An Improved Decomposition Algorithm to Differentiate Forest from Urban Targets with Strong Double Scattering in Polsar Data

• Published in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium pp. 1035 - 1038
• Main Authors: Zhang, Yin, Wang, Yong, Duan, Dingfeng, Li, Hong
• Format: Conference Proceeding
• Language: English
• Published: IEEE 17.07.2022
• Subjects: Azimuthal symmetry; Classification algorithms; Forest target; Forestry; L-band; Polarimetric synthetic aperture radar (PolSAR); PolSAR decomposition; Radar scattering; Scattering; Urban areas; Urban target; Usability
• ISSN: 2153-7003
• DOI: 10.1109/IGARSS46834.2022.9883930

Trees in flat and wet forest floors and urban targets with small orientation angles can produce strong double scattering. Then, misclassification of trees as urban targets occurs in the PolSAR data decomposition. This study proposed an improved decomposition algorithm for the urban and forest targets classification. First, strong double scattering between forest and urban targets was differentiated, and then forest targets were treated as azimuthally symmetric radar targets in the PolSAR decomposition algorithm. The improved decomposition algorithm was verified by two L-band PolSAR datasets, a UAVSAR dataset northwest New Bern, NC, USA, and one ALOS PALSAR dataset San Francisco, CA, USA. In the datasets, the double scattering was dominant for forested areas. The double scattering dominated some urban areas, but other urban areas had strong volume scattering. Nevertheless, the revised decomposition algorithm correctly delineated both types of targets and extended the usability of the original decomposition algorithm.