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基于决策树的干旱区湿地信息自动提取——以疏勒河流域为例
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  • 英文篇名:The Automatic Extraction of Wetland Information in Arid Zone based on Decision Tree Algorithm——A Case Study in the Shule River Basin
  • 作者:韩忻忆 ; 颉耀文
  • 英文作者:Han Xinyi;Xie Yaowen;College of Earth and Environmental Sciences,Lanzhou University;Academy of Disaster Reduction and Emergency Management Ministry,Beijing Normal University;
  • 关键词:干旱区湿地 ; 决策树 ; 信息提取 ; 遥感分类
  • 英文关键词:Arid zone;;Decision tree;;Information extraction;;Remote sensing classification
  • 中文刊名:YGJS
  • 英文刊名:Remote Sensing Technology and Application
  • 机构:兰州大学资源环境学院;北京师范大学减灾与应急管理研究院;
  • 出版日期:2015-12-15
  • 出版单位:遥感技术与应用
  • 年:2015
  • 期:v.30;No.146
  • 基金:国家基础科学人才培养基金科研训练及科研能力提高项目(J1210065);; 国家自然科学基金项目(41471163)
  • 语种:中文;
  • 页:YGJS201506014
  • 页数:7
  • CN:06
  • ISSN:62-1099/TP
  • 分类号:116-122
摘要
以疏勒河流域为研究区,探讨了干旱区湿地的遥感影像自动提取方法。以Landsat 8卫星影像数据为主要数据源并辅以数字高程模型(DEM),利用改进的干旱区湿地指数(MAZWI)、归一化植被指数(NDVI)、地表反照率(Albedo)、灰度共生矩阵(GLCM)的非相似性分量等识别指数构建决策树模型,对研究区湿地进行提取,并将结果与最大似然分类结果进行对比。结果表明:该方法在一定程度上提高了湿地提取的精度,与最大似然分类结果相比总体精度和Kappa系数分别提高了6.52%和0.124。证明决策树法是干旱区水域湿地自动提取的一种有效手段。
        Selecting the Shule River Basin which locates in the west of Gansu Province as the study area,the automated extraction method for wetlands in arid regions was discussed.Using the Landsat 8satellite images as the data sources,supported by the digital elevation model(DEM),the modified arid zone wetlands index(MAZWI),the normalized difference vegetation indices(NDVI)and the surface albedo,and the identification of dissimilarity index of the gray level co-occurrence matrix(GLCM),were used as the indicators to establish the decision tree model and the wetlands were extracted.Comparing with the results obtaining by the maximum likelihood supervised classification,it showed that the decision tree method based on the indices can improve the overall accuracy by 6.52%and the overall kappa coefficient by 0.1243.The results of this study suggested that the decision tree method based on indices is an effective tool for wetlands classification in arid zone.
引文
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