GTOPO30 DocumentationTable of Contents:
GTOPO30 is a global digital elevation model (DEM) resulting from a
collaborative effort led by the staff at the U.S. Geological Survey's
EROS Data Center in Sioux Falls, South Dakota. Elevations in GTOPO30 are
regularly spaced at 30-arc seconds (approximately 1 kilometer). GTOPO30
was developed to meet the needs of the geospatial data user community for
regional and continental scale topographic data. This release represents
the completion of global coverage of 30-arc second elevation data that
have been available from the EROS Data Center beginning in 1993. Several
areas have been updated and the entire global data set has been repackaged,
so these data supersede the previously released continental data sets.
Comments from users of GTOPO30 are welcomed and encouraged. Please send
your comments to Dean Gesch at email@example.com or to Sue Greenlee
The 27 tiles that individually cover 50 degrees of latitude and 40 degrees of longitude each have 6,000 rows and 4,800 columns. The 6 Antarctica tiles that individually cover 30 degrees of latitude and 60 degrees of longitude each have 3,600 rows and 7,200 columns. There is no overlap among the tiles so the global data set may be assembled by simply abutting the adjacent tiles.
The tile named ANTARCPS includes the same data as the 6 geographic tiles covering Antarctica, but is presented in a polar stereographic projection. The horizontal grid spacing is 1,000 meters, and the tile has 5,400 rows and 5,400 columns. The projection parameters used for the polar stereographic projection are: 0 degrees for the longitude of the central meridian, 71 degrees south for the latitude of true scale, and 0 for the false easting and false northing.
Data for each tile are provided in a set of 8 files. The files are named with the tile name and a file name extension indicating the contents of the file. The following extensions are used:
The simple format should allow for easy ingest into most popular image
processing and geographic information systems packages. Further information
on the contents of the files is provided below.
The DEM is provided as 16-bit signed integer data in a simple binary raster.
There are no header or trailer bytes imbedded 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.).
The DEM header file is an ASCII text file containing size and coordinate
information for the DEM. The following keywords are used in the header file:
3.3 World File (.DMW)
The world file is an ASCII text file containing coordinate information. It
is used by some packages for georeferencing of image data. The following is
an example world file (W100N40.DMW) with a description of each record:
3.4 Statistics File (.STX)
The statistics file is an ASCII text file which lists the band number,
minimum value, maximum value, mean value, and standard deviation of the
values in the DEM data file.
3.6 Shaded Relief Image (.GIF)
A shaded relief image is provided as an overview of the data in each tile.
The images were derived from a generalized version of GTOPO30 with a
horizontal grid spacing of 240-arc seconds (approximately 8 kilometers), so
many small islands and features will not be visible. The images are meant
to provide a convenient way for users to view the general topographic
features portrayed in each tile. The shaded relief images are provided as
GIF images which can be displayed by many popular image display programs and
World Wide Web browsers. An image size of 750 rows by 600 columns is used
for the tiles covering 50 degrees of latitude by 40 degrees of longitude.
An image size of 450 rows by 900 columns is used for the Antarctica tiles
which cover 30 degrees of latitude by 60 degrees of longitude each. The
Antarctica polar stereographic tile is portrayed by a shaded relief image
having 675 rows by 675 columns.
The source map is a simple 8-bit binary image which has values that indicate the source used to derive the elevation for every cell in the DEM. The source 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:
3.8 Source Map Header File (.SCH)
The source map header file is an ASCII text file containing size and coordinate information, similar to the DEM header file. The following keywords are used in the source map header file:
4.0 Data Distribution
Data for each GTOPO30 tile are distributed electronically as a compressed tar
file. The 8 files for each tile have been combined into one file with the
Unix "tar" command, and the tar file has been compressed with GNU "gzip"
utility. To use the GTOPO30 data files, the tar file must first be
decompressed and then the individual data files extracted from the tar file.
For example, the following Unix command could be used:
Macintosh gzip and tar:
DOS gzip and tar:
4.1 Procedures for Obtaining Data
GTOPO30 is available electronically through an Internet anonymous File Transfer Protocol (FTP) account at the EROS Data Center (at no cost).
To access this account:
Click here to place an order for the data on CD-ROM or 8 mm high density tar tape.
For assistance and information contact:
LP DAAC User Services
EROS Data Center
Sioux Falls, SD 57198 USA
Tel: 605-594-6116 (7:30 am to 4:00 pm CT)
Fax: 605-594-6963 (24 hours)
Internet: firstname.lastname@example.org (24 hours)
Data distributed on CD-ROM and 8 mm tape are provided as sets of files for
each tile as described above in section 3.0 (Data Format). They are not
combined into one tar file or compressed as they are for electronic
After decompression and extraction from the tar files, the following file
sizes are present for each of the 3 sizes of tiles:
For each tile, the total for all the other file types (HDR, DMW, STX, PRJ, GIF, and SCH) is well under 1 megabyte.
