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Antarctic 5-km Digital Elevation Model from ERS-1 Altimetry

Summary

This data set provides a digital elevation model (DEM) for Antarctica to 81.5°S, at a resolution of 5 km. Approximately 20,000,000 data points were used to generate this data set. Data points were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995. The improved density in coverage and resolution, compared with past satellite altimetry missions, provides better detection of topographic detail such as surface undulations, ice streams, grounding zones, and interstream ridges. DEM data are in a polar stereographic projection with the origin at the South Pole, and are referenced to the OSU91A geoid.

The ERS-1 satellite radar altimeter measurements are highly useful for determining precise ice sheet elevations in Antarctica. The orthometric heights derived from the ERS-1 data contribute to a more accurate and complete mapping of the Antarctic Ice Sheets than previously possible, and therefore to ongoing studies of ice mass balance studies in Antarctica.

The DEM is provided as a single ASCII text file, accessible by FTP. Data access is unrestricted, but we recommend that users register with us. Registered users automatically receive e-mail notification of product updates and changes to processing.

Citation

We kindly request that you cite the use of this data set in a publication using the following citation example. For more information, see our Use and Copyright Web page.

If these data are used in a publication, they should be cited using the following reference:

Bamber, J.L. and R.A. Bindschadler. 1997. An improved elevation dataset for climate and ice-sheet modelling: validation with satellite imagery. Annals of Glaciology 25:438-444.

Also, to help us serve the scientific and cryospheric research communities, please acknowledge NSIDC:

Data provided by the National Snow and Ice Data Center DAAC, University of Colorado, Boulder, CO.

Table of Contents

1 Data Set Overview
2 Applications
3 Theory of Measurements
4 Acquisition Materials and Methods
5 Preparation and Description
6 Notes and Plans
7 Products and Access
8 References
9 Acronyms and Abbreviations
10 Document Information

1. Data Set Overview

Data Set Identification

Antarctic 5-km Digital Elevation Model from ERS-1 Altimetry

Data Set Introduction

This digital elevation model (DEM) provides coverage of the Antarctic ice sheet to 81.5°S at 5 km resolution. Data were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995. DEM data are in a polar stereographic projection with the origin at the South Pole, and are referenced to the OSU91A geoid. Data are in space-delimited ASCII text format.

Objective/Purpose

Prior to the ERS-1 radar altimeter, researchers had very limited knowledge of the topography of Antarctica south of 72°S. The geodetic phase of ERS-1 provided coverage of the ice sheet to 81.5°S, with a higher density of data collection than previous satellite altimetry missions. When the DEM was gridded to 5 km resolution, it provided researchers with a more detailed observation of ice sheet flow characteristics and topography.

Summary of Parameters

The ERS-1 radar altimeter measures ice sheet elevation and backscatter over land ice.

Discussion

In March 1995, ERS-1 was operating along two repeat cycles of 168 days, which were offset so that they were equivalent to a single 336 day cycle. This provided 8.3 km across-track spacing at the equator, 4 km spacing at 60°S, and 2 km spacing at 70°S. The along-track spacing of each altimeter height measurement is 335 m (Bamber and Bindschadler 1997).

Detailed coverage of the Antarctic ice sheet by the ERS-1 radar altimeter, compared with past satellite altimetry missions, has improved the accuracy of the corresponding DEM by ensuring coverage of marginal regions, reducing spacing between adjacent sub-satellite tracks (thus reducing slope-induced error), and reducing random errors in individual altimeter height measurements.

A quantitative assessment of DEM accuracy is difficult to determine due to the lack of in situ validation data from the Antarctic ice sheet. However, vertical and horizontal accuracy are known to have improved from earlier Antarctic DEMs. To improve the accuracy of elevation estimates, various corrections were applied to the data including: a range-estimate refinement procedure (waveform tracking), slope correction, data filtering, and removal of anomalous orbits (Bamber and Bindschadler 1997).

