Information extraction methods of coastal wetland based on GF-3 fully polarimetric SAR data
HE Chenlinqiu1,2(), CHENG Bo1(), CHEN Jinfen1,2, ZHANG Xiaoping1,2
1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China 2. University of Chinese Academy of Sciences, Beijing 100049, China
The study on the information extraction methods of coastal wetlands is highly significant for accurately grasping the distribution status of coastal wetlands and for protecting and managing the rare resources in coastal wetlands. To improve the information extraction precision of surface features in coastal wetland conservation areas, this paper screens the polarimetric decomposition features using the separability index and classifies fully polarimetric SAR images using the random forest method. The details are as follows. Based on the domestic GF-3 fully polarimetric radar images of the Liaohe River Estuary National Nature Reserve in Liaoning Province, five polarimetric target decomposition methods were used to extract polarimetric features, the separable index was adopted to optimize feature selection, and finally the random forest method was utilized to conduct the classification and accuracy assessment of surface features in the study area. The experiment results show that the classification accuracy of surface features in wetlands based on optimized polarimetric features was up to 75.47%. Meanwhile, the optimized polarimetric feature parameters can effectively avoid information redundancy and improve the information extraction accuracy of surface features in coastal wetland conservation areas.
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2021, Vol. 33 
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