The global 16-bit DEM (21,600 rows by 43,200 columns) has a size of 1.74 gigabytes. The global 8-bit source map of the same dimensions has a size of 889.9 megabytes.
Through the use of the gzip compression utility the total size of the global data set is reduced about 90% from almost 2.72 gigabytes to under 290 megabytes. The list below shows the compressed size for each tile. The sizes range from less than 1 megabyte to about 25 megabytes, with the average at about 8 megabytes. Decompressed, the tar file for each tile can be as large as 84 megabytes.
5.0 Notes and Hints for GTOPO30 Users
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 Motorola byte order, which stores the most significant byte first ("big endian"). Systems such as Sun SPARC and Silicon Graphics workstations use the Motorola byte order. The Intel byte order, which stores the least significant byte first ("little endian"), is used on DEC Alpha systems and most PCs. Users with systems that address bytes in the Intel byte order may have to "swap bytes" of the DEM data unless their application software performs the conversion during ingest. The statistics file (.STX) provided for each tile gives the range of values in the DEM file, so users can check if they have the correct DEM values stored on their system.
Users of ARC/INFO or ArcView can display the DEM data directly after simply
renaming the file extension from .DEM to .BIL. However, if a user needs
access to the actual elevation values for analysis in ARC/INFO the DEM must
be converted to an ARC/INFO grid with the command IMAGEGRID. IMAGEGRID does
not support conversion of signed image data, therefore the negative 16-bit
DEM values will not be interpreted correctly. After running IMAGEGRID, an
easy fix can be accomplished using the following formula in Grid:
The converted grid will then have the negative values properly represented,
and the statistics of the grid should match those listed in the .STX file.
If desired, the -9999 ocean mask values in the grid could then be set to
NODATA with the SETNULL function.
GTOPO30, completed in late 1996, was developed over a 3 year period through
a collaborative effort led by staff at the U.S. Geological Survey's EROS Data
Center (EDC). The following organizations participated by contributing
funding or source data: the National Aeronautics and Space Administration
(NASA), the United Nations Environment Programme/Global Resource Information
Database (UNEP/GRID), the U.S. Agency for International Development (USAID),
the Instituto Nacional de Estadistica Geografica e Informatica (INEGI) of
Mexico, the Geographical Survey Institute (GSI) of Japan, Manaaki Whenua
Landcare Research of New Zealand, and the Scientific Committee on Antarctic
GTOPO30 is based on data derived from 8 sources of elevation information, including vector and raster data sets. The following table lists the percentage of the global land surface area derived from each source (a full description of each source is provided below):
6.1.1 Digital Terrain Elevation Data
DTED was used as the source for most of Eurasia and large parts of Africa, South America, Mexico, Canada, and Central America. DTED coverage for Mexico was provided by INEGI.
6.1.2 Digital Chart of the World
Digital Chart of the World (DCW) is a vector cartographic data set based on the 1:1,000,000-scale Operational Navigation Chart (ONC) series, which is the largest scale base map source with global coverage (Danko, 1992).
The topographic information of interest for generating DEM's is contained in
several DCW hypsography layers. The primary contour interval on the source
ONC's is 1,000 feet (305 meters), and supplemental contours at an interval of
250 feet (76 meters) are shown in areas below 1,000 feet in elevation. In
limited areas of higher elevation there supplemental contours at 500-foot
(152-meter) intervals. The DCW drainage layers were also used as input to
the DEM generation process; this information included stream networks, lake
shorelines, lake elevations, and ocean coastlines. The DCW was used as the
primary source for filling gaps in the DTED coverage, including all of
Australia, most of Greenland, and large areas of Africa, South America, and
Paper maps at a scale of 1:1,000,000 produced by the Army Map Service (AMS),
a predecessor of DMA and NIMA, were acquired and digitized by GSI 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 EDC as digital vector
cartographic data sets.
Paper maps from the 1:1,000,000-scale International Map of the World (IMW)
series were digitized by GSI to provide source data for the Amazon basin.
The International Map of the World includes national maps produced to a
United Nations specified standard for 1:1,000,000-scale mapping. The maps
used for this project had a 100-meter contour interval.
Small areas of a 1:1,000,000-scale map from the Peruvian government were
digitized to fill gaps in source data for South America. The map had a
contour interval of 1,000 meters.
Manaaki Whenua Landcare Research contributed a DEM with a 500-meter
horizontal grid spacing for New Zealand. The DEM was derived from elevation
information on 1:63,360-scale maps with a 100-foot (30-meter) contour
The Antarctic Digital Database (ADD) was produced under the auspices of the
Scientific Committee on Antarctic Research. Digital contours and coastlines
from the ADD were used as source material for Antarctica. The 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 the ADD vary widely,
with the more detailed data near the coastline and very generalized data in
the interior of the continent. Detailed metadata provided in the ADD
identifies the map scale from which each contour line was extracted.
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,
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.
