Committee on Antarctic Research
SDTS Spatial Data Transfer Standard
SGN Servizio Geologico Nazionale (National Geological Service (Italy))
SRTM Shuttle Radar Topography Mapper mission
UCL University College London
UNO United Nations Organization
URL Uniform Resource Locator (Web address)
USATC U.S. Army Topographic Command
USGS U.S. Geological Survey
WGD Working Group on Data
WGISS Working Group on Information Systems and Services
WGS World Geodetic System
WVS World Vector Shoreline
WWW World Wide Web
Global Land One-kilometer Base Elevation
114
Appendix C.
Federal Geographic Data Committee Metadata, and
Global Change Master Directory .DIF for GLOBE
Below are the Federal Geographic Data Committee (FGDC) metadata for GLOBE Version 1.0. Global
Change Master Directory .dif file contents begin on page 130.
Federal Geographic Data Committee Metadata
We adapted answers to several FGDC metadata fields:
n Publication_Date: “Varies” is not allowed, but accurately describes several GLOBE source
data fields. Where “varies” is the correct answer, “Unknown” (an FGDC-allowable but
technically incorrect answer) is used.
n Source_Scale_Denominator: Only an integer value is allowed in this field. “Varies” is not
allowed, but accurately describes several GLOBE source data sets, especially when sources
include maps and imagery of varying scales. Some sources, such as those used to make
DTED, are undocumented. In these cases, 99999999 is used.
The following is the FGDC metadata for GLOBE Version 1.0:
1 Identification_Information:
1.1 Citation
1.1.8.1 Originator: National Geophysical Data Center (editor)
1.1.8.2 Publication_Date: 1998
1.1.8.4 Title: GLOBE: Global Land One-km Base Elevation 30-sec. DEM
1.1.8.5 Edition: Version 1.0
1.1.8.6 Geospatial_Data_Presentation_Form: Model
1.1.8.7 Series_Information:
1.1.8.7.1 Series_Name: Key to Geophysical Records Documentation (KGRD) 34
1.1.8.7.2 Issue_Identification: Hastings, David A., and P. K. Dunbar. Global Land One-km
Base Elevation (GLOBE) Digital Elevation Model Documentation, National Oceanic
and Atmospheric Administration, National Geophysical Data Center, Publication
KGRD 34, Boulder, Colorado, 1999.
1.1.8.8 Publication_Information:
1.1.8.8.1 Publication_Place: Boulder, CO
1.1.8.8.2 Publisher: National Geophysical Data Center
1.1.8.10 Online_Linkage: http://www.ngdc.noaa.gov/seg/topo/globe.shtml
1.2 Description:
1.2.1 Abstract:
GLOBE is a project to develop the best available 30-arc-second (nominally 1 kilometer) global
digital elevation data set. This Version 1.0 of GLOBE contains data from 11 sources, and 18
combinations of source and lineage. It continues much in the tradition of the National
Geophysical Data Center’s TerrainBase (DIF 1090), as TerrainBase served as a generally
lower-resolution prototype of GLOBE data management and compilation techniques.
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115
The GLOBE mosaic has been compiled onto CD-ROMs for the international user community.
It is also available from the World Wide Web and via anonymous FTP. Improvements to the
global model are anticipated, as appropriate data and/or methods are made available. In
addition, individual contributions to GLOBE (several areas have more than one candidate)
should become available at the same Web site.
GLOBE may be used for technology development, such as helping plan infrastructure for
cellular communications networks, other public works, satellite data processing, and
environmental monitoring and analysis. GLOBE prototypes (and probably GLOBE itself after
its release) has been used to help develop terrain avoidance systems for aircraft. In all cases,
GLOBE data should be treated as any potentially useful but guaranteed imperfect data set.
Mission- or life-critical applications should consider the documented artifacts, as well as likely
undocumented imperfections, in the data.
1.2.2 Purpose: Provide Topographic Data for Scientific, Technical, and other Applications
1.2.3 Supplemental_Information:
1.2.3.1 Entry_ID: FE01180
1.2.3.2 Sensor_Name: ALTIMETERS
1.2.3.2 Sensor_Name: ECHO SOUNDERS
1.2.3.2 Sensor_Name: CAMERAS
1.2.3.2 Sensor_Name: IMAGING RADIOMETERS
1.2.3.3 Source_Name: AIRCRAFT
1.2.3.3 Source_Name: SATELLITES, MISCELLANEOUS
1.2.3.3 Source_Name: FIELD SURVEYS
1.2.3.3 Source_Name: SHIPS
1.2.3.3 Source_Name: MODELS
1.2.3.5 Originating_Center: National Geophysical Data Center
1.2.3.6 Storage_Medium: 3480 Cartridge
1.2.3.6 Storage_Medium: CD-ROM
1.2.3.6 Storage_Medium: Online
1.2.3.9 NOAAServer URLs:
1.2.3.9.1 Moreinfo: http://www.ngdc.noaa.gov/seg/topo/globe.shtml
1.3 Time_Period_of_Content:
1.3.1 Currentness_Reference: Publication date
1.3.1.3 Range_of_Dates/Times:
1.3.1.3.1 Beginning_Date: 1975-01-01
1.3.1.3.3 Ending_Date: Publication date
1.4 Status:
1.4.1 Progress: Complete
1.4.2 Maintenance_and_Update_Frequency: Irregular
1.5 Spatial_Domain:
1.5.1 Bounding_Coordinates:
1.5.1.1 West_Bounding_Coordinate: -180.0
1.5.1.2 East_Bounding_Coordinate: 180.0
1.5.1.3 North_Bounding_Coordinate: 90.0
1.5.1.4 South_Bounding_Coordinate: -90.0
1.6 Keywords:
1.6.1 Theme:
1.6.1.1 Theme_Keyword_Thesaurus: Uncontrolled Keywords as used in GCMD DIF
1.6.1.2 Theme_Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Landforms
1.6.1.2 Theme_Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Relief
Global Land One-kilometer Base Elevation
116
1.6.1.2 Theme_Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Surface
Roughness
1.6.1.2 Theme_Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Terrain
Elevation
1.6.1.2 Theme_Keyword: EARTH SCIENCE > OCEANS > Coastal Processes > Coastal
Elevation
1.6.1.2 Theme_Keyword: INFOTERRA > Environmental Monitoring > Environmental
Measurements > Elevation
1.6.1.2 Theme-Keyword: CIESIN > ENVIRONMENTAL PROTECTION > GEOGRAPHY AND
LAND COVER > TOPOGRAPHIC DATA
1.6.1.2 Theme-Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING >
GEOGRAPHIC INFORMATION SYSTEMS
1.6.1.2 Theme-Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING >
MODELING
1.6.1.2 Theme-Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING >
RESEARCH AND DEVELOPMENT > MODELS
1.6.1.1 Theme_Keyword_Thesaurus: None
1.6.1.2 Theme_Keyword: DEM
1.6.1.2 Theme_Keyword: Digital elevation model
1.6.1.2 Theme_Keyword: Elevations
1.6.1.2 Theme_Keyword: Topography
1.6.2 Place:
1.6.2.1 Place_Keyword_Thesaurus: Uncontrolled Keywords GCMD
1.6.2.2 Place_Keyword: Location: Global
1.6.4 Temporal:
1.6.4.1 Temporal_Keyword_Thesaurus: None
1.6.4.2 Temporal_Keyword: Generally current (no special instant in time)
1.7 Access_Constraints: None
1.8 Use_Constraints: None for one (G.O.O.D.) version of GLOBE. Copyright restrictions on
derivation/reproduction or redistribution of another (B.A.D.) version of GLOBE, as described in
GLOBE documentation.
