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7 October 2019 DEM generation using point cloud from ICESat and high-resolution satellite stereo images for Indian region
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Precise quantification of land surface dynamics finds its way in various applications ranging from hydrological modeling to disaster management studies. The elevation accuracy of global DEMs generated though stereo images and interferometric techniques are prone to bias due to vegetation and built-up structure. Thus, the global elevation models depict the surface elevations rather than bare earth elevation. Recent advancement in point cloud processing from LiDAR has paved way for isolating ground points i.e., bare earth points from nonground points, thus improving bare earth model generation. Point clouds generated through photogrammetric techniques from very high resolution stereo images has been a promising alternative to LiDAR data. The objective of this study is to understand the capability of point cloud data from spaceborne LiDAR and high resolution stereo images for creating accurate bare earth models for Indian region. This study employs point cloud obtained from ICESat mission and point cloud generated from high-resolution satellite stereo images from Cartosat-1 mission. Various parameters extracted from ICESat waveform were used to extract the bare earth footprints. Filtering techniques were used to extract ground points from photogrammetrically derived point cloud. The bare earth points were interpolated to generate DEM. Resultant DEM were compared to global DEM for elevation changes with respect to different land cover classes.
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Athul Kaitheri and Anandakumar M. Ramiya "DEM generation using point cloud from ICESat and high-resolution satellite stereo images for Indian region", Proc. SPIE 11155, Image and Signal Processing for Remote Sensing XXV, 111551K (7 October 2019);

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