Related Data Sets

Investigator(s)

Investigator(s) Name and Title

Jonathan L. Bamber Bristol Glaciology Centre School of Geographical Sciences University of Bristol University Road Bristol, BS8 1SS United Kingdom

Contact(s) Name, Address, Telephone, Fax, and e-mail

NSIDC User Services
National Snow and Ice Data Center
CIRES, 449 UCB
University of Colorado
Boulder, CO 80309-0449  USA
phone: +1 303.492.6199
fax: +1 303.492.2468
form: Contact NSIDC User Services
e-mail: nsidc@nsidc.org

2. Applications

Radar altimetry data is generally used for studies of ice sheet mass balance and ice dynamics (direction and magnitude of ice flow). The 5 km resolution DEM for the Antarctic ice sheet provides detection of subtle topographic features including: surface undulations, flow lines, ice streams, interstream ridges, and grounding zones.

3. Theory of Measurements

Satellite radar altimeters measure the time it takes an electromagnetic signal to travel from the altimeter antenna to the ice sheet surface and back to the altimeter's receiver. This "range measurement" allows investigators to determine the satellite's height above the ice sheet. NSIDC's Radar Altimeter document describes the instrument and how it works.

Corrections are applied to the range measurements to account for the fact that returns are different over ice than over the ocean. The correction for interpreting the data over ice is called "retracking," and is described in papers by Davis and Zwally (1993), and Zwally, et al. (1983).

Over sloping terrain, the radar altimeter measurement needs to be corrected because the return comes from a point not directly below the satellite, but to the uphill side. The elevation indicated by the return time in this case is higher than that directly below the satellite. The data are slope-corrected to reduce the errors, using the slope correction algorithm from Brenner et al. (1983).

4. Acquisition Materials and Methods

Acquisition Equipment

Sensor/Instrument Description

Please see the radar altimeter description.

Source/Platform

For information about the ERS-1 spacecraft, its mission, its environment, and the ground data system, please refer to the Alaska Satellite Facility DAAC Web page and to the European Space Agency home page.

5. Preparation and Description

Data Description

Spatial Characteristics

Spatial Coverage

This data set contains surface elevations of the Antarctic ice sheet derived from ERS-1 from 65°S to 81.5°S. Antarctic Digital Database data filled the gap between 81.5°S to 90°S. Elevations in this region, along with areas of open ocean, are set to a fill value of 999.999.

Spatial Coverage Map

thumbnail

Spatial Resolution

The data are gridded with a cell size of 5 km.

Projection

Data are in a polar stereographic projection with geodetic latitude and longitude coordinates. The origin is at the South Pole. The projection is referenced to the WGS84 ellipsoid with an equatorial radius of 6378.137 km and an eccentricity of 0.081819190843. The standard parallel is 71°S.

Grid Characteristics

A Cartesian grid is centered on the South Pole, with grid dimensions of 1121 by 1121 pixels and a range of -2800 km to + 2800 km. The following table summarizes the locations of the centers of selected grid cells in the DEM:

Cell Column Row Line Latitude Longitude
Upper left 0 0 1255521 -54.6732 -44.999
Upper right 1120 0 1256641 -54.6726  45.000
Lower left 0 1120 1 -54.6738 -135.000
Lower right 1120 1120 1121 -54.6732  134.999
Center 560 560 628321 -89.9993  45.000

Temporal Characteristics

Temporal Coverage

Data were derived from ERS-1 radar altimetry during the geodetic phase from March 1994 to May 1995.

Temporal Resolution

Data were collected daily from the ERS-1 satellite for 336 days.

Data Characteristics

Parameter/Variable

Elevations are derived from orthometric heights referenced to the WGS84 ellipsoid.

Unit of Measurement

Elevation is represented in meters [m].

Data Source

ERS-1 Satellite Radar Altimetry

Data Range

Elevation data (the third field) range from 0.00525553 m to 5675.0 m.

Sample Data Record

Sample ASCII output from "bamber.5km97.dat":

Lat Lon Elev Difference
-81.3404 138.867 2375.68 -44.24
-81.3102 138.639 2387.87 -44.17
-81.2799 138.412 2396.72 -44.07
-81.2495 138.187 2403.71 -43.96

Columns represent latitude, longitude, and elevation with reference to the OSU91A geoid. The last column is the difference between the OSU91A geoid and the WGS84 ellipsoid. A value of "999.999" represents a grid cell where interpolation was not possible.

