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该文对应用高程、坡向及土壤等辅助信息提高分类精度进行了研究 .在GIS支持下 ,运用GIS的空间分析技术综合研究高程、坡向等辅助信息与植被类型的内在关系 ,运用模糊数学的基本原理将这种内在关系量化 ,形成可以反映植被与辅助信息间规律的模糊矩阵 ,综合应用所得到的模糊矩阵通过后分类法来修正无监、有监分类得到的初分类图像 .该研究以贺兰山中段汝箕沟一带为研究对象 ,成功地应用该方法得到了研究区的植被分类图像 .研究表明 ,三维及相关辅助信息可以有效地提高遥感图像的分类精度
In this paper, the classification accuracy is improved by using the auxiliary information such as elevation, aspect and soil.Under the support of GIS, GIS spatial analysis technology is used to comprehensively study the relationship between the auxiliary information such as elevation and aspect and the vegetation type. By using fuzzy mathematics The basic principle of this method is to quantize this internal relationship to form a fuzzy matrix that can reflect the regularity between vegetation and auxiliary information and to apply the resulting fuzzy matrix to correct the initial classification images obtained by unsupervised and supervised classification by using the post classification method. With the study of Rujigou area in the middle section of Helan Mountain, this method has been successfully applied to get the vegetation classification images of the study area.The research shows that the three-dimensional and related auxiliary information can effectively improve the classification accuracy of remote sensing images