Recommend: Cite GLOBE as a scientific publication: GLOBE Task Team and others (Hastings,
David A., Paula K. Dunbar, Gerald M. Elphingstone, Mark Bootz, Hiroshi Murakami, Hiroshi
Maruyama, Hiroshi Masaharu, Peter Holland, John Payne, Nevin A. Bryant, Thomas L. Logan, J.-
P. Muller, Gunter Schreier, and John S. MacDonald), eds., 1999. The Global Land One-kilometer
Base Elevation (GLOBE) Digital Elevation Model, Version 1.0. National Oceanic and Atmospheric
Administration, National Geophysical Data Center, 325 Broadway, Boulder, Colorado 80303,
U.S.A. Digital data base on the World Wide Web (URL: http://www.ngdc.noaa.gov/seg/topo/
globe.shtml) and CD-ROMs.
1.9 Point of Contact:
1.9.10.2 Contact_Organization_Primary
1.9.10.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data Center
1.9.10.2.2 Contact_Person: David A. Hastings
1.9.10.4 Contact_Address
1.9.10.4.1 Address_Type: mailing address
1.9.10.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
1.9.10.4.3 City: Boulder
1.9.10.4.4 State_or_Province: CO
1.9.10.4.5 Postal_Code: 80303
1.9.10.4.6 Country: USA
1.9.10.5 Contact_Voice_Telephone: (303) 497-6729
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1.9.10.6 Contact_TDD/TTY_Telephone: (303) 497-6958
1.9.10.7 Contact_Facsimile_Telephone: (303) 497-6513
1.9.10.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2 Data_Quality_Information
2.1 Attribute_Accuracy
2.1.1 Attribute_Accuracy_Report: Some of the methods used to measure elevation do not actually
measure that of the ground surface. See Section 6 of GLOBE documentation (KGRD 34).
2.1.2 Quantitative_Attribute_Accuracy_Assessment:
2.1.2.1 Attribute_Accuracy_Value: variable may range +/- 10 to +/- 250 meters or more
2.1.2.2 Attribute_Accuracy_Explanation: statistical and histogram analysis
2.2 Logical_Consistency_Report: GLOBE documentation discusses logical consistency implicitly in its
quality control and accuracy assessments. Adjacent data files have no gaps between themselves.
A few land areas of 30 arc-seconds in size may be missing. Most smaller areas are missing.
Bathymetry is not included in GLOBE Version 1.0. (See NGDC’s TerrainBase or ETOPO5 for
lower-resolution bathymetric data. GLOBE Version 2.0 may include bathymetric data.)
2.3 Completeness_Report: GLOBE has full global coverage of the land surface within the context of
its 30-arc-second gridding. (Smaller features are usually not seen.)
2.4 Positional_Accuracy:
2.4.1 Horizontal_Positional_Accuracy:
2.4.1.1 Horizontal_Positional_Accuracy_Report: Arc-seconds of latitude and longitude
2.4.1.2 Quantitative_Horizontal_Positional_Accuracy_Assessment:
2.4.1.2.1 Horizontal_Positional_Accuracy_Value: 18.0
2.4.1.2.2 Horizontal_Positional_Accuracy_Explanation: Few elevation values should be more
than about 18 arc-seconds from their implied location in the 30 arc-second grid.
2.4.2 Vertical_Positional_Accuracy:
2.4.2.1 Vertical_Positional_Accuracy_Report: Vertical accuracy varies by source materials used
in GLOBE. Values may range from 10 meters to 250 meters (and in rare cases, to over
500 meters in elevation).
2.4.2.2 Quantitative_Vertical_Positional_Accuracy_Assessment:
2.4.2.2.1 Vertical_Positional_Accuracy_Value:
2.4.2.2.2 Vertical_Positional_Accuracy_Explanation: Methods of assessing vertical accuracy
include statistical analyses of high-resolution DEM sources by their producers,
assessments of contour intervals in some source maps, histogram analyses of DEMs
lacking in more detailed assessments. (Histograms often show “spikes” suggesting
contour intervals of source maps.)
2.5 Lineage:
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: National Imagery and Mapping Agency
2.5.1.1.1.2 Publication Date: 1996
2.5.1.1.1.4 Title: Digital Terrain Elevation Data
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: magnetic tape
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: 1975
Global Land One-kilometer Base Elevation
118
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1996
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DTED
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Australian Surveying and Land Information Group
2.5.1.1.1.2 Publication Date: 1996
2.5.1.1.1.4 Title: Australian Point Elevation File
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1996
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: AUSLIG elevation point file
2.5.1.6 Source_Contribution: Point elevations
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Geographical Survey Institute of Japan
2.5.1.1.1.2 Publication Date: 1995
2.5.1.1.1.4 Title: 30 arc-second DEM of Japan
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 200000
2.5.1.3 Type_of_Source_Media: Disc
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1995
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DEM for Japan
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Servizio Geologico Nazionale (Italy)
2.5.1.1.1.2 Publication Date: 1985
2.5.1.1.1.4 Title: Italian DEM for gravity terrain corrections
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: model
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119
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1985
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: Italian DEM for gravity terrain corrections
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Manaaki Whenua Landcare Research, Ltd. (NZ)
2.5.1.1.1.2 Publication Date: 1995
2.5.1.1.1.4 Title: 500-metre DEM for New Zealand
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 63360
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1995
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: 500-metre DEM for New Zealand
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: H.J. Zwally and others
2.5.1.1.1.2 Publication Date: 1997
2.5.1.1.1.4 Title: DEM for Greenland
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: 1985
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1986
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DEM for Greenland
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
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120
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Defense Mapping Agency (now NIMA)
2.5.1.1.1.2 Publication Date: 1992
2.5.1.1.1.4 Title: Digital Chart of the World
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Atlas
2.5.1.2 Source_Scale_Denominator: 1000000
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: 1987
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1992
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DCW
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Army Map Service (U.S. Army, now part of NIMA)
2.5.1.1.1.2 Publication Date: Unknown
2.5.1.1.1.4 Title: Various maps
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Atlas
2.5.1.2 Source_Scale_Denominator: 1000000
2.5.1.3 Type_of_Source_Media: Paper
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: Unknown
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: AMS maps
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Fundacao Instituto Brasiliero de Geografia e Estatistica (Brazil),
published under the International Map of the World series
2.5.1.1.1.2 Publication Date: Unknown
2.5.1.1.1.4 Title: Various maps
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Atlas
2.5.1.2 Source_Scale_Denominator: 1000000
2.5.1.3 Type_of_Source_Media: Paper
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
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2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: Unknown
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: IMW maps
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Ministerio de Guerra (Peru)
2.5.1.1.1.2 Publication Date: 1984
2.5.1.1.1.4 Title: Mapa Fisico Politico del Peru