Latitude and longitude are expressed in decimal degrees to two decimal places. Negative longitude values represent the Western Hemisphere, and negative latitude values represent the Southern Hemisphere.

Data Organization

Data Granularity

A general description of data granularity as it applies to the Earth Observing System Data and Information System (EOSDIS) appears in the EOSDIS Glossary.

Data are contained within a single ASCII text file that is 39.6 MB.

Data Format

Data are in space-delimited ASCII text format, with 5 fields and 1,256,641 records. See Sample Data Record for more information about fields.

Data Manipulations

Formulae

Derivation Techniques and Algorithms

The following discussion applies to the interior Antarctic ice sheet to 81.5°S.

Waveform retracking
The purpose of a waveform retracking algorithm is to calculate the difference between a tracking point derived by the onboard software and a known, fixed position on the leading edge of a waveform signal. The point on a waveform that corresponds to the point on the surface closest to the satellite typically does not provide a useful representation of the surface height. However, determining elevation at any other location presents a problem because facets (faces of topographic features) with different elevations result in the interpretation of complex leading edges. Waveform analysis over variable terrain is a complicated procedure which requires prior knowledge of surface properties. Threshold and beta (ß) parameter retracking algorithms were used because they were considered the best methods for estimating the elevation at specific points (Bamber 1994).

Slope induced error correction
A "relocation" algorithm was used to locate the closest point to the satellite and calculate the correction necessary to determine the surface elevation at that point, using an estimate of the surface slope magnitude and direction. For each data point, the algorithm first extracts the appropriate slope correction values from a look-up table, and calculates the magnitude and direction of the slope based on the range to the satellite. The latitude and longitude of this point is then estimated. The algorithm also calculates an elevation correction to account for the measurement not being taken at the satellite's nadir. The revised surface elevation is calculated using the relocation method (Bamber 1994).

Data Processing Sequence

Processing Steps

To make these data more useful in comparative studies, or as a control for ice sheet data and to avoid the need for other Level 2 products, Bamber attempted to improve the accuracy of elevation estimates of variable topographic surfaces with minimal biases by using the following steps (Bamber 1994).

  1. A range-estimate refinement procedure (waveform tracking) was implemented using the offset center of gravity method for calculating the waveform amplitude, with a power threshold of 25 percent.

  2. Slope correction was applied using a variation of the relocation method (Bamber 1994).

  3. Data filtering techniques were implemented, including tests applied to the return-echo waveform shape, backscatter coefficient, and retracking correction value for each altimeter height estimate. Approximately 27 percent of the data were removed during this procedure.

  4. Anomalous orbits were removed, by comparing one track with another where they cross (cross-over analysis).

  5. Data were interpolated onto a 5 km grid, and a two-stage gridding procedure was employed with the following steps:

    • Production of a local distance-weighted means of x, y and z in the region of a grid point, producing a quasi-regular array of average height estimates.

    • A triangulation procedure to interpolate to the exact grid point locations and to extrapolate to grid points where no altimeter data were present (Bamber, Ekholm, and Krabill 1998).

Errors

The following discussion applies to the interior Antarctic ice sheet to 81.5°S.

Sources of Error

Errors in altimeter data can be introduced from several sources including geographically correlated orbit errors, errors in slope correction procedures, and non-uniform spatial sampling (Bamber, Ekholm, and Krabill 1998).

Quality Assessment

Data Validation by Source

Data were validated by a validation procedure that uses surface elevation and backscatter coefficient data collected from an area larger than the antenna footprint. A surface is fitted to these data and used as input into an altimeter waveform simulator program. The output is a range estimate, which is compared with the actual altimeter range measurement. Slope-induced error is not considered at this point because it could potentially mask all other variables. The program also calculates surface elevation, an estimate of the relocated latitude and longitude coordinates, and a slope magnitude and direction. These data can be used to assess how well the processing sequence, including the slope correction algorithm, is performing. The magnitude of the difference between the two data sets depends primarily on how large the slope values are, and how accurately they are known. Limited in situ data sets were available for validating the surface DEM (Bamber, Ekholm, and Krabill 1998).

