ESRGAN-BASED DEM SUPER-RESOLUTION FOR ENHANCED SLOPE DEFORMATION MONITORING IN LANTAU ISLAND OF HONG KONG
Monitoring, evaluating and understanding the slopes by Interferometric Synthetic Aperture Rader (InSAR) technology are critical for both human economy and natural environment. However, the resolution limitation of existing digital elevation model (DEM) in the slope areas causes the DEM phase residues and atmospheric effects promoted, which will influence the interpret accuracy of InSAR results. In this study, we propose a novel two-step ESRGAN-based DEM SR method to effectively recover high-resolution DEM from the original version. Firstly, we pretrain an ESRGAN with a large number of natural images. Based on it, we transfer the learnt knowledge into the DEM problem and fine-tune the DEM SR network. The recovered DEMs are utilized as the reference data to improve slope deformation monitoring and enhance the accuracy of InSAR estimation, especially in the mountainous areas with cloudy and rainy weather. Experiments indicate that the proposed method can achieve better results than the traditional methods and works in phase simulation, which is one of the key step of InSAR deformation monitoring.