Land Cover Classification by Gaofen Satellite Images Based on CART Algorithm in Yuli County, Xinjiang, China

High-resolution remote-sensing images can be used in human activity analysis and criminal monitoring, especially sparsely populated zones. In this paper, we explore the applicability of China’s Gaofen satellite land cover classification Xinjiang, China. First all, features spectral reflectance a normalized radar cross section (NRCS) for different types covers were analyzed. Moreover, seasonal variation NRCS SAR (Synthetic Aperture Radar) study area, Dunkuotan Village Yuli County, China, was demonstrated by GEE (Google Earth Engine) platform accordingly. Finally, CART (classification regression trees) algorithm DT (decision tree) applied to investigate western area China when both optical employed. An overall accuracy 83.15% with kappa coefficient 0.803 observed using GF-2/GF-3 (2017–2021) area. The DT-based procedure proposed investigation proved that series engaged effectively promote routine workflow administrative department.