237 The SRTM Data Finishing Process and Products
James A. Slater, Graham Garvey, Carolyn Johnston, Jeffrey Haase, Barry Heady, George Kroenung, and James Little
The Shuttle Radar Topography Mission (SRTM) successfully acquired terrain elevation data for 80 percent of the Earth’s landmass in February 2000. The radar system and data collection scheme designed by NASA’s Jet Propulsion Laboratory (JPL) met the global requirements of the U.S. Department of Defense for Level 2 Digital Terrain Elevation Data (DTED®). JPL processed the raw data into unfinished DTED® 2 and other products that were delivered to two contractors of the National Geospatial-Intelligence Agency. The contractors edited the unfinished DTED® 2, updated the associated products, and generated finished products for distribution. Automated processes were developed by each contractor to identify, delineate and set heights for lakes, rivers, and ocean coastlines in conformance with an extensive set of editing rules created to maintain consistency and uniformity in the final products. The finished DTED® is significantly better than the 16 m vertical accuracy required by the original specification.
249 A Global Assessment of the SRTM Performance
Ernesto Rodríguez, Charles S. Morris, and J. Eric Belz
The NASA/NGA Shuttle Radar Topography Mission (SRTM) collected interferometric radar data which has been used by the Jet Propulsion Laboratory to generate a near-global topography data product for latitudes smaller than 60°. One of the primary goals of the mission was to produce a data set that was globally consistent and with quantified errors. To achieve this goal, an extensive global ground campaign was conducted by NGA and NASA to collect ground truth that would allow for the global validation of this unique data set. This paper documents the results of this SRTM validation effort using this global data set. The table shown below summarizes our results (all quantities represent 90 percent errors in meters).
|Africa||Australia||Eurasia||Islands||N. America||S. America|
|Absolute Geolocation Error||11.9||7.2||8.8||9.0||12.6||9.0|
|Absolute Height Error||5.6||6.0||6.2||8.0||9.0||6.2|
|Relative Height Error||9.8||4.7||8.7||6.2||7.0||5.5|
In the paper, we present a detailed description of how the results in this table were obtained. We also present detailed characterizations of the height and planimetric components of the error, their magnitudes, geographical distribution, and spatial structure.
261 How Complementary are SRTM-X and -C Band Digital
Jörn Hoffmann and Diana Walter
Two different digital elevation models (DEM) were derived during the 2000 Shuttle Radar Topography Mission from C- and X-band interferometric radar data. While these two DEMs share several of their properties, they were processed independently. Here, we investigate what can be gained by merging the two DEMs into a single composite DEM for four different test areas. Based on an analysis of the relative differences and the deviations from an absolute reference in one test area, we propose an algorithm for combining the two DEMs optimally. We then compare the composite DEM with both individual DEMs and with a reference of a large number of precise GPS profiles in one test area in southern Germany. We find that in our test areas, the area of missing values is reduced significantly in the composite DEM. Even compared with the more complete C-band DEM, the number of void pixels can be reduced by 22 percent to 53 percent. Also, outlier values resulting from errors in the interferometric phase unwrapping can often be identified and removed in the merging. The deviations of both C- and X-band DEMs from the GPS reference are very similar and well within the accuracy specifications of the global data set. The standard deviation of the difference between the composite DEM and the reference is about 14 percent below that of the original values. Depending on the requirements for completeness and accuracy, merging the two SRTM elevation data sets may provide an important improvement above either of the original DEMs.
269 Geomorphometry from SRTM: Comparison to NED
Peter L. Guth
The Shuttle Radar Topography Mission (SRTM) produced near-global 1" and 3" DEMs. The cartographically-derived National Elevation Dataset (NED) provides a mechanism to assess SRTM quality. We compared 12 geomorphometric parameters from SRTM to NED for about 500,000 sample areas over the continental United States. For basic parameters like average elevation or relief, the two data sets correlate very highly. For more derived measures, such as curvature and higher moments (skewness and kurtosis), the correlations are much lower, with some parameters essentially uncorrelated between the two DEMs. Correlations improve after restricting analysis to region with average slopes greater than 5 percent, and the SRTM data set compares more closely to simulated 2" NED than to 1" NED. SRTM has too much noise in flat areas, increasing average slope, while in high relief areas SRTM over smoothes topography and lowers average slopes. The true resolution of 1" SRTM DEMs proves to be no better than 2".
