A Spatial-Distance Analysis Approach of Multi-Spectrum Feature Distribution for Remote Sensing Image Land Use/Cover
LIN Jian1,2,TAN Yong-hong2,YANG Yue-long2,PENG Shun-xi3,LIU Jian-xun1
1. Laboratory of Knowledge Grid, Hunan University of Science & Technology, Xiangtan 411201, China 2. Department of GIS, Hunan University of Science & Technology, Xiangtan 411201, China 3. School of Info-Physics and Geomatics Engineering, Central South University, Changsha 410083, China
Abstract：Aiming at the problem that a convenient multivariate statistical model is in general not available for the multi-spectrum feature of land use/cover(LUC)class in remote sensing (RS) image, because the class is made of multiple covered species, a spatial-distance analysis approach of multi-spectrum feature distribution for RS image LUC is present, with the mean vector of samples as LUC class center, with max-min clustering algorithm forming the class multi-clustering-centers, the spatial-distances from the class center to these multi-clustering-centers were calculated. With the distance as abscissa and the percentage of the clustering-center pixels to the whole sample pixels as ordinate, the intra- and inter-classes distance distribution charts were constructed to analyze the multi-spectrum feature distribution of RS image LUC. The results of these samples classification tally with the conclusions of spatial distance analysis, indicating that this approach is feasible. In this approach the multi-dimensional spectrum information is turned into one dimensional distance information, the spatial-distance calculation and clustering threshold confirmation are realized easily, and the multi-spectrum feature of LUC class is clear, so it is a better approach to solving the multivariate distributing problem of multi-spectrum feature.
林剑1,2,谭勇鸿2,阳岳龙2,彭顺喜3,刘建勋1 . 遥感图像土地利用/覆盖多光谱特征分布空间距离分析方法[J]. 光谱学与光谱分析, 2009, 29(02): 436-440.
LIN Jian1,2,TAN Yong-hong2,YANG Yue-long2,PENG Shun-xi3,LIU Jian-xun1. A Spatial-Distance Analysis Approach of Multi-Spectrum Feature Distribution for Remote Sensing Image Land Use/Cover. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2009, 29(02): 436-440.
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