Processing of the raster source data, including DTED, USGS DEM's, and the New
Zealand DEM, involved generalizing the higher resolution data to the 30-arc
second horizontal grid spacing. Because the DTED and USGS DEM's were already
in a geographic "projection" they only required a sampling of the full
resolution 3-arc second data. One representative elevation value was selected
to represent the area covered by 100 full resolution cells (a 10 by 10
matrix). As the project progressed, several methods of generalization were
used. Selection of the representative 30-arc second value was accomplished
by systematic subsampling for North and South America, by calculation of the
median value for Eurasia, and by the breakline emphasis approach (Gesch and
Larson, 1996) for Africa. The 500-meter New Zealand DEM was generalized to
30-arc seconds by reprojecting it from the New Zealand National Grid
projection to geographic coordinates using bilinear resampling.
The topographic information from the vector cartographic sources, including the DCW, the ADD, 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 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 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).
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.
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 global product was assembled from the continental and regional DEM's.
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.
The absolute vertical accuracy of GTOPO30 varies by location according to the source data. Generally, the areas derived from the raster source data have higher accuracy than those derived from the vector source data. The full resolution 3-arc second DTED and USGS DEM's have a vertical accuracy of + or - 30 meters linear error at the 90 percent confidence level (Defense Mapping Agency, 1986; U.S. Geological Survey, 1993). 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 those assumptions, vertical accuracy expressed as + or - 30 meters linear error at 90 percent can also be described as a RMSE of 18 meters. The areas of GTOPO30 derived from DTED and USGS DEM's retain that same level of accuracy because through generalization a representative elevation value derived from the full resolution cells is chosen to represent the area of the reduced resolution cell (although the area on the ground represented by that one elevation value is now much larger than the area covered by one full resolution cell).
The absolute vertical accuracy of the DCW, the vector source with the largest area of coverage, is stated in its product specification as + or - 650 meters linear error at the 90% confidence level (Defense Mapping Agency, 1990). Experience 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 the areas of GTOPO30 derived from DCW vector hypsography, the DCW grid was compared to 30-arc second DTED, which had been aggregated by averaging. 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. Eliminated from the comparison were those areas of the DCW grid for which supplemental DTED point control had been included in the gridding process. 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 above, a RMSE of 97 meters can be expressed as + or - 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.
The accuracy of the areas of GTOPO30 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 + or - one-half 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. The table below lists the estimated absolute vertical accuracy for the areas of GTOPO30 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).
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
As with all digital geospatial data sets, users of GTOPO30 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 GTOPO30 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.
For any application, the horizontal grid spacing (which limits the resolution) and the vertical accuracy of GTOPO30 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.
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.
Users should maintain the distinction between grid spacing and resolution.
Even though the global data set has a consistent 30-arc second grid spacing,
not all topographic features that one would expect to be resolved at that
spacing will be represented. 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.
Certainly, a 30-arc second grid spacing is appropriate for the areas derived
from higher resolution DEM's (DTED, USGS DEM's, 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 and Greenland
contain larger such areas. Also, the quality of the contours from the ADD
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.
Differences in topographic detail among the sources are evident in GTOPO30. 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 very noticeable. 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 instance, approximately
30% of the DTED 1-degree by 1-degree tiles (the production and distribution
unit for full resolution DTED) have an absolute vertical accuracy worse than
the product specification of + or - 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.
Artifacts due to the production method are apparent in some areas of GTOPO30. While the magnitude of the artifacts in a local area are usually well within the estimated accuracy for the source, users are nonetheless made aware because the effects are plainly visible and they may affect some applications of the DEM. Some areas derived from DTED, especially in Africa and the Mideast, exhibit a striping artifact, most likely due to the production method of the DTED. 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 reflection of the 1-degree tiling structure of the full resolution DTED. These areas derived from contiguous DTED 1-degree tiles appear blocky because of vertical offsets among the tiles in the original full resolution DTED. The artifacts in the DTED areas may or may not be visible, depending on the method used to display the data. For instance, when viewing the DEM data as an image either in shades of gray or color, the artifacts may be 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 small 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 were sparse. Additionally,
a "stair step" (or terracing) effect may be seen in profiles of some areas,
where 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. When a
histogram of elevations is presented there are sharp peaks at elevations
that are multiples of the contour interval of the source. This effect is
common in DEM's 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, but some level of these conditions inevitably remain
due to the nature of vector-to-raster surface generation.
GTOPO30 provides a new level of detail in global topographic data.
Previously, the best available global DEM was the ETOPO5 data set, and its
successor TerrainBase, with a horizontal grid spacing of 5-arc minutes
(approximately 10 kilometers) (Row, Hastings, and Dunbar, 1995). GTOPO30
data are suitable for many regional and continental applications, such as
climate modeling, continental-scale land cover mapping, extraction of
drainage features for hydrologic modeling (Danielson, 1996; Verdin and
Greenlee, 1996), and geometric and atmospheric correction of medium and coarse
resolution satellite image data (Gesch, 1994; Jet Propulsion Laboratory,
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and does not imply endorsement by the U.S. Government.