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Map
2.5.1.2 Source_Scale_Denominator: 1000000
2.5.1.3 Type_of_Source_Media: Paper
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1984
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: Peru map
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Scientific Committee on Antarctic Research
2.5.1.1.1.2 Publication Date: 1994
2.5.1.1.1.4 Title: Antarctic Digital Database
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Atlas
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1994
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: ADD
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: National Oceanic and Atmospheric Administration (National
Geophysical Data Center)
2.5.1.1.1.2 Publication Date: Unknown
2.5.1.1.1.4 Title: Digital Topographic Data
Global Land One-kilometer Base Elevation
122
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: Unknown
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: NGDC Topographic Data
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: GLOBE Task Team of the Committee on Earth Observation Satellites,
via the National Oceanic and Atmospheric Administration (National Geophysical
Data Center)
2.5.1.1.1.2 Publication Date: 1999
2.5.1.1.1.4 Title: Global Land One-km Base Elevation Digital Elevation Model
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1999
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: GLOBE
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: U.S. Geological Survey
2.5.1.1.1.2 Publication Date: Unknown
2.5.1.1.1.4 Title: Digital elevation models
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 250000
2.5.1.3 Type_of_Source_Media: Magnetic tape
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
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123
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1970
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: USGS DEMs
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: U.S. Geological Survey
2.5.1.1.1.2 Publication Date: 1997
2.5.1.1.1.4 Title: GTOPO30
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1996
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: USGS GTOPO30
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: National Oceanic and Atmospheric Administration (National
Geophysical Data Center)
2.5.1.1.1.2 Publication Date: 1997
2.5.1.1.1.4 Title: AUSLIG/NGDC DEM for Australia
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1996
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DEM for Australia
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: National Oceanic and Atmospheric Administration (National
Geophysical Data Center)
Global Land One-kilometer Base Elevation
124
2.5.1.1.1.2 Publication Date: 1994
2.5.1.1.1.4 Title: DEM for Italy
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: CD-ROM
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1984
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DEM for Italy
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: Jet Propulsion Laboratory
2.5.1.1.1.2 Publication Date: 1996
2.5.1.1.1.4 Title: Zwally (and others)/NSIDC/JPL DEM for Greenland
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 99999999
2.5.1.3 Type_of_Source_Media: File transfer
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1994
2.5.1.4.1.3.4 Ending_Time: Unknown
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: Zwally (and others)/NSIDC/JPL DEM for Greenland
2.5.1.6 Source_Contribution: Elevation data
2.5.1 Source_Information:
2.5.1.1 Source_Citation:
2.5.1.1.1 Citation_Information:
2.5.1.1.1.1 Originator: U.S. Geological Survey
2.5.1.1.1.2 Publication Date: 1996
2.5.1.1.1.4 Title: DEM for New Zealand
2.5.1.1.1.6 Geospatial_Data_Presentation_Form: Model
2.5.1.2 Source_Scale_Denominator: 63360
2.5.1.3 Type_of_Source_Media: Online
2.5.1.4 Source_Time_Period_of_Content:
2.5.1.4.1 Time_Period_Information:
2.5.1.4.1.3 Range_of_Dates/Times:
2.5.1.4.1.3.1 Beginning_Date: Unknown
2.5.1.4.1.3.2 Beginning_Time: Unknown
2.5.1.4.1.3.3 Ending_Date: 1996
2.5.1.4.1.3.4 Ending_Time: Unknown
Documentation Version 1.0
125
2.5.1.4.2 Source_Currentness_Reference: Publication date
2.5.1.5 Source_Citation_Abbreviation: DEM for New Zealand
2.5.1.6 Source_Contribution: Elevation data
2.5.2 Process_Step:
2.5.2.1 Process_Description: DTED has had several processing runs at the Defense Mapping
Agency (now NIMA), the U.S. Geological Survey (USGS), and the National Geophysical
Data Center (NGDC), before being mosaicked into GLOBE Version 1.0. Generally, DTED
Level 1 data were resampled to 30 arc-second gridding by different methods at different
times, mosaicked from 1x1 degree DTED cells, quality-checked, then blended by USGS
and/or NGDC into regional or GLOBAL DEMs. The latter were used for the final blending
into GLOBE. GLOBE documentation gives more detail.
2.5.2.2 Source_Used_Citation_Abbreviation: DTED
2.5.2.3 Process_Date: 1997
2.5.2.5 Source_Produced_Citation_Abbreviation: USGS DEMs
2.5.2.5 Source_Produced_Citation_Abbreviation: NGDC topographic data
2.5.2.5 Source_Produced_Citation_Abbreviation: GTOPO30
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data
Center
2.5.2.6.2.2 Contact_Person: David A. Hastings
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
2.5.2.6.4.3 City: Boulder
2.5.2.6.4.4 State_or_Province: CO
2.5.2.6.4.5 Postal_Code: 80303
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (303) 497-6729
2.5.2.6.6 Contact_TDD/TTY_Telephone: (303) 497-6958
2.5.2.6.7 Contact_Facsimile_Telephone: (303) 497-6513
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2.5.2 Process_Step:
2.5.2.1 Process_Description: The AUSLIG elevation point file was interpolated to a 30 arc-
second grid file using the GRASS-GIS function s.surf.idw (using 3 nearest points). This
work was done at the National Geophysical Data Center, under an agreement with
AUSLIG, to produce a model for use in GLOBE.
2.5.2.2 Source_Used_Citation_Abbreviation: AUSLIG elevation point file
2.5.2.3 Process_Date: 1997
2.5.2.5 Source_Produced_Citation_Abbreviation: DEM for Australia
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data
Center
2.5.2.6.2.2 Contact_Person: David A. Hastings
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
2.5.2.6.4.3 City: Boulder
2.5.2.6.4.4 State_or_Province: CO
2.5.2.6.4.5 Postal_Code: 80303
Global Land One-kilometer Base Elevation
126
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (303) 497-6729
2.5.2.6.6 Contact_TDD/TTY_Telephone: (303) 497-6958
2.5.2.6.7 Contact_Facsimile_Telephone: (303) 497-6513
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2.5.2 Process_Step:
2.5.2.1 Process_Description: The Italian DEM for gravity terrain corrections was resampled to
30" gridding by the National Geophysical Data Center (NGDC), following a joint design by
NGDC and the Servizio Geologico Nazionale of Italy.
2.5.2.2 Source_Used_Citation_Abbreviation: Italian DEM for gravity terrain corrections
2.5.2.3 Process_Date: 1994
2.5.2.5 Source_Produced_Citation_Abbreviation: DEM for Italy
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data
Center
2.5.2.6.2.2 Contact_Person: David A. Hastings
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
2.5.2.6.4.3 City: Boulder
2.5.2.6.4.4 State_or_Province: CO
2.5.2.6.4.5 Postal_Code: 80303
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (303) 497-6729
2.5.2.6.6 Contact_TDD/TTY_Telephone: (303) 497-6958
2.5.2.6.7 Contact_Facsimile_Telephone: (303 497-6513
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2.5.2 Process_Step:
2.5.2.1 Process_Description: The 500-m DEM for New Zealand was reprojected from the New
Zealand national projection and datum to latitude-longitude 30" gridding by the U.S.
