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Fujisada H.,Sensor Information Laboratory Corporation | Urai M.,Sensor Information Laboratory Corporation | Iwasaki A.,Sensor Information Laboratory Corporation
IEEE Transactions on Geoscience and Remote Sensing | Year: 2012

At the core of the technical methodology for creating the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) global digital elevation model (GDEM) is the procedure for generating a global set of 1 $ \circ latitude-by-1$ circ longitude tiles containing DEM data in geographic latitude and longitude coordinates and with one arc second postings from scene-based ASTER DEMs. The ASTER GDEM is comprised of all tiles, which include at least 0.01% land in them, each containing 3601-by-3601 elevation data points. The tiles are created by stacking all observed scene DEM data matched geographically to the tile container, selecting valid data for each pixel, removing abnormal data values, and then averaging the remaining selected valid data to assign as the tile elevation data. Valid Earth surface elevation values typically clump within a $\pm$ 40-m range and are assumed to be lower in elevation than residual cloud outliers. The filtering process, which assigns the tile elevation data, is one of the most important parts of the GDEM generation system. The median-based selection method is designed to efficiently select the valid data for each pixel. The combination of cloud-masked and non-cloud-masked data is another important part of the process to assign accurate elevation data for each pixel, because the cloud masking capability is not perfect. The algorithm used to combine both data is described. The postprocessing for inland water bodies is successfully carried out to yield a flattened elevation value. This postprocessing is essential to assign unique elevation values for each inland water body. GDEM tile elevation data include some residual anomalies, mostly in areas with fewer than three valid stacked input scenes. The correction method using existing reference data also is described. © 1980-2012 IEEE.


Fujisada H.,Sensor Information Laboratory Corporation | Urai M.,Sensor Information Laboratory Corporation | Iwasaki A.,Sensor Information Laboratory Corporation
IEEE Transactions on Geoscience and Remote Sensing | Year: 2011

Image matching and water-body-detection methodologies are essential parts of generating good-quality digital elevation model (DEM) data. It is one of the very important results for image matching where 1-D searching in the along-track direction is sufficient to find the maximum correlation point if reconstructed unprocessed Advanced Spaceborne Thermal Emission and Reflection data (Level-1A data) are used as the source data for DEM products. This important situation is obtained from the general formulation of how to make 1-D searching possible. The image matching quality is evaluated for this 1-D searching method. An image correlation kernel size of 5 by 5 is recommended as the most suitable selection for better horizontal resolution with a slight sacrifice of the image matching error. The satellite pointing fluctuation effect on image matching is also evaluated, leading to the conclusion that it does not seriously affect DEM quality. The water-body-detection technique is another core of DEM generation. The low image correlation coefficient, the low reflectance of water in the near-infrared band 3N, and other spectral characteristics of water were used to identify surface water bodies. In addition, water-body size and the standard deviation of the water-body perimeter elevation are limited for consistent detection without misidentification. As a result, the minimum size of a detectable water body is 0.2 km2. © 2011 IEEE.

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