Measurement Error for Parameters

A lack of in situ data precludes an exact quantitative assessment of the improvement in accuracy of the 5 km DEM based on ground truth data, as compared with lower resolution DEMs (Bamber 1997). However, results were similar to those from the 10 km grid. For this particular grid surface, slopes less than 0.4° were estimated to have an accuracy better than 1.5 m. For surface slopes greater than 0.65°, height estimates from the altimeter become unreliable. This affects 10% of Antarctica, primarily near the ice margins. The precision for a single data point is ± 0.81 m. This value represents an average over all the different surface types. Accuracy ranges from 10.7 m at 65°S and a slope of 0.65°, to 1.4 m at 75°S and a slope of 0.1°. These errors are dominated by the height variability within each grid cell, rather than errors in the individual altimetric elevation estimates. In summary, the accuracy and noise level of the altimeter data is best over the ice shelves as they are the flattest regions in Antarctica (Bamber, Ekholm, and Krabill 1998, Bamber 1994).

6. Notes and Plans

Limitations of the Data

Problems still remain with lack of high-density surface elevation estimates south of 81.5°S.

7. Products and Access

Contact Information

Please contact NSIDC User Services with any questions.

Data Center Identification

National Snow and Ice Data Center

Procedures for Obtaining Data

Data are available via FTP or through Reverb.

Output Products and Availability

The DEM is provided in a single space-delimited ASCII text file, available via FTP.

8. References

Bamber, J.L., Ekholm, S., and Krabill, W. B. 1998. The accuracy of satellite radar altimeter data over the Greenland ice sheet determined from airborne laser data, Geophysical Research Letters. 25(16): 3177-3180.

Bamber, J.L. and R.A. Bindschadler. 1997. An improved elevation dataset for climate and ice-sheet modelling: validation with satellite imagery. Annals of Glaciology 25:438-444.

Bamber, J.L. and P. Huybrechts. 1996. Geometric boundary conditions for modelling the velocity field of the Antarctic ice sheet. Annals of Glaciology 23:364-373.

Bamber, J. and C. Bentley. 1994. A comparison of satellite-altimetry and ice-thickness measurements of the Ross Ice Shelf, Antarctica. Annals of Glaciology 20:357-364.

Bamber, J. 1994. A digital elevation model of the Antarctic ice sheet derived from ERS-1 altimeter data and comparison with terrestrial measurements. Annals of Glaciology 20:48-54.

Bamber, J. 1994. Ice sheet altimeter processing scheme. International Journal of Remote Sensing 15:925-938.

Brenner, A.C., R.A. Bindschadler, R.H. Thomas, H.J. Zwally. 1983. Slope-induced errors in radar altimetry over continental ice sheets. Journal of Geophysical Research 88:1617-1623.

Davis C.H., H.J. Zwally. 1993. Geographic and seasonal variations in the surface properties of the ice sheets by satellite radar altimetry. Journal of Glaciology 39:687-697.

Zwally, H.J., R.A. Bindschadler, A.C. Brenner, T.V. Martin, R.H. Thomas. 1983. Surface elevation contours of Greenland and Antarctic ice sheets. Journal of Geophysical Research 88(C3):1589-1596.

9. Acronyms and Abbreviations

The following acronyms and abbreviations are used in this document.

ASCII American Standard Code for Information Interchange
DEM Digital Elevation Model
EOSDIS Earth Observing System Data and Information System
ERS-1 The first European Remote Sensing Satellite
FTP File Transfer Protocol
NASA National Aeronautics and Space Administration
NOAA National Oceanic and Atmospheric Administration
NSIDC National Snow and Data Center
SAR Synthetic Aperture Radar

10.Document Information

Document Revision Date

30 April 2004

Document Review Date

15 August 2000

Document Curator

NSIDC Writers

Document URL

http://nsidc.org/data/docs/daac/nsidc0076_antarctic_5km_dem.gd.html