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《Science of Surveying and Mapping》 2014-01
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Vegetation classification technology of hyperspectral remote sensing based on decision tree tool

HE Cheng;Dong Zhi-hai;ZHANG Si-yu;FENG Zhong-ke;GUO Xiao-xiao;Nanjing Forest Police College;Institute of GIS RS & GPS,Beijing Forestry University;Beijing Institute of Surveying and Mapping;  
In order to express the macroscopic and fuzzy crop planting structure with quantitative,accurate and intuitive description,this paper used the method of integrating the multi-temporal and full-covered MODIS and medium resolution sample TM data,through the human-computer interaction means, which is the combination of analysis of MODIS vegetation indices on the crop growth laws and decision tree classification system.At last,the distribution information of winter wheat,cotton,maize,peanuts,fruit and vegetables which in Heilonggang was extracted successfully.The results showed that the accuracy of classification used by combination of TM images based on decision tree system and MODIS_EVI images could be up to 91.5%,and comparing with traditional image supervised classification results,those of vegetables,wheat,cotton,corn and maize could increase by 13.8%,2.0%,1.3% and 20.5% respectively.
【Fund】: 国家863计划(2009AA12Z327 2008AA121305-4);; 国家科技支撑计划项目(2012BAH34B01);; 北京市自然科学基金项目(09D0297);; 国家自然科学基金(30872038)
【CateGory Index】: Q94-3;TP79
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