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《Geography and Geo-Information Science》 2003-02
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An Improved Method of Spectral Unmixing of Remote Sensing Image and Its Application in Water Pollution Monitoring and Assessing

QIAN Shao-meng1, LIN Qi-zhong1, CHEN Xue2(1.Institute of Remote Sensing Applications, The Chinese Academy of Sciences, Beijing 100101;2.The Research Center for Remote Sensing and GIS,Beijing Normal University,Beijing 100875,China)  
The spectral signal of a pixel in remotely sensed image in most cases is the result of the reflected spectral properties of mixed land cover types constituting the pixel. However, most remotely sensed image classification algorithms aim at sorting a pixel according to its spectral statistic feature. Spectral unmixing can not only give the abundance images of surface cover types constituting the pixel, but also get the classification image. This paper introduced an improved method of spectral unmixing of remote sensing image and its application in water pollution monitoring and assessing. A TM image of the Dianchi Lake received on October 4,2001 was processed and analyzed as the following: (1) Atmospheric calibration of the image data, (2) Extracting the water area from other land cover types, (3)Definiting the unpolluted water area and calculating the average spectral value of all selected pixels,(4) Subtracting the average value from all pixels, (5) Selection of the endmembers representing different water pollution types, (6) Spectral unmixing of the image data by the linear model, (7) Getting the abundance image of every endmember constituting the pixel, and the classification image. By the classification image,the distribution of each type of water pollution in the Dianchi Lake was showed. Moreover, the factors affecting the classification product were discussed and some research aspects for the future were put forward.
【Fund】: 十五"国家科技攻关项目"滇池蓝藻水华污染控制技术研究"子课题"滇池水华污染遥感监测与水域生态环境管理信息系统
【CateGory Index】: X832
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