SRTM data was notorious when it was first released in 2003. With the release of SRTM V2 by NASA, all of the spikes and wells have reported been removed from the 'Finished' data (although the Australian data has not yet been processed) and the coastlines have been masked for unambiguous definition of coastal areas. However, many void areas still exist. These have commonly been interpolated out. The BLACKART program available from this website was one of the first utilities available for such interpolations. Several other GIS applications have added this ability, including 3DEM and MicroDem.
Interpolation provides an OK solution in areas of low relief. In mountainous areas it can produce very poor results, for example turning mountain tops into plateaus and filling in valleys. BLACKART attempted to remedy this by merging alternative DEM data sets into the SRTM data and then patching the holes with the merged data. This was sometimes better, but still suffered from problems. Standard error between the DEM datasets produced uneven transitions in the patched area. For practical purposes, the DEM data available for merging was of much lower resolution than the SRTM target.
The CGIAR consortium has confronted the task of improving the situation by processing the native SRTM data using the best available patching solutions. For example one of the data sets they use is data from Jonathan de Ferranti's PathfinderPanorama web site. Mr. De Ferranti uses an innovative (if not laborious) technique of contour line extension to provide much better patch data. In this process, the contour lines are first generated from the SRTM. Then the missing or corrupted contour lines are fixed by extending adjacent contour lines, using (usually Russian topo) contour map data. This is probably done by a manual or semi-manual method. Once the contour lines are prepared, the contour map is interpolated to produce a DEM. The DEM is then merged with the source SRTM, preserving the valid data and applying the patch. As a result new data is added to the map and transitions are much more continuous.
Quoting from the CGIAR website:
" THE SRTM DATA NOW AVAILABLE FROM THIS SITE HAS BEEN UPGRADED TO VERSION 3. THIS LATEST VERSION REPRESENTS A SIGNIFICANT IMPROVEMENT FROM PREVIOUS VERSIONS DUE TO USE OF USGS "FINISHED" GRADE DATA, FURTHER OPTIMISATION OF THE HOLE FILLING ALGORITHM AND THE USE OF AUXILLARY DEMs FOR FILLING IN THE HOLES. FURTHER INFORMATION IS AVAILABLE ON THE METHODS PAGE.
The first processing stage involves importing and merging the 1-degree tiles into continuous elevational surfaces in ArcGRID format. The second process fills the no-data holes through an interpolative technique within an Arc/Info AML model:
1. The original SRTM DEM (finished grade data downloaded from ftp://e0srp01u.ecs.nasa.gov/srtm/version2/SRTM3/ is used to produce contours at an interval of 10 vertical metres (which was lowered in cases where the region around the void had less than 10m elevation difference). Processing was made on a void by void basis.
2. In cases when a higher resolution auxiliary DEM was available, a point coverage is produced of the elevation values at the centre of each cell of the auxiliary DEM within void areas.
3. The contours and points if available are interpolated to produce a hydrologically sound DEM using the TOPOGRID algorithm in Arc/Info. TOPOGRID is based upon the established algorithms of Hutchinson (1988; 1989), designed to use contour data (and stream and point data if available) to produce hydrologically sound DEMs. This process interpolates through the no-data holes, producing a smooth elevational surface where no data was originally found. Drainage enforcement is activated, and the tolerances set at 5 for "tolerance 1", representing the density and accuracy of input topographic data, and a horizontal standard error of 1m and vertical standard error of 0m.
4. The interpolated DEM for the no-data regions is then merged with the original DEM to provide continuous elevational surfaces without no-data regions. This entire process is performed for tiles with large overlap with neighbouring tiles, thus ensuring seamless and smooth transitions in topography in large void areas.
5. The resultant seamless dataset is then clipped along coastlines using the Shorelines and Water Bodies Database (SWBD). This dataset is very detailed along shorelines, and contains all small islands. More information about this dataset is available in USGS (2006c).
Auxiliary DEMs were available from the following sources:
· USA - NED 3-arc second digital elevation model for mainland USA, Alaska, Hawaii and Puerto Rico. Available from USGS Seamless
· Mexico - 90m DEM available from INEGI
· Canada - Canadian Digital Elevation Data Level 1derived from 1:50,000 and 1:250,000 topographic maps, available from Geobase
· New Zealand - 100m DEM made kindly available by Geographx
· Australia - GEODATA TOPO 100k contour data, interpolated to produce a 90m DEM available from Geoscience Australia
· Mountainous areas in Central Asia, China, Europe, Caucasus, Northern Andes and Southern Andes based on data from Jonathan de Ferranti's webpage: Viewfinder Panoramas
· Costa Rica - 50m DEM derived from digitized topographic maps made available to CIAT by Antonio Trabucco.
· Ecuador - a 90m DEM derived from digitized topographic maps available from Dr. Marc Souris
· Global - Where other auxiliary DEMs were not available, the SRTM30 1km product was used as an auxiliary DEM (USGS, 2006d).
This method produces a smooth elevational surface of no-data regions. Whilst micro-scale topographic variation is not captured using this method, most macro-scale features are captured in small-intermediate sized holes. Jarvis et al. (2004) (available here) make a detailed analysis of the accuracy of the interpolated elevational data in a region in Colombia with 43% of the region containing no-data in the original SRTM release. They find an average vertical error of just 5m in interpolated regions when compared with a DEM derived from cartographic maps, though the maximum error stretches to 257m in a region with approximately 1500m elevation. When hydrological models are applied to the interpolated DEM and the cartographic DEM, little difference is found in hydrological response in terms of overland flow and discharge. "
The processed CGIAR data is archived in 5 degree tiles in GEOTIFF or ArcInfo ASCII. This tutorial uses GEOTIFF. The procedure for downloading data is as follows:
Select the 'SRTM Data Search and Download' menu item from the SRTM DEM page. Now, select you tile of interest. The easiest way is to click on a map grid illuminating one or more tiles. The tiles are quite large so you may want to choose one at a time. After selecting, pick 'Search'. If you want the data, select 'Data Download FTP'. If you want the mask showing where the voids were, select one of the mask downloads. The data file is large, approximately 39MB. It does not match any original SRTM tiles as it covers 5 degrees of latitude and longitude rather than the original one degree of the SRTM data. The alternative websites offer the tiles in the smaller size and this may be more convenient, particularly if you are trying to match an overlay that is sized for the SRTM tiles.
After downloading, unzip the file. It can be opened with a variety of applications, including 3DEM, Global Mapper and MicroDem. An example of the Global Mapper image is shown at the right. The corresponding 3DEM image is shown below.
The CGIAR data set is recommended over the native SRTM data for the reasons cited. It is also welcome in light of US government agencies converting formerly free data sets to fee-based access (ASTER for example.)e