文献类型：期刊文献

中文题名：基于决策树的高寒湿地类型遥感分类方法研究

英文题名：Study on Highland Wetlands Remote Sensing Classification Based on Decision Tree Algorithm

作者：邹文涛[1] 张怀清[1] 鞠洪波[1] 刘华[1]

机构：[1]中国林业科学研究院资源信息研究所

年份：2011

卷号：24

期号：4

起止页码：464-469

中文期刊名：林业科学研究

外文期刊名：Forest Research

收录：CSTPCD;;Scopus;北大核心:【北大核心2008】；CSCD:【CSCD2011_2012】；

基金：中央级公益性科研院所基本科研业务费专项资金"气候变化背景下的三江源典型区湿地变化研究(IFRIT200906)";国家"十一五"科技支撑重点项目课题"综合监测技术体系集成与应用示范(2006BAD23B06)"

语种：中文

中文关键词：三江源高寒湿地;决策树分类;NDWI;缨帽变换

外文关键词：highland wetlands; decision tree; NDWI; tasseled cap transformation

分类号：S771.8

摘要：以索加-曲麻河区域为例,探讨了三江源区域高寒湿地遥感分类方法。利用TM影像数据和DEM及缨帽变换后的亮度、绿度、湿度,以及归一化水体指数(NDWI)等复合识别指标,构建决策树模型,对研究区不同地类进行区分。然后通过与传统的最大似然法监督分类所得到的结果进行对比,结果表明:利用基于指数的决策树分类方法对高寒湿地类型进行分类,较传统的最大似然法监督分类总体精度提高12.05%;总体kappa系数提高0.140 7;对于河流、湖泊、沼泽、滩地等湿地类型,生产者精度和用户精度分别提高了6.06%,6.25%;0.12%,3.13%;6.99%,25.00%;6.12%,28.13%,比监督分类均有明显的提高。证明基于指数的决策树分类方法是高寒区域湿地遥感分类的一种有效手段。
Suojia-Qumahe Nature Reserve,which locates in the source region of Three Rivers（Yangtze River,Yellow River and Lancang River）,was taken as the research field to discuss the proper method for remote sensing classification of highland wetlands.The TM images,DEM,NDWI（Normalized Difference Water Indices） and the brightness,greenness and humidity after the tasseled cap transformation were used as the indicators to establish the decision tree model to distinguish the different wetlands and other land cover types.The authors compared the results with the traditional maximum likelihood supervised classification,it showed that the decision tree method based on the indices can improve the overall accuracy by 12.05%,and the overall kappa coefficient by 0.140 7.For rivers,lakes,swamps and floodplains,the producer＇s accuracy and user＇s accuracy increased by 6.06%,6.25%;0.12%,3.13%;6.99%,25.00% and 6.12%,28.13% respectively.The results of this study suggest that the decision tree method based on indices is an effective tool for wetlands remote sensing classification in highland area.