279 Validation of SRTM Elevations Over Vegetated and
Non-vegetated Terrain Using Medium-Footprint Lidar
Michelle Hofton, Ralph Dubayah, J Bryan Blair, and David Rabine
The Shuttle Radar Topography Mission (SRTM) generated one of the most complete high-resolution digital topographic data sets of the world to date. The elevations generated by the on-board C-band sensor represent surface elevations in "bare earth" regions, and the elevations of various scatterers such as leaves and branches in other regions. Elevations generated by a medium-footprint (>10m diameter) laser altimeter (lidar) system known as NASA's Laser Vegetation Imaging Sensor (LVIS) were used to assess the accuracy of SRTM elevations at study sites of variable relief, and land-cover. Five study sites in Maine, Massachusetts, Maryland, New Hampshire, and Costa Rica were chosen where coincident LVIS and SRTM data occur. Both ground and canopy top lidar elevations were compared to the SRTM elevations. In"bare earth" regions, the mean vertical offset between the SRTM elevations and LVIS ground elevations varied with study site and was approximately 0.0m, 0.5m, 3.0m, 4.0m, and 4.5m at the Maine, Maryland, Massachusetts, New Hampshire, and Costa Rica study sites, respectively. In vegetated regions, the mean vertical offset increased, implying the phase center fell above the ground, and the offset varied by region. The SRTM elevations fell on average approximately 14m below the LVIS canopy top elevations, except in Costa Rica where they were approximately 8 m below the canopy top. At all five study sites, SRTM elevations increased with increasing vertical extent (i.e., the difference between the LVIS canopy top and ground elevations and analogous to canopy height in vegetated regions). A linear relationship was found sufficient to describe the relationship between the SRTM-LVIS elevation difference and canopy vertical extent.
287 SRTM C-band and ICESat Laser Altimetry Elevation
Comparisons as a Function of Tree Cover and Relief
Claudia C. Carabajal and David J. Harding
The Geoscience Laser Altimeter System (GLAS) instrument onboard the Ice, Cloud, and land Elevation Satellite (ICESat) provides a globally distributed elevation data set that is well-suited to independently evaluate the accuracy of digital elevation models (DEMs), such as those produced by the Shuttle Radar Topography Mission (SRTM). We document elevation differences between SRTM C-band 1 and 3 arcsecond resolution DEMs and ICESat 1064 nm altimeter channel elevation data acquired in an areas of variable topography and vegetation cover in the South American Amazon Basin, Asian Tibetan Plateau – Himalayan Mountains, East Africa, western Australia, and the western United States. GLAS received waveforms enable the estimation of SRTM radar phase center elevation biases and variability with respect to the highest (canopy top where vegetated), centroid (distance-weighted average), and lowest (ground) elevations detected within ICESat laser footprints. Distributions of ICESat minus SRTM elevation differences are quantified as a function of waveform extent (a measure of within-footprint relief), SRTM roughness (standard deviation of a 3 × 3 array of elevation posts), and percent tree cover as reported in the Vegetation Continuous Field product derived from Moderate Resolution Imaging Spectrometer (MODIS) data. SRTM roughness is linearly correlated with waveform extent for areas where percent tree cover is low. The SRTM phase center elevation is usually located between the ICESat highest and lowest elevations, and on average is closely correlated with the ICESat centroid. In areas of low relief and sparse tree cover, the mean of ICESat centroid minus SRTM phase center elevation differences for the five regions examined vary between -3.9 and 1.0m, and the corresponding standard deviations are between 3.0 and 3.7 m. With increasing SRTM roughness and/or tree cover, the SRTM elevation remains essentially unbiased with respect to the ICESat centroid but the standard deviations of the differences increase to between 20 and 34m, depending on the region. For the Australia, Amazon, Africa, United States, and Asia regions, including all tree cover and roughness conditions, 90 percent of the SRTM elevations are within 6.9, 11.5, 12.1, 16.8, and 37.1m of the ICESat centroid, respectively. In vegetated areas, the SRTM elevation on average is located approximately 40 percent of the distance from the canopy top to the ground. The variability of this result increases significantly with increasing SRTM roughness. The results are generally consistent for the five regions examined, providing a method to estimate for any location the correspondence between SRTM elevations and highest, average, and lowest elevations using the globally-available MODIS-derived estimate of tree cover and the measure of SRTM roughness.
