Potential of Quad-Polarimetric SAR Data in Identifying Flat Areas Over Natural Geological Surfaces

In this paper, we investigate the potential of polarimetric synthetic aperture radar (SAR) in identifying flat areas using fractal dimension and polarimetric scattering similarity. A two-step method is proposed, including rough selection and fine selection. First, rough selection is performed by calculating the fractal dimension of the radar backscattered total power image. Then for each candidate region, the fine selection is conducted using polarimetric scattering similarity parameters. Furthermore, the effectiveness of the method is verified by GF-3 quad-polarimetric SAR data and SRTM1 DEM data in desert areas of China. Results show that for the final selected flat area (320 × 320 m), the maximum elevation deviation is 3.39 m and the elevation standard deviation is 0.72 m. Therefore, without depending on additional DEM data, the proposed method can effectively achieve flat areas identification, which can be helpful for the future application of polarimetric SAR data in the Moon.