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《Geography and Geo-Information Science》 2010-06
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Research on Salinity Inversion from Remote Sensing of Saline Soil Based on BP Neural Network

FAN Yan-guo,HOU Chun-ling,ZHU Hao,WU Teng-teng,SUN Yuan-fang(College of Geo-Resource and Information,China University of Petroleum,Qingdao 266555,China)  
The research on salinity inversion from remote sensing with the measured spectral data and salinity data has been done using remote sensing technology and BP neural network technology.The model was designed and implemented by programming.The forecast accuracy of BP neural network model is 62.5%,better than statistical model.The experiment confirms that BP neural network can simulate the relationship between soil salinity and spectral data,which shows that it is feasible to use this method in salinity inversion from remote sensing.
【Fund】: 山东省科技攻关项目(2008GG10009018);山东省科技计划项目(J08LD55)
【CateGory Index】: S156.4;S127
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