摘要
以湖北省松滋市部分区域为研究对象,基于2011年Landsat 5TM、2017年Landsat-8遥感影像和ASTGTM2的DEM数字高程数据,深入探讨研究区两种影像数据的多特征提取,设计基于指数的土地分类试验。结果表明,EBSI、MNDWI、MSAVI、MNDBI等遥感指数的分类精度较高;依据上述遥感指数和DEM特征,生成决策树规则,构建决策树分类模型,得到研究区的土地利用分类结果,决策树分类精度明显高于SVM法和最大似然法,Landsat-8影像分类精度高于Landsat 5TM;2011—2017年部分裸土得到了利用,主要转化为居民用地和生态用地。
Taking part of Songzi city,Hubei province as the research area,multiple feature extraction of remote sensing in research area is discussed based on remote sensing images of Landsat 5TM in 2011 and Landsat-8 in 2017,and DEM digital elevation data of ASTGTM2.Many comparative experiments of land classification based on index have found that the indices such as EBSI,MNDWI,MSAVI,and MNDBI have higher classification accuracy;the decision tree rules are generated based on the remote sensing index and DEM characteristics,the decision tree classification model is constrcted,and the land use classification results in the research area are obtained.The experimental results show that the classification accuracy of decision tree is higher than that of SVM and maximum likelihood,and classification accuracy of Landsat-8 image is higher than Landsat 5TM;some bare soil was maily used to converte into residential land and ecological land from 2011 to 2017.
作者
何朝霞
HE Zhao-xia(Yangtze University College of Technology&Engineering,Jingzhou 434023,Hubei,China)
出处
《湖北农业科学》
2019年第21期176-180,共5页
Hubei Agricultural Sciences
基金
湖北省教育厅2018年度科学研究计划指导性项目(B2018415)
关键词
遥感影像
DEM
决策树
土地利用
精度
remote sensing image
DEM
decision tree
land use
accuracy
