FINE CLASSIFICATION OF POLSAR LAND COVER TYPES BASED ON MULTI-BAND

Considering the distinct scattering characteristics observed in diverse frequency bands for terrain surfaces, the utilization of complementary information from multi-band PolSAR data proves advantageous in effectively distinguishing targets that may present challenges when assessed in isolation within a single band. In this study, we employ the polarimetric target decomposition methods to investigate the scattering characteristics of representative targets within the C and L bands. Based on these findings, we construct a random forest fine classification model specifically tailored for different types of urban vegetation. Notably, experimental results demonstrate a noteworthy enhancement in classification accuracy following the integration of multi-band data.