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Investigating the Terrain Complexity from ATL06 ICESat-2 data for Terrain Elevation and its Use for Assessment of Openly accessible InSAR based DEMs in parts of Himalaya's
1  Indian Institute of Remote Sensing, Dehradun, India
Academic Editor: Cosimo Distante

Abstract:

Spaceborne sensors are now providing invaluable datasets for the Earth’s surface studies. Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) with Advanced Topographic Laser Altimeter System (ATLAS) instrument was launched by NASA on September 15, 2018, to measure the elevation of Earth’s surface using laser wavelength of 532 nm and pulse repetition frequency of 10kHz giving footprint of approximately 70cm on the ground. The ICESat-2 datasets are used in this study for the visualization and investigation of the complex Himalayan terrain in the parts of the Kinnaur district and surroundings, which are prone to landslides due to the geology of the region as observed during the recent landslide events. The ICESat-2 elevation data sets were compared with the openly accessible DEM datasets namely, ALOS PALSAR RTC HR (12.5m) and TanDEM-X (90m) at ICESat-2 footprint locations. Preprocessing of datasets was done for selecting ICESat-2 footprints (Track ID: 325, 1270, 828, 386) at locations of high-quality datasets for analysis. The analysis of pre-processed 19,755 ICESat-2 footprints (out of 20,948 footprints) was done with ALOS PALSAR RTC HR (12.5m) and TanDEM-X (90m) datasets. The visualization of the region in the Google earth and OpenAltimetry 3D viewer depicts that the mountain slopes are very steep indicating rugged terrain difficult to access and challenging for construction of transport facilities. The results of Track ID: 325, show that the range of elevations in ICESat-2 elevation values in the study area is from 3409.75m to 5976.31m. The standard deviation representing terrain ruggedness using ICESat-2 elevation values is found as 432.06m. Considering higher accuracy ICESat-2 values for the difficult terrain as a reference, the mean error (ME), mean absolute error (MAE), and RMSE for TanDEM-X were found as 0.26m, 12.92m, and 17.4m respectively. Whereas the ME, MAE, and RMSE for ALOS PALSAR RTC HR DEM were found as 0.20m, 9.50m, and 13.88m respectively. Thus for the study site, using ICESat-2 ATL06 products, ALOS PALSAR RTC HR DEM is found more suitable than TanDEM-X 90m openly accessible datasets for any kind of application.

Keywords: LiDAR, ATLAS, DEM, ALOS PALSAR RTC HR, TanDEM-X
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