Geological Survey.
2.5.2.2 Source_Used_Citation_Abbreviation: 500-m DEM for New Zealand
2.5.2.3 Process_Date: 1996
2.5.2.5 Source_Produced_Citation_Abbreviation: DEM for New Zealand
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: U.S. Geological Survey
2.5.2.6.2.2 Contact_Person: Susan K. Greenlee
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: USGS EROS Data Center
2.5.2.6.4.3 City: Sioux Falls
2.5.2.6.4.4 State_or_Province: SD
2.5.2.6.4.5 Postal_Code: 57198
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (605) 594-6011
2.5.2.6.7 Contact_Facsimile_Telephone: (605) 594-6589
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2.5.2 Process_Step:
2.5.2.1 Process_Description: The NSIDC DEM for Greenland was resampled to 30 arc-seconds
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127
by the Jet Propulsion Laboratory, and blended with other data where available. The latter
blended data were removed for transmittal to the GLOBE Task Team for GLOBE
assembly, as they were not needed.
2.5.2.2 Source_Used_Citation_Abbreviation: Zwally (and others)/NSIDC/JPL DEM for Greenland
2.5.2.3 Process_Date: 1997
2.5.2.5 Source_Produced_Citation_Abbreviation: Zwally (and others)/NSIDC/JPL DEM for
Greenland
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: Jet Propulsion Laboratory
2.5.2.6.2.2 Contact_Person: Nevin A. Bryant
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: Jet Propulsion Laboratory, 4800 Oak Grove Drive
2.5.2.6.4.3 City: Pasadena
2.5.2.6.4.4 State_or_Province: CA
2.5.2.6.4.5 Postal_Code: 91109-8009
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (818) 354-7236
2.5.2.6.7 Contact_Facsimile_Telephone: (818) 354-8982
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
2.5.2 Process_Step:
2.5.2.1 Process_Description: The DCW hypsography was converted to 30" latitude-longitude
grids by the U.S. Geological Survey. Prototyping of techniques also involved University
College London. The ANUDEM contour-to-grid software of Australian National University
was used, which incorporates streamlines to help guide the gridding process. The other
cartographic source materials were also converted to grids by the same general methods.
Those other sources, which were originally in hardcopy format, were adapted for input to
this processing by the Geographical Survey Institute of Japan. The exception is the
Antarctic Digital Database, which was also in digital format
2.5.2.2 Source_Used_Citation_Abbreviation: DCW
2.5.2.2 Source_Used_Citation_Abbreviation: Peru map
2.5.2.2 Source_Used_Citation_Abbreviation: AMS maps
2.5.2.2 Source_Used_Citation_Abbreviation: IMW maps
2.5.2.2 Source_Used_Citation_Abbreviation: ADD
2.5.2.3 Process_Date: 1996
2.5.2.5 Source_Produced_Citation_Abbreviation: USGS GTOPO30
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: U.S. Geological Survey
2.5.2.6.2.2 Contact_Person: Susan K. Greenlee
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: USGS EROS Data Center
2.5.2.6.4.3 City: Sioux Falls
2.5.2.6.4.4 State_or_Province: SD
2.5.2.6.4.5 Postal_Code: 57198
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (605) 594-6011
2.5.2.6.7 Contact_Facsimile_Telephone: (605) 594-6589
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
Global Land One-kilometer Base Elevation
128
2.5.2 Process_Step:
2.5.2.1 Process_Description: All candidate data sets for GLOBE were evaluated, and blended
using the GRASS-GIS function r.patch (with appropriate masking to avoid incorporating
the wrong parts of candidates into the model).
2.5.2.2 Source_Used_Citation_Abbreviation: DTED
2.5.2.2 Source_Used_Citation_Abbreviation: DEM for Japan
2.5.2.2 Source_Used_Citation_Abbreviation: DEM for Italy
2.5.2.2 Source_Used_Citation_Abbreviation: AUSLIG/NGDC DEM for Australia
2.5.2.2 Source_Used_Citation_Abbreviation: Zwally (and others)/NSIDC/JPL DEM for Greenland
2.5.2.2 Source_Used_Citation_Abbreviation: NGDC topographic data
2.5.2.2 Source_Used_Citation_Abbreviation: USGS DEMs
2.5.2.2 Source_Used_Citation_Abbreviation: USGS GTOPO30
2.5.2.3 Process_Date: 1998
2.5.2.5 Source_Produced_Citation_Abbreviation: GLOBE
2.5.2.6 Process_Contact:
2.5.2.6.2 Contact_Organization_Primary
2.5.2.6.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data
Center
2.5.2.6.2.2 Contact_Person: David A. Hastings
2.5.2.6.4 Contact_Address
2.5.2.6.4.1 Address_Type: Mailing address
2.5.2.6.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
2.5.2.6.4.3 City: Boulder
2.5.2.6.4.4 State_or_Province: CO
2.5.2.6.4.5 Postal_Code: 80303
2.5.2.6.4.6 Country: USA
2.5.2.6.5 Contact_Voice_Telephone: (303) 497-6729
2.5.2.6.6 Contact_TDD/TTY_Telephone: (303) 497-6958
2.5.2.6.7 Contact_Facsimile_Telephone: (303) 497-6513
2.5.2.6.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
3 Spatial_Data_Organization_Information:
3.2 Direct_Spatial_Reference_Method: Raster
3.4 Raster_Object_Information:
3.4.1 Raster_Object_Type: Grid Cell
3.4.2 Row_Count: 21600
3.4.3 Column_Count: 43200
4 Spatial_Reference_Information
4.1 Horizontal_Coordinate_System_Definition:
4.1.1 Geographic:
4.1.1.1 Latitude_Resolution: 30.0
4.1.1.2 Longitude_Resolution: 30.0
4.1.1.3 Geographic_Coordinate_Units: Decimal seconds
4.2 Vertical_Coordinate_System_Definition:
4.2.1 Altitude_System_Definition:
4.2.1.1 Altitude_Datum_Name: Mean sea level
4.2.1.2 Altitude_Resolution: 1.0
4.2.1.3 Altitude_Distance_Units: Meters
4.2.1.4 Altitude_Encoding_Method: Attribute values
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129
6 Distribution_Information
6.1 Distributor
6.1.10 Contact_Information
6.1.10.2 Contact_Organization_Primary
6.1.10.2.1 Contact_Organization: NOAA/NESDIS/NGDC > National Geophysical Data Center
6.2.10.2.2 Contact_Person: Paula K. Dunbar
6.1.10.4 Contact_Address
6.1.10.4.1 Address_Type: Mailing Address
6.1.10.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
6.1.10.4.3 City: Boulder
6.1.10.4.4 State_or_Province: CO
6.1.10.4.5 Postal_Code: 80303
6.1.10.4.6 Country: USA
6.1.10.5 Contact_Voice_Telephone: (303) 497-6084
6.1.10.6 Contact_TDD/TTY_Telephone: (303) 497-6958
6.1.10.7 Contact_Facsimile_Telephone: (303) 497-6513
6.1.10.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
6.2 Resource_Description: Digital topographic model
6.3 Distribution_Liability:
Disclaimer: While every effort has been made to ensure that these data are accurate and reliable
within the limits of the current state of the art, NOAA cannot assume liability for any damages
caused by any errors or omissions in the data, nor as a result of the failure of the data to function
on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of
distribution constitute such a warranty.
