SRTM 9. 0m Digital Elevation Database v. The SRTM digital elevation data, produced by NASA originally, is a major breakthrough in digital mapping of the world, and provides a major advance in the accessibility of high quality elevation data for large portions of the tropics and other areas of the developing world. Introduction. The SRTM digital elevation data provided on this site has been processed to fill data voids, and to facilitate it’s ease of use by a wide group of potential users. This data is provided in an effort to promote the use of geospatial science and applications for sustainable development and resource conservation in the developing world. Digital elevation models (DEM) for the entire globe, covering all of the countries of the world, are available for download on this site. The SRTM 9. 0m DEM’s have a resolution of 9. RESEARCH ARTICLE Performance Estimation of Aster Global DEM Depending upon the Terrain Inclination Umut Gunes Sefercik Received: 24 November 2011 /Accepted: 6 January. I have had many requests over the years to add a USGS topographic Map overlay without the map borders. This is a huge project and I have finally decided to move. Want to elevate your chances of finding a digital elevation model? Sure you do. You should dive into our list of free global DEM data sources. Learn about the many gridded elevation formats supported by Global Mapper GIS software. The Land Processes Distributed Active Archive Center (LP DAAC) is one of several discipline-specific data centers within the NASA Earth Observing System Data and. The Shuttle Radar Topography Mission (SRTM) obtained elevation data on a near-global scale to generate the most complete high-resolution digital topographic database. ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is a Japanese sensor which is one of five remote sensory devices on board the Terra satellite. All are produced from a seamless dataset to allow easy mosaicing. These are available in both Arc. Info ASCII and Geo. Tiff format to facilitate their ease of use in a variety of image processing and GIS applications. Data can be downloaded using a browser or accessed directly from the ftp site. If you find this digital elevation data useful, please let us know at csi@cgiar. The NASA Shuttle Radar Topographic Mission (SRTM) has provided digital elevation data (DEMs) for over 8. This data is currently distributed free of charge by USGS and is available for download from the National Map Seamless Data Distribution System, or the USGS ftp site. The SRTM data is available as 3 arc second (approx. DEMs. A 1 arc second data product was also produced, but is not available for all countries. The vertical error of the DEM’s is reported to be less than 1. The data currently being distributed by NASA/USGS (finished product) contains “no- data” holes where water or heavy shadow prevented the quantification of elevation. These are generally small holes, which nevertheless render the data less useful, especially in fields of hydrological modeling. Andy Jarvis and Edward Guevara of the CIAT Agroecosystems Resilience project, Hannes Isaak Reuter (JRC- IES- LMNH) and Andy Nelson (JRC- IES- GEM) have further processed the original DEMs to fill in these no- data voids. This involved the production of vector contours and points, and the re- interpolation of these derived contours back into a raster DEM. These interpolated DEM values are then used to fill in the original no- data holes within the SRTM data. These processes were implemented using Arc/Info and an AML script. The DEM files have been mosaiced into a seamless near- global coverage (up to 6. WGS8. 4 datum. These files are available for download in both Arc- Info ASCII format, and as Geo. Tiff, for easy use in most GIS and Remote Sensing software appications. In addition, a binary Data Mask file is available for download, allowing users to identify the areas within each DEM which has been interpolated. Methodology. The first release of Shuttle Radar Topography Mission (SRTM) data was provided in 1- degree digital elevation model (DEM) tiles from the USGS ftp server (ftp: //e. The data was released continent by continent, as and when the data was processed by NASA and the USGS. For the United States, data was made available at 1- arc second resolution (approximately 3. SRTM elevation data has now been released for the entire terrestrial surface, and a “Finished” product has now been released (ftp: //e. SRTM3/). In this web site, the Consortium for Spatial Information (CGIAR- CSI) of the Consultative Group for International Agricultural Research (CGIAR) is offering post- processed 3- arc second DEM data for the globe. The original SRTM data has been subjected to a number of processing steps to provide seamless and complete elevational surfaces for the globe. In its original release, SRTM data contained regions of no- data, specifically over water bodies (lakes and rivers), and in areas where insufficient textural detail was available in the original radar images to produce three- dimensional elevational data. There are a total of 3,4. Nepal they constitute 9. No- data regions due to insufficient textural detail were especially found in mountainous regions (Himalayas and Andes, for example), or desertic regions (e. Sahara). The existence of no- data regions in a DEM cause significant problems in using SRTM DEMs, especially in the application of hydrological models which require continuous flow surfaces. For the CGIAR- CSI SRTM data product we apply a hole- filling algorithm to provide continuous elevational surfaces. The data is projected in a Geographic (Lat/Long) projection, with the WGS8. EGM9. 6 vertical datum. We follow the method described by Reuter et al. The first processing stage involves importing and merging the 1- degree tiles into continuous elevational surfaces in Arc. GRID format. The second process fills small holes iteratively, and the cleaning of the surface to reduce pits and peaks. The third stage then interpolates through the holes using a range of methods. The method used is based on the size of the hole, and the landform that surrounds it. The processing is made using Arc/Info AML model. Specifically: The original SRTM DEM (finished grade data downloaded fromftp: //e. SRTM3/ is used to produce contours or points (depending on the interpolation methodology to be used for the void). Processing was made on a void by void basis. 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. When no high resolution auxiliary DEM is available, the 3. SRTM3. 0 DEM is used as an auxiliary for large voids. For areas with a high resolution auxiliary DEM: The contours and points surrounding the hole and inside the hole are interpolated to produce a hydrologically sound DEM using the TOPOGRID algorithm in Arc/Info. TOPOGRID is based upon the established algorithms of Hutchinson (1. 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. For areas without a high resolution auxiliary DEM: The most appropriate interpolation technique is selected based on void size and landform typology, and applied on the data immediately surrounding the hole, using SRTM3. The best interpolations methods can be generalised as: Kriging or Inverse Distance Weighting interpolation for small and medium size voids in relatively flat low- lying areas; Spline interpolation for small and medium sized voids in high altitude and dissected terrain; Triangular Irregular Network or Inverse Distance Weighting interpolation for large voids in very flat areas, and an advanced Spline Method (ANUDEM) for large voids in other terrains. 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. 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 (2. Auxiliary DEMs were available from the following sources: The original SRTM DEM (finished grade data downloaded from ftp: //e. SRTM3/ is used to produce contours or points (depending on the interpolation methodology to be used for the void). Processing was made on a void by void basis. 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. When no high resolution auxiliary DEM is available, the 3. SRTM3. 0 DEM is used as an auxiliary for large voids. For areas with a high resolution auxiliary DEM: The contours and points surrounding the hole and inside the hole are interpolated to produce a hydrologically sound DEM using the TOPOGRID algorithm in Arc/Info. TOPOGRID is based upon the established algorithms of Hutchinson (1. 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. For areas without a high resolution auxiliary DEM: The most appropriate interpolation technique is selected based on void size and landform typology, and applied on the data immediately surrounding the hole, using SRTM3. The best interpolations methods can be generalised as: Kriging or Inverse Distance Weighting interpolation for small and medium size voids in relatively flat low- lying areas; Spline interpolation for small and medium sized voids in high altitude and dissected terrain; Triangular Irregular Network or Inverse Distance Weighting interpolation for large voids in very flat areas, and an advanced Spline Method (ANUDEM) for large voids in other terrains. This dataset is very detailed along shorelines, and contains all small islands. More information about this dataset is available in USGS (2.
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