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Decision Tree Classification of Remote Sensing Image in Mountain Areas Supported by GIS
Author(s): YOU Hao-chen, XU Zhang-hua, LIU Jian, YU Kun-yong, ZHANG Xin-zhu
Pages: 34-
40,45
Year: 2011
Issue:
1
Journal: Journal of Beijing Union University(Natural Sciences)
Abstract: 以福建省顺昌县为研究区,首先利用光谱、纹理等信息对森林进行初分类;在此基础上,分析各森林类型在不同地形条件下的混淆情况,借助GIS手段,建立再分类规则,实现森林分类精度的提高.从分类总精度看,再分类结果较初分类结果高出9.11%,而Kappa系数则高出0.134 8,说明GIS支持下的决策树分类可较大幅度地提高南方山地丘陵区域的森林分类精度,具有良好的应用前景.
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