299 Mapping Height and Biomass of Mangrove Forests in
the Everglades National Park with SRTM Elevation Data
Marc Simard, Keqi Zhang, Victor H. Rivera-Monroy, Michael S. Ross, Pablo L. Ruiz, Edward Castañeda-Moya, Robert R. Twilley , and Ernesto Rodriguez
We produced a landscape scale map of mean tree height in mangrove forests in Everglades National Park (ENP) using the elevation data from the Shuttle Radar Topography Mission (SRTM). The SRTM data was calibrated using airborne lidar data and a high resolution USGS digital elevation model (DEM). The resulting mangrove height map has a mean tree height error of 2.0 m (RMSE) over a pixel of 30 m. In addition, we used field data to derive a relationship between mean forest stand height and biomass in order to map the spatial distribution of standing biomass of mangroves for the entire National Park. The estimation showed that most of the mangrove standing biomass in the ENP resides in intermediate-height mangrove stands around 8 m. We estimated the total mangrove standing biomass in ENP to be 5.6 × 109 kg.
313 Capability of SRTM C and X Band DEM Data to
Measure Water Elevations in Ohio and the Amazon
Brian Kiel, Doug Alsdorf, and Gina LeFavour
We analyze Shuttle Radar Topography Mission (SRTM) water surface elevation data to assess the capacity of interferometric radar for future surface water missions. Elevations from three Ohio reservoirs and several Amazon floodplain lakes have standard deviations, interpreted as errors, that are smaller in C-band compared to X-band and are smaller in Ohio than in the Amazon. These trends are also evident when comparing water surface elevations from the Muskingum River in Ohio with those of the Amazon River. Differences are attributed to increased averaging in C-band compared to X-band, greater sensitivity to surface water motion in X-band, and generally larger off-nadir look angles in X-band. Absolute water surface elevations are greater in the C-band DEM for much of the two study areas and yield expected slope values. Height and slope differences are attributed to differing usage of geoids and ellipsoids. These SRTM measurements suggest the great possibility for space-based, laterally-spatial (2D) measurements of water surface elevations.
321 Detection of Ancient Settlement Mounds – Archaeological
Survey Based on the SRTM Terrain Model
B.H. Menze, J.A. Ur, and A.G. Sherratt
In the present study we demonstrate the value of the SRTM three arcsecond terrain model for a virtual survey of archaeological sites: the detection and mapping of ancient settlement mounds in the Near East. These so-called "tells" are the result of millennia of occupation within the period from 8000–1000 BC, and form visible landmarks of the world's first farming and urban communities. The SRTM model provides for the first time an opportunity to scan areas not yet surveyed archaeologically on a supra-regional scale and to pinpoint probable tell sites. In order to map these historic monuments for the purpose of settlement-study and conservation, we develop a machine learning classifier which identifies probable tell sites from the terrain model. In a test, point-like elevations of a characteristic tell shape, standing out for more than 5 to 6 m in the DEM were successfully detected (85/133 tells). False positives (327/(600*1200) pixels) were primarily due to natural elevations, resembling tells in height and size.