6.4 Standard_Order_Process:
6.4.2 Digital_Form:
6.4.2.1 Digital_Transfer_Information
6.4.2.1.1 Format_Name: BSQ (Imagery, band interleaved sequential)
6.4.2.1.6 File_Decompression_Technique: GZIP for selected versions with .gz file extensions.
No compression applied to files without .gz extensions.
6.4.2.1.7 Transfer_size: 1800.0
6.4.2.2 Digital_Transfer_Option
6.4.2.2.1 Online_Option:
6.4.2.2.1.1 Computer_Contact_Information:
6.4.2.2.1.1.1 Network_Address:
6.4.2.2.1.1.1.1Network_Resource_Name: http://www.ngdc.noaa.gov/seg/topo/globe.shtml
6.4.2.2.2 Offline_Option
6.4.2.2.2.1 Offline_Media: CD-ROM
6.4.2.2.2.2 Recording_Capacity
6.4.2.2.2.2.1 Recording_Density: 2048
6.4.2.2.2.2.2 Recording_Density_Units: Bytes per block
6.4.2.2.2.3 Recording_Format: ISO 9660
6.4.3 Fees: Depends on the data set
6.4.4 Ordering_Instructions: Price information is available upon request. Prepay by check, money
order or bank card. There is a standard handling charge, with additional costs for special
handling. Orders may be placed via fax, email, regular mail, or telephone.
6.4.5 Turnaround: 4 Days
6.5 Custom_Order_Process: Contact Data Center for information
6.6 Technical_Prerequisites: Contact Data Center for information
Global Land One-kilometer Base Elevation
130
7 Metadata_Reference_Information
7.1 Metadata_Date: 1998-02-01
7.2 Metadata_Review_Date: 1999-03-01
7.3 Metadata_Future_Review_Date: 2001-06-01
7.4 Metadata_Contact:
7.4.10 Contact_Information:
7.4.10.1 Contact_Organization_Primary:
7.4.10.1.1 Contact_Person: David A. Hastings
7.4.10.1.2 Contact_Organization: National Geophysical Data Center
7.4.10.4 Contact_Address
7.4.10.4.1 Address_Type: Mailing address
7.4.10.4.2 Address: NOAA/NESDIS/NGDC (E/GC1) 325 Broadway
7.4.10.4.3 City: Boulder
7.4.10.4.4 State_or_Province: CO
7.4.10.4.5 Postal_Code: 80303
7.4.10.4.6 Country: USA
7.4.10.5 Contact_Voice_Telephone: (303) 497-6729
7.4.10.6 Contact_TDD/TTY_Telephone: (303) 497-6958
7.4.10.7 Contact_Facsimile_Telephone: (303) 497-6513
7.4.10.8 Contact_Electronic_Mail_Address: Email: Internet > [email protected]
7.5 Metadata_Standard_Name: Content Standards for Digital Geospatial Metadata
7.6 Metadata_Standard_Version: June 8, 1994
7.8 Metadata_Access_Constraints: none
7.9 Metadata_Use_Constraints: None
Global Change Master Directory .DIF for GLOBE
The following is a Global Change Master Directory .dif entry generated from the information listed
above.
Entry_ID: FE01180
Entry_Title: GLOBE: Global Land One-km Base Elevation 30-sec. DEM
Start_date: 1940-01-01
Stop_date: Publication date
Sensor_Name:
Source_Name:
Group: Investigator
Last_name: Team
First_name: GLOBE
Middle_name: Task
End_Group
Group: Technical_Contact
Last_name: Hastings
First_name: David
Middle_name: A.
Email_address: INTERNET>Email: [email protected]
Phone: (303) 497-6729
Group: Address
Documentation Version 1.0
131
NOAA/NESDIS/NGDC (E/GC1)
325 Broadway
Boulder, CO 80303
USA
End_Group
End_Group
Group: Author
Last_name: Hastings
First_name: David
Middle_name: A.
Email_address: INTERNET>Email: [email protected]
Phone: (303) 497-6729
Group: Address
NOAA/NESDIS/NGDC (E/GC1)
325 Broadway
Boulder, CO 80303
USA
End_Group
End_Group
Group: Data_Center
Data_Center_Name: NOAA/NESDIS/National_Geophysical_Data_Center
Dataset_ID: Digital topographic model
Group: Data_Center_Contact
Last_name: Dunbar
First_name: Paula
Middle_name: K.
Email_address: INTERNET>Email: [email protected]
Phone: (303) 497-6084
Group: Address
NOAA/NESDIS/NGDC (E/GC1)
325 Broadway
Boulder, CO 80303
USA
End_Group
End_Group
End_Group
Originating_Center: NOAA/NESDIS/National_Geophysical_Data_Center
Campaign_or_Project:
Storage_Medium: Magnetic disk
Group: Coverage
Minimum_longitude: -180.0
Maximum_longitude: 180.0
Maximum_latitude: 90.0
Minimum_latitude: -90.0
End_Group
Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Landforms
Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Relief
Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Surface
Keyword: EARTH SCIENCE > LAND SURFACE > Topography > Terrain
Keyword: EARTH SCIENCE > OCEANS > Coastal Processes > Coastal Elevation
Keyword: INFOTERRA > Environmental monitoring > Environmental Measurements > Elevation
Global Land One-kilometer Base Elevation
132
Keyword: CIESIN > ENVIRONMENTAL PROTECTION > GEOGRAPHY AND LAND COVER >
TOPOGRAPHIC DATA
Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING > GEOGRAPHIC INFORMATION
SYSTEMS
Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING > MODELING
Keyword: CIESIN > ENVIRONMENTAL PROTECTION > MODELING > RESEARCH AND
DEVELOPMENT > MODELS
Keyword: DEM
Keyword: Digital elevation model
Keyword: Elevations
Keyword: Topography
Keyword: Location: Global
Revision_Date: 1998-02-01
Science_Review_Date: 1998-03-15
Future_Review_Date: 2000-03-15
Group: Reference
Originator: National Geophysical Data Center (editor)
Publication_Date: 1998
Title: GLOBE: Global Land One-km Base Elevation 30-sec. DEM
Edition: Version 1.0
Geospatial_Data_Presentation_Form: Model
Series_Information:
Series_Name: Key to Geophysical Records Documentation (KGRD) 34
Issue_Identification: Hastings, David A., and P. K. Dunbar. Global Land One-km Base Elevation
(GLOBE) Digital elevation model Documentation, National Oceanic and Atmospheric
Administration, National Geophysical Data Center, Publication KGRD 34, Boulder, Colorado,
1999.
