基于新疆和田地区1994年10月9日和10日SIR-C-L波段全极化雷达数据。首先对极化干涉测量的基本原理和数据处理流程进行了详细的阐述，接着，用Cloude相干最优算法得到了与3种地物散射机制相对应的3个最优相干图。并且就地物相干性对极化的强烈依赖和3种散射机制中地物的最优相干特性进行了分析，具有最高相干值的相位图在提取DEM方面较有利，具有最低相干值的相干图在地物识别方面较有利。最后，在对最优相干系数。后向散射系数和熵进行数据相关性分析基础上，利用得到的最优相干系数，熵和后向散射系数数据进行了土地类型的识别和分类，得到了很好的效果。

Based on the SIR-C L-band fully polarimetric SAR data of hotan area of Xinjiang Province,on October 9 and 10, in 1994,first,the basic principles of polarimetric SAR interferometiy measurement and data processing scheme are de-tailedly discussed. Then, three optimized coherence map related to three scattering mechanism are obtained by Cloude optimization algorithm. Furthermore, the strong dependency of interferometric coherence on the polarization and the coherence signatures of land cover related to three scattering mechanism are analysied, the inferometric phase corresponding to highest coherence map is useful in DEM extraction, the lowest coherence map is useful in identification of land cover. At last, based on the data correlation analysis of optimized coherence coefficient, backscattering coefficient and polarimetric entropy, making use of optimized coherence, polarimetric entropy and backscattering coefficient data, Identification and classification of land cover is implemented and evaluated. The good result is obtained.