DEM ASTER

HowTo|HowTo

ASTER GDEM v2
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is one of a number of instruments on board the Terra platform, which was launched in December 1999. ASTER provides fourteen spectral bands with 15- to 90-meter resolutions depending on the band(s). [...] The instrument consists of three separate telescopes; each provides a different spectral range and resolution. The VNIR (visible and near-infrared) sensor provides 4 bands at 15-meter resolution. The SWIR (short-wave infrared) sensor provides 6 bands at 30-meter resolution. The TIR (thermal infrared) sensor provides 5 bands at 90-meter resolution. [...] ASTER data distributed from the Land Processes Distributed Active Archive Center is available in the Universal Transverse Mercator (UTM) projection, with a resampling method of cubic convolution for daytime scenes and nearest neighbor for nighttime scenes. Files are in the HDF-EOS or GeoTIFF format with the exception of ASTER Level-3 products, which are available in GeoTIFF only. 

Download
The ASTER GDEM covers land surfaces between 83°N and 83°S and is comprised of 22,702 tiles. Tiles that contain at least 0.01% land area are included. The ASTER GDEM is distributed as Geographic Tagged Image File Format (GeoTIFF) files with geographic coordinates (latitude, longitude). The data are posted on a 1 arc-second (approximately 30–m at the equator) grid and referenced to the 1984 World Geodetic System (WGS84)/ 1996 Earth Gravitational Model (EGM96) geoid.


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Quality and Validation
ASTER images record the reflective surface, thus the derived elevations in GDEM v2 represent the height of those imaged surfaces. In areas with dense, taller vegetation or built structures, the derived ASTER elevation will represent the elevation of these features rather than ground level.

The Root Mean Square Error (RMSE) is an accuracy metric commonly used for elevation data, and the measured RMSE for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 m for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset (either positive or negative) from the true ground level. The GDEM v2 mean error of -0.20 meters is a significant improvement compared to the GDEM v1 mean error of -3.69 meters.


 * http://www.isprs2012.org/abstract/299.asp


 * https://lpdaac.usgs.gov/products/aster_products_table/aster_gdem_version_2_validation


 * http://gis.cri.fmach.it/aster-gdem-quality/

Filtering
The DEM can be rather well filtered and smoothed with the Sun's denoising algorithm using GRASS add-on r.denoise.

r.denoise denoises (smooths/despeckles) topographic data, particular DEMs derived from radar data (including SRTM), using Xianfang Sun's denoising algorithm. It is designed to preserve sharp edges and to denoise with minimal changes to the original data.

Experiments showed that the best smoothing of ASTER GDEM 2 is reached with such parameters of :

threshold = 0.8 iterations = 10-20

Also filtering with r.neighbors by "average" method and window size >=5 is quite useful to remove some noise from DEM.


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