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《Acta Pedologica Sinica》 2007-05
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Chen Jie1 Sun Zhiying1,2 Tan Manzhi1,2(1 State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing 210008,China)(2 Graduate School of the Chinese Academy of Sciences,Beijing 100039,China)  
Application of remote sensing data in landuse classification often comes cross some difficulties and problems that originate from various types of uncertainty associated with image information extraction and ambiguity of the linguistic rules involved in the context information concerning dependency between features and landuse.Fuzzy classification system,as one of the most powerful soft classifiers,is capable of incorporating inaccurate sensor measurements,vague class descriptions and imprecise modeling in the analysis process,and outputting classification results that better demonstrate the limitation of human knowledge and the real world.Therefore,fuzzy classification is considered as a better method in landuse mapping based on remote sensing data.In this paper,a case study of the periurban Nanjing was carried out to extract landuse information by means of the supervised fuzzy classification,based on object-oriented segmentation and the resultant so-called image object information of not only spectral values,but also feature space using shape and topological features.Results indicte that fuzzy classification of landuse based on remote sensing data could achieve a more reasonable and meaningful result,in comparison with conventional rigid methods.
【Fund】: 国家自然科学基金项目(40571065);; 中国科学院知识创新工程重要方向项目(KZCX3-SW-427)资助
【CateGory Index】: F301;F224;P237
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