Publication_Information:
Publication_Place: Boulder, CO
Publisher: National Geophysical Data Center
Online_Linkage: http://www.ngdc.noaa.gov/mgg/topo/globe.html
End_Group
Group: Quality
Attribute_Accuracy:
Attribute_Accuracy_Report: Some of the methods used to measure elevation do not actually
measure that of the ground surface. See Section 6 of GLOBE documentation.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: variable may range +/- 10 to +/- 250 meters or more
Attribute_Accuracy_Explanation: statistical and histogram analysis
Logical_Consistency_Report: GLOBE documentation discusses logical consistency implicitly in its
quality control and accuracy assessments. Adjacent data files have no gaps between
themselves. A few land areas of 30 arc-seconds in size may be missing. Most smaller areas are
missing. bathymetry is not included in GLOBE Version 1.0 (See NGDC’s TerrainBase or
ETOPO5 for lower-resolution bathymetric data. GLOBE Version 2.0 may include bathymetric
data.)
Completeness_Report: GLOBE has full global coverage of the land surface within the context of its
30-arc-second gridding. (Smaller features are usually not seen.)
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report: arc-seconds of latitude and longitude
Quantitative_Horizontal_Positional_Accuracy_Assessment:
AcrB558.pdf 4/1/2008 12:31:10 PM
Documentation Version 1.0
133
Horizontal_Positional_Accuracy_Value: 18.0
Horizontal_Positional_Accuracy_Explanation: Few elevation values should be more than about 18
arc-seconds from their implied location in the 30 arc-second grid. Greenland and Antarctica
may have greater error.
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report: Vertical accuracy varies by source materials used in GLOBE.
Values may range from 10 meters to 250 meters (and in rare cases, to over 500 meters in
elevation).
Quantitative_Vertical_Positional_Accuracy_Assessment:
Vertical_Positional_Accuracy_Value:
Vertical_Positional_Accuracy_Explanation: Methods of assessing vertical accuracy include
statistical analyses of high-resolution DEM sources by their producers, assessments of
contour intervals in some source maps, histogram analyses of DEMs lacking more detailed
assessments. (Histograms often show “spikes” suggesting contour intervals of source
maps.)
End_Group
Group: Summary
Provide Topographic Data for Scientific, Technical, and other Applications.
GLOBE is a project to develop the best available 30-arc-second (nominally 1 kilometer) global
digital elevation data set. This Version 1.0 of GLOBE contains data from 11 sources, and 18 combi-
nations of source and lineage. It continues much in the tradition of the National Geophysical Data
Center’s TerrainBase (DIF 1090), as TerrainBase served as a generally lower-resolution prototype
of GLOBE data management and compilation techniques.
The GLOBE mosaic has been compiled onto CD-ROMs for the international user community. It is
also available from the World Wide Web and via anonymous FTP. Improvements to the global
model are anticipated, as appropriate data and/or methods are made available. In addition,
individual contributions to GLOBE (several areas have more than one candidate) should become
available at the same Web site.
GLOBE may be used for technology development, such as helping plan infrastructure for cellular
communications networks, other public works, satellite data processing, and environmental
monitoring and analysis. GLOBE prototypes (and probably GLOBE itself after its release) has been
used to help develop terrain avoidance systems for aircraft. In all cases, GLOBE data should be
treated as any potentially useful but guaranteed imperfect data set. Mission- or life-critical
applications should consider the documented artifacts, as well as likely undocumented
imperfections, in the data.
End_Group
Global Land One-kilometer Base Elevation
134
A
accuracy
15, 57, 67–73, 75, 80, 81, 83–85, 92,
96, 97, 128, 129, 133
acknowledgments 108, 111
acronyms 112
Africa
13, 16, 17, 19, 20, 23, 30, 35, 49, 50,
51, 57, 67, 71, 102
Alaska 11
Altiplano 35, 51
Amazon 53
analysis, analyses
4, 12, 14, 19, 38, 42, 48, 50, 52, 58, 61,
72, 73, 102, 104, 106, 107, 111, 112,
115, 117, 132, 133
Anatolian 35
Andes 35
Antarctic
12, 50, 55, 57, 60, 63, 64, 66, 67, 70, 85,
106, 113, 121, 127
Antarctic Digital Database (ADD)
12, 34, 49, 55, 57, 63, 67, 85, 106, 112,
121, 127
ANUDEM 16, 49, 50, 112, 127
application
1, 2, 18, 37, 66–68, 73, 99, 100, 115,
133
arc-minute 1
arc-second
1, 4, 5, 10, 11, 14–18, 37, 41, 42, 50,
60, 66–68, 71, 72, 102, 103, 105, 106,
114, 117, 118, 125, 126, 132, 133
Arc/INFO
38, 81, 85, 88–90, 95, 96, 97
ArcView
81, 85, 88–90, 96, 97, 103
Argentina 67
Armenia 34
Army Map Service (AMS)
12, 13, 19, 32, 39, 40, 44, 45, 48–52,
58, 60, 63, 85, 102, 111, 112, 117, 120,
127, 133
artifacts
14, 15, 19, 49, 58, 59, 62, 66, 68, 77,
115, 133
Asia
13, 17, 20, 23, 30, 32, 34, 35, 51, 52, 57,
63, 67, 73, 85, 103, 106
aspect 15, 58, 76, 77
Australia
4, 6, 7, 12, 25, 37–40, 49, 57, 59, 63,
67, 73, 74, 84, 100, 102, 108, 111,
112, 118, 123, 125, 127, 128
Australian National University 49, 112, 127
Australian Surveying and Land Information
Group (AUSLIG) 4, 6, 7, 9, 12, 25,
37–40, 58, 59, 63, 65, 67, 70, 72, 74,
83, 84, 100, 101, 102, 105, 108, 111,
112, 118, 123, 125, 128
Azienda Generale Italiana Petroli (AGIP)
42, 112
B
bathymetric, bathymetry
2, 76, 78, 80, 112, 117, 132
Belgium 18
