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LAND COVER CLASSIFICATION OF FINNISH LAPLAND USING DECISION TREE CLASSIFICATION ALGORITHM

机译:基于决策树分类算法的芬兰拉普兰土地覆被分类

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Land cover of Finnish Lapland was classified to 16 land cover classes using optical IRS LISS, Spot XS and MODIS satellite images, ancillary GIS data and decision tree classifier. The aim of this study was to test decision tree classifier for land cover classification and study the effects of its parameters to classification result. In the best case, the overall accuracy was about 68% for all 16 classes when individual images were classified. The overall accuracy was only about 45% when whole mosaic was classified. It seems that the most problematic classes are those with vegetation but which are not forest.
机译:使用光学IRS LISS,Spot XS和MODIS卫星图像,辅助GIS数据和决策树分类器,将芬兰拉普兰的土地覆盖物分为16种土地覆盖物类别。这项研究的目的是测试用于土地覆盖分类的决策树分类器,并研究其参数对分类结果的影响。在最佳情况下,对单个图像进行分类时,所有16个类别的总体准确度约为68%。当对整个镶嵌图进行分类时,总体精度仅为大约45%。似乎最有问题的类别是那些有植被但不是森林的类别。

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