基于单时相MODIS数据的决策树自动构建及分类研究
Automated Construction and Classification of Decision Tree Classifier Based on Single-Temporal MODIS Data
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摘要: 以甘肃省为试验区,利用单时相MODIS数据的光谱信息,使用最大似然法和基于See 5.0数据挖掘的决策树分类方法,进行了分类对比研究。分类结果表明,加入温度-植被角度TVA和温度-植被距离TVD两个指数后,低植被覆盖区的分类效果得到了改善;基于See 5.0数据挖掘的决策树方法能够快速地建立决策树,且能提高较难识别地物类型的分类精度。Abstract: With single-temporal MODIS data of Gansu Province,we used a maximum likelihood method and decision tree methed based on data mining software See 5.0 to stuly the land cover classification.The experimental result shows that the accuracy of low vegetation area is improved with the indexes of TVA and TVD,compared with Maximum likelihood classfier,and data mining software See 5.0 is able to build decision tree quickly and improve the precision of miscible classes.
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