摘要
ERS 1 WSC data were obtained by international cooperation. The distributive characteristics of radar backscattering coefficient image of China land surface are analyzed and the research results are presented. The capability of ERS 1 WSC data for monitoring land surfaces is investigated. The results show that the radar backscattering coefficient images can reveal the natural landform features of China land. Using the WSC data can discriminate six types of major land coverage, including evergreen vegetation and snow covered region, vegetation and crops, mountains, grassland, desert and grassland, desert. On the whole, the radar backscattering coefficient image of China land is the synthesis of the vegetation map and terrain map. Statistical study of the typical terrain shows that the radar backscatter coefficients of China land range from -29 dB to -5 dB. The lowest value corresponds to the deserts of Badain Jaran, Takla Makan, and Tengger. The highest value corresponds to snow covered regions of Himalaya Mountains and Tianshan Mountains.
ERS 1 WSC data were obtained by international cooperation. The distributive characteristics of radar backscattering coefficient image of China land surface are analyzed and the research results are presented. The capability of ERS 1 WSC data for monitoring land surfaces is investigated. The results show that the radar backscattering coefficient images can reveal the natural landform features of China land. Using the WSC data can discriminate six types of major land coverage, including evergreen vegetation and snow covered region, vegetation and crops, mountains, grassland, desert and grassland, desert. On the whole, the radar backscattering coefficient image of China land is the synthesis of the vegetation map and terrain map. Statistical study of the typical terrain shows that the radar backscatter coefficients of China land range from -29 dB to -5 dB. The lowest value corresponds to the deserts of Badain Jaran, Takla Makan, and Tengger. The highest value corresponds to snow covered regions of Himalaya Mountains and Tianshan Mountains.
基金
TheauthorsthanktheESAforprovidingtheERS_1WSCdatabyProjectA0 2