big-endian 84, 90
blended data, blend zones
17, 23, 29, 35, 37, 47, 57, 59, 63, 84,
85, 125, 127, 128
Borneo 57
Brazil 12, 32, 53, 62, 73, 85, 104, 120
breakline data, breakline method
16, 17, 23, 37, 84
BSTATS 95
C
California Institute of Technology (CALTECH)
1, 15, 102, 104, 109, 112, 113
Canada 49
Caribbean 57
cartographic
11, 14, 15, 34, 36, 39, 42, 44, 45, 48,
49, 52, 53, 56, 58, 61, 63, 69–72, 109,
111, 127
Index
Documentation Version 1.0
135
Caspian 34
caveats 2, 9, 10, 77, 99
cell-centered registration
16, 17, 36, 39, 41, 44, 45, 50, 52, 54, 55
Central America 57
Chile 35
China 34
citation of GLOBE 8
Clark University 92
coast, coastline
10, 37, 43, 46–50, 52, 54, 55, 57,
59–61, 63, 116, 131
color palette files 86–92, 94–96
Committee on Earth Observation Satellites
(CEOS) 5, 7, 108, 110, 112, 122
contours
5, 14, 34–44, 46–56, 58, 59, 62,
64, 67–70, 72, 73, 112, 117, 127, 133
contour-to-grid
5, 42, 49, 50, 52–55, 59, 62, 65, 127
copyright
1, 3, 4, 6, 7, 9, 12, 59, 84, 100, 101, 116
coverage of data
2, 4–6, 10–12, 16, 36, 38, 46, 48–51,
54, 57–68, 70, 71, 73, 100, 102, 111,
117, 131, 132
Cyprus 36
D
datum
3, 7, 14, 42, 63, 69, 71, 74, 75, 98, 126,
128
De Montfort University 74
Dead Sea 19
Defense Mapping Agency (DMA)
3, 6, 7, 11, 13, 15, 16, 24, 36, 48,
49, 52, 60–63, 70, 71, 73, 76, 85, 99,
100, 102, 103, 111, 112, 120, 125
Denmark 18
Department of Defense (DOD)
4, 18, 48, 64, 78, 99, 110, 112
Deutsches Zentrum für Luft- und Raumfahrt
(DLR) 5, 6, 108, 112
Deutsches Fernerkundungsdatenzentrum (DFD)
5, 108, 112
Digital Chart of the World (DCW)
5, 6, 12, 25, 30, 31, 34, 39, 40, 46–51, 57,
59–65, 67, 70–76, 85, 106, 112, 120, 127
digital elevation model (DEM)
1–12, 14–17, 19–37, 39–42, 44–70,
72–79, 83–85, 90, 92, 94–97, 100,
102–106, 111–114, 116–119, 122–128,
130, 132, 133
Digital Terrain Elevation Data (DTED)
1, 3, 8, 12, 13, 18–24, 34, 35, 46,
47, 49–51, 57, 59, 64, 65, 67, 68, 70, 73,
102, 103, 105, 112, 114, 117, 118,
128
DTED Level 0 3, 6, 11–13, 16, 18,
36, 37, 43, 58–61, 65, 69, 71, 74,
75, 84, 99, 111
DTED Level 1 14, 15, 17, 18, 36,
59, 61, 65, 69, 71, 74, 111, 125
disclaimers 9, 10, 99–101, 129
discrete data
15, 16, 18–21, 34–36, 43, 50, 51,
58, 60, 61, 63, 64, 69, 74, 75, 84
drainage 2, 49, 50, 52, 67, 102
E
Earth Observing System (EOS)
5, 65, 104, 112
Earth Resources Data Analysis System (ERDAS)
90, 94, 95, 112
ecosystems 8, 105
ELEVBATHY 111
Environmental Protection Agency (EPA)
105, 112
Environmental Science Research Institute (ESRI)
81, 82, 89, 95, 96, 103, 104, 112
EROS Data Center
6, 39, 106, 111, 112, 126, 127
Earth Resources Satellite (ERS-1)
46, 74, 102, 104
ETOPO5
1, 5, 62, 64, 76, 78, 111, 112, 117, 132
Eurasia 13, 17, 22, 35, 57
Europe 19, 20, 23, 30, 50, 51, 71
F
Federal Communications Commission 1
Federal Geographic Data Committee (FGDC)
85, 112, 114
file extensions 81, 87, 89, 129
file naming conventions 80–89
Global Land One-kilometer Base Elevation
136
FIXHEAD 95
France 18, 35, 36
File Transfer Protocol (FTP)
78, 79, 115, 133
G
Generic Mapping Tool (GMT) 38, 111, 112
geographic information system (GIS)
4, 5, 15, 16, 36, 39, 41, 44, 45, 47, 50,
52–56, 98, 104, 107–113, 125, 128
Geographical Survey Institute of Japan (GSI)
6, 7, 26, 41, 44, 52–54, 58, 61, 63, 65,
67, 74, 84, 85, 103, 109, 112, 118, 127
georeferencing
12, 16, 17, 36, 39, 41, 44, 45, 47,
50, 52–54, 56, 64, 95, 96, 98
georegistration 12, 36
GEOSAT 45, 46, 64, 69, 105, 107
GeoVu 81, 82, 84, 85–87, 90, 91
Germany 5, 18, 108, 112
Global Change Master Directory 114, 130
Global Positioning System (GPS) 75
Gruppo Nazionale di Geofisica della Terra Solida
(GNGTS) 43, 112
Goddard Space Flight Center (GSFC) 45, 112
GRASS
4, 38, 39, 62, 81, 82, 85, 88, 90, 92–94,
98, 111, 112, 125, 128
Greece 36
Greenland
12, 29, 45–47, 50, 58–60, 63, 65, 69,
71, 73, 74, 85, 105, 119, 124, 126–128
Greenland Ice Sheet 45, 47, 65, 105
GTOPO30
1, 6, 11, 13, 16, 35–37, 44, 47, 48, 52–65,
69, 70, 74, 75, 84, 100, 106, 111, 113,
123, 125, 127, 128
GZIP 79, 80, 81, 83, 89, 94, 113, 129
H
headers, header file
71, 81, 82, 84–91, 94–96, 98
histograms
11, 19–35, 39, 40, 42, 44, 45, 47,
50, 51, 54, 56, 58, 63, 68,
72, 73, 111, 117, 132, 133
history of GLOBE 5
hypsography, hyspographic
5, 47, 50, 57, 67, 68, 71, 104, 106, 127
I
Iceland 36
Idrisi 81, 82, 85, 87, 92, 98
IMAGEGRID 95, 96
importing GLOBE data 89–98
Indonesia 62
Instituto Brasiliero de Geografia e Estatistica
(IBGE) 53, 85, 104, 113, 120
International Council of Scientific Unions (ICSU)
110, 113
International Geosphere-Biosphere Programme
(IGBP) 5, 7, 110, 113
International Map of the World (IMW)
49, 51–53, 85, 102, 103, 106, 113, 120,
121, 127
International Society of Photogrammetry and
Remote Sensing (ISPRS) 7, 110, 113
interpolation
38–40, 43, 46, 50, 67, 68, 70, 72, 103,
104, 125
Israel 36
Italy
12, 18, 27, 42–44, 58, 61, 63–65, 67, 71,
84, 102, 106, 113, 118, 119, 124, 126, 128
Italian Alps 44
J
Japan
6, 7, 12, 26, 41, 42, 44, 52–54, 58, 61,
63, 67, 71, 73–75, 84, 103, 112, 118,
127, 128
Jeppesen 74
Jet Propulsion Laboratory (JPL)
1, 2, 7, 15, 29, 46–49, 57, 59, 60, 64, 65,
71, 74, 85, 102, 104, 105, 109, 111,
113, 124, 127, 128
L
Lake Biwa 42
Lake Hovsgol 35
Lake Titicaca 35
Lake Tuzand 35
Lake Van 36
Documentation Version 1.0
137
latitude
1, 4, 5, 7, 10, 14, 15, 17, 19, 34–36,
41, 43, 45–47, 50, 51, 61, 65–67,
75, 80, 82, 83, 93–95, 97, 98, 117,
126–128, 131, 132
license (data for Australia)
