基于RS的冬小麦种植面积提取及最佳时相选择  

Extraction of Winter Wheat Planting Areas and Selection of Optimal Time Phase Based on Remote Sensing

作　　者：冯美臣[1] 杨武德[1] 

机构地区：[1]山西农业大学农学院,山西太谷030801

出　　处：《山西农业大学学报（自然科学版）》2010年第6期487-490,共4页Journal of Shanxi Agricultural University(Natural Science Edition)

基　　金：山西省科技攻关项目(2006031114);山西省气象局开放式研究基金项目(SX053001);山西农业大学科研启动基金(XB2009016)

摘　　要：为探求冬小麦种植面积提取的方法,本研究通过多种图像处理方法对TM数据进行处理,结合实地调查和研究区主要种植作物的物候历,利用TM数据提取了冬小麦的种植面积。同时为了提高解译精度,结合GIS进行了两次目视解译过程,消除了分类器分类会出现的多分和漏分现象。结果表明:通过分类后计算混淆矩阵与地面真实感兴趣区(ROI)进行比较,发现Mahalanobis Distance分类法阈值(最大误差距离)为2.9时分类效果最佳。得到2007年研究区域冬小麦遥感监测面积为560 650 hm2,提取精度达到了95.23%。三个地区以临汾地区提取精度最高,而晋中地区最低。因此利用该方法提取冬小麦种植面积是可行的。In order to seek the planting area extraction method of winter wheat,TM data were analyzed using various methods and planting areas of winter wheat were extracted by TM data with combination of the field survey and phenology of main crops in the research regions.For a fraction of leakage and spillage after image classification,the planting area vectograph produced by classification was superimposed by TM remote sensing image in ArcGIS through second visual interpretation to produce area vectograph ultimately.By comparison between confusion matrix calculated after classified and ground RIO,the classification effect was found to be the best when the threshold value of Mahalanobis Distance classification was 2.9.Remote sensing areas of winter wheat in the research regions in 2007 was 560 650 hm2 and the extraction degree of accuracy was as high as 95.23%.The extraction accuracy degree of Linfen was highest,and Jingzhong was lowest.So it was feasible to extract the planting area of winter wheat using the method.

关 键 词：冬小麦 遥感 最佳时相 面积提取 

分 类 号：S512[农业科学—作物学] S127