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基于决策树的高寒湿地类型遥感分类方法研究
引用本文:邹文涛,张怀清,鞠洪波,刘华.基于决策树的高寒湿地类型遥感分类方法研究[J].林业科学研究,2011,24(4):464-469.
作者姓名:邹文涛  张怀清  鞠洪波  刘华
作者单位:中国林业科学研究院资源信息研究所,北京,100091
基金项目: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)"
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。

关 键 词:三江源高寒湿地  决策树分类  NDWI  缨帽变换
收稿时间:2010/11/11 0:00:00

Study on Highland Wetlands Remote Sensing Classification Based on Decision Tree Algorithm
ZOU Wen-tao,ZHANG Huai-qing,JU Hong-bo and LIU Hua.Study on Highland Wetlands Remote Sensing Classification Based on Decision Tree Algorithm[J].Forest Research,2011,24(4):464-469.
Authors:ZOU Wen-tao  ZHANG Huai-qing  JU Hong-bo and LIU Hua
Institution:Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China;Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China;Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China;Research Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
Abstract: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....
Keywords:highland wetlands  decision tree  NDWI  tasseled cap transformation
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