6, 12, 37, 40, 59, 84, 100, 101
lineage
1, 8–13, 16, 17, 35–37, 41, 42, 44, 46,
48, 52–57, 60, 61, 69, 70, 76, 77, 81, 83,
84, 92, 94, 100, 114, 117, 133
little-endian 84
longitude
1, 4, 5, 7, 10, 14, 15, 17, 19, 34, 35,
41, 45, 50, 51, 66, 80, 82, 83, 93, 95,
97, 98, 117, 126–128, 131, 132
M
Manaaki Whenua Landcare Research, Ltd. (LCR)
28, 44, 61, 85, 104, 113, 119
mean
7, 10, 15, 16, 18, 36, 39, 42, 43, 49,
58, 60, 70, 72, 74, 100–102, 128
median 17, 22, 23, 35, 37, 70, 84
metadata 55, 81, 85, 114, 130
Mexico 104, 107
Ministerio della Publica Instruziane (MPI)
43, 54, 85, 104, 113, 121
Mongolia 35
Multiangle Imaging SpectroRadiometer (MISR)
46, 58, 65, 69, 70, 74, 102, 111, 113
N
National Aeronautics and Space Administration
(NASA) 1, 4, 5, 65, 109, 111–113
National Environmental Satellite, Data, and
Information Service (NESDIS)
113, 116, 125, 126, 128–131
National Geophysical Data Center (NGDC)
1–3, 5, 6, 8, 11, 13, 15, 16, 24, 25, 27,
36–40, 42, 43, 47, 57–64, 70, 74, 75, 78,
79, 83–85, 90, 100, 102, 103, 105, 111,
113–117, 122, 123, 125, 126, 128–132
National Imagery and Mapping Agency (NIMA)
3, 6, 7, 11–15, 17–19, 35, 36, 43,
47, 48, 51, 57–61, 63, 70, 71, 76, 84,
99, 100, 110–113, 117, 120, 125
National Oceanic and Atmospheric Administration
(NOAA) 1, 3, 6, 8, 12, 46, 74, 76, 79,
100, 103, 105, 106, 110, 113, 115, 116,
121–123, 125, 126, 128–131
National Snow and Ice Data Center (NSIDC)
29, 45–48, 58–60, 63, 71, 85, 105, 107,
113, 124, 126–128
nearest-neighbor
16, 17, 22, 35–37, 41, 44, 45, 60, 61,
69, 70, 84
Netherlands 18
New Zealand
12, 28, 44, 45, 58, 61, 67, 71, 73,
85, 89, 104, 119, 124–126
North America 21, 24, 31, 34, 36, 51, 57
Norway 18
O
Operational Navigation Chart (ONC)
40, 46, 48, 49, 51, 62, 75, 113
P
palette files 81, 82, 86–92, 94–97
Peru 12, 33, 49, 54, 73, 85, 104, 121, 127
Photoshop 97
proprietary data 7, 37, 43
prototype
4–7, 12, 13, 15, 16, 18, 64, 114, 115, 133
Q
Qinghai 34
quasi-maximum 2
quasi-minimum 2
R
raster
4, 10, 13, 15, 48–50, 57, 68–71, 76, 81,
82, 95, 98, 112, 128
resampled, resampling
16, 17, 35, 36, 45, 58, 60–62, 69, 76,
84, 125, 126
review of GLOBE
1–8, 36, 58–61, 64, 74, 75
root-mean-square error (RMSE)
41, 70–74, 113
Global Land One-kilometer Base Elevation
138
S
Scientific Committee on Antarctic Research
(SCAR) 55, 58, 60, 63, 64, 70, 73,
85, 106, 112, 113, 121
SEASAT 45, 46, 105, 107
Servizio Geologico Nazionale (SGN)
27, 42–44, 58, 59, 61, 63, 65, 67, 84,
106, 113, 118, 126
Shuttle Radar Topography Mapper (SRTM)
4, 65, 113
slope 14, 18, 43, 58, 67, 68, 72, 76, 77
source/lineage map
9, 17, 37, 48, 57, 76, 84, 85
(See also back cover of publication.)
South America
21, 31, 32, 35, 49, 51, 52, 54, 57, 62,
67, 85, 102, 106
South Korea 36
Spain 18
Spatial Data Transfer Standard (SDTS) 80, 113
spikes (in histograms)
19, 34–36, 39, 40, 42, 44, 45, 51, 52,
54, 56, 58, 117, 133
statistics, statistical information
42, 46, 70, 74, 82, 83, 85, 95, 102, 104,
117, 132, 133
Sulawesi 57
T
Taiwan 106
TerrainBase
1, 4–8, 42, 62, 64, 76, 78, 105, 111,
114, 117, 132, 133
tiles, tiling
43, 57, 64, 68, 71, 76, 78, 80, 82–85,
87, 92, 94–97
Tokyo Bay 41
Turkey 23, 35, 36
U
U.S. Army Topographic Command (USATC)
13, 51, 106, 113
U.S. Geological Survey (USGS)
1, 5, 6, 11–13, 16, 17, 24, 36, 37, 39,
40, 44–50, 52, 54–65, 71–74, 76, 84, 85,
100, 103–106, 110, 111, 113, 123,
125–128
United States
1, 3, 8, 11, 16, 57, 60, 63, 99, 100,
103, 116, 125–131
United Kingdom 18, 36, 74, 106
United Nations 53, 106, 113
University College London (UCL)
5, 6, 39, 45, 47, 59, 61, 74, 109,
113, 119, 127
University of Lecce 43
updates to GLOBE
3, 6, 7, 11, 55, 64, 78, 79, 115
V
vector
10, 39, 48–50, 52, 55–59, 68,
70, 71, 76, 85
vector-to-raster 49, 56, 68
W
Working Group on Data (WGD) 5, 7, 113
Working Group on Information Systems and
Services (WGISS) 5, 108, 110, 113
World Geodetic System (WGS)
7, 10, 15, 41, 49, 96, 98, 113
World Vector Shoreline (WVS)
10, 39, 47, 48, 57, 59, 113
Code Source/Lineage
1 DTED Level 0 discrete 30" DEM.
2 DTED-based 30" median DEM from USGS/GTOPO30.
3 DTED-based nearest-neighbor (to center of 30" GLOBE grid cell) DEM from USGS/GTOPO30.
4 DTED resampled to 30" by NIMA, provided to NGDC for public distribution in the 1980s.
5 DTED provided to USGS in the 1970s, regridded to 30" by nearest-neighbor techniques by USGS.
6 DTED-based 30" “breakline” DEM from USGS/GTOPO30.
7 DTED-based DEM. Linear blending between classes 2 and 6 at their suture.
8 DEM for Australia; copyright 1998 by AUSLIG, licensed to NGDC for distribution with GLOBE.
9 DEM of Japan, from GSI.
10 DEM for Italy at high resolution from SGN, converted to 30" gridding by NGDC (for SGN).
11 DEM of New Zealand at 500m gridding by LCR, reprojected to 30" by USGS.
12 DEM of Greenland at 90" by Zwally (and others)/NSIDC, converted to 30" by JPL.
13 Zwally (and others)/NSIDC/JPL and DCW DEM. Linear blending between classes 12 & 14 at their suture.
14 Digital Chart of the World developed by DMA, converted to 30" grid by USGS.
15 Maps for parts of southeast Asia and South America by AMS, digitized by GSI, gridded by USGS.
16 Maps for part of Brazil by the FBGE, adapted by GSI, gridded by USGS.
17 Map for part of Peru by the Ministerio de Guerra of Peru, adapted by GSI, gridded by USGS.
18 SCAR Antarctic Digital Database, converted by USGS, repaired by NGDC.
Global Land One-kilometer Base Elevation
Documentation Version 1.0
NOAA/NGDC, 1999
