摘要
以甘肃玛曲县为研究区,以区域湿地遥感信息提取为目标,采用TM多光谱数据和DEM数据,利用归一化植被指数和主成分分析得到的第一主成分作为分类特征,通过对数据的空间特征、波谱特征与统计结果的对比分析,构建湿地信息提取决策树模型,并与非监督分类法、最大似然法相比较,表明基于多特征决策树分类法能够用于湿地专题信息的提取,在研究区有较好的适用性。
This study is focused on the extraction of information concerning regional wetland based on Remote Sensing Multi -spectral Thematic Mapper data in the study area of Maqu Country, Gansu Province. For this purpose, local Digital Elevation Model, Normalized Difference Vegetation Index, and the first principal component extracted from principal components analysis were taken as the main factors of classification. A decision tree model was built based on these factors through spatial, spectral and statistic analysis for extracting wetland information. A comparison between the output of this model and that of unsupervised classification or maximum likelihood classification indicates that the multi - feature decision tree classification can be applied to the extraction of wetland information and that this classification is quite suitable for the study area.
出处
《国土资源遥感》
CSCD
2009年第4期96-100,共5页
Remote Sensing for Land & Resources
基金
国家自然科学基金项目(编号:30700100)
国家教育部社科项目(编号:06JC790020)
国家博士点基金项目(编号:20070740031)
甘肃省"十一五"科技支撑项目(编号:0708NKCA121)
国家863项目(编号:2007AA10Z232)共同资助
关键词
湿地
决策树分类
光谱分析
湿地提取
精度
Wetlands
Decision tree classification
Spectroscopy
Wetlands extraction
Accuracy