Generation of high-quality digital elevation models by assimilation of remote sensing-based DEMs

Abstract

Advanced spaceborne remote sensing techniques are currently available for the generation of high-resolution digital elevation models (DEMs) aiding in the advancement of Earth’s topographic modeling. DEM assimilation using data-driven models is a technique that can effectively overcome the limitations of individual DEMs generated from different techniques and sources of remote sensing data. The assimilation of DEMs generated from optical stereo pairs (Cartosat-1) and InSAR pair (ALOS PALSAR-1) was done for improving the DEM quality. Further, by using data assimilation techniques, the openly accessible DEM products derived from remote sensing datasets were used for generation of improved high-quality DEMs. The feature level fusion and the Kalman optimal interpolation techniques were used for the assimilation of these DEMs. Three sites, namely Dehradun, Jaipur, and Kendrapara, were selected on basis of topographic conditions, i.e., rugged, moderate, and gentle. RMSEs calculated for Dehradun and Jaipur have shown significant improvement in assimilated DEMs. Assimilation of CartoDEM V3 R1 and ALOS PALSAR RTC HR DEMs at the Jaipur site has resulted in highly improved RMSE in elevation of 1.22 m using the Kalman optimum interpolation model. However, in case of the plain region of Kendrapara, the CartoDEM V3 R1 data are found to have the highest accuracy of 2.00 m, indicating importance of selective use of input DEMs and assimilation methods.