煤炭工程 ›› 2014, Vol. 46 ›› Issue (9): 120-122.doi: 10.11799/ce201409039

• 研究探讨 • 上一篇    下一篇

基于分区决策树的乌达煤田土地覆被分类研究

刘文龙1,李峰2   

  1. 1. 北京工业职业技术学院
    2. 中国矿业大学(北京)
  • 收稿日期:2014-05-07 修回日期:2014-07-31 出版日期:2014-09-10 发布日期:2014-09-10
  • 通讯作者: 刘文龙 E-mail:lwlcumt@126.com

Land Cover Classification Reasearch of Wuda Coalfield Based on Subregion Decision Tree

  • Received:2014-05-07 Revised:2014-07-31 Online:2014-09-10 Published:2014-09-10

摘要:

煤火灾害会对自然地貌、生态和环境造成严重的负面影响。土地覆被的变化可以反映出煤火灾害对周边生态环境所带来的危害。精确的土地覆被分类结果是研究煤田火区生态环境变化的基础。本文基于Landsat8卫星遥感数据,以乌达煤田为区为研究区,依据该区地形特征、地物主体类型以及地势地形将其分为五个子区,分别分析五个区的NDVI、NDBI、NDWI、高程、坡度及光谱特征值,构建不同的决策树实现土地覆被分类。分类结果表明,基于决策树法的分区分类方法总体分类精度为87.63%,Kappa系数为0.86。与传统决策树分类法相比,总体分类精度提高了14.75%,Kappa系数增加了0.17,其准确性有了较大的提高。

关键词: 乌达煤田, 分区, 决策树, 土地覆被分类

Abstract:

Coal fire disaster would have a serious negative impact on the natural landscape, ecology and the environment. Land cover change could evaluate the damages to the surrounding environment caused by coal fire disaster. Accurate results from land cover classification is the basis of ecological changes in coalfield fire area. This paper studied the method of land cover classification of Wuda coalfield using Landsat8 data. According to the landform features, surface features and topography features, Wuda coalfield was divided into five sub-regions. Based on the actual situation of different areas, different decision trees were constructed by the NDVI, NDBI, NDWI, altitude, slope, and spectral characteristics. The results showed that the classification method of sub-region decision tress leads to a high overall accuracy up to 87.63% and Kappa Coefficient was 0.86. Compared with the traditional decision tree classification, overall accuracy of our method was increased by 14.75%, and Kappa coefficient was increased by 0.17.

Key words: Wuda coalfield, subregion, decision tree, land cover classification