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作 者:查力[1,2] 宫辉力[1,2,3,4] 胡卓玮[1,2,3,4] 杜红悦
机构地区:[1]首都师范大学资源环境与旅游学院 [2]三维信息获取与应用教育部重点实验室 [3]资源环境与地理信息系统北京市重点实验室 [4]北京市城市环境过程与数字模拟国家重点实验室培育基地,北京100048
出 处:《首都师范大学学报(自然科学版)》2015年第4期85-89,共5页Journal of Capital Normal University:Natural Science Edition
基 金:国家科技支撑计划课题--天基遥感数据获取与处理系统研发(2012BAH27B00)
摘 要:针对天绘一号卫星高分辨率影像,采用面向对象分类方法对怀柔水库区域进行水体信息提取,在多尺度分割的基础上,统计地物的光谱信息、形状因子和亮度均值等,建立水体信息的特征集,充分利用高分辨率的特点提取水体信息,同时选取了参数相近的SPOT和Rapid Eye两幅国外高分影像进行对比研究,使用相同方法进行水体提取,对实验过程和结果进行了对比分析.针对提取结果,采用野外采样和矢量图分析两种方法综合进行精度评价.实验制定了适用于天绘影像的水体提取的方法和规则,分析不同因素对分割与分类结果的影响,同时,我们比较了天绘影像与国外同级别高分影像的优劣性,为天绘影像的进一步应用提供了参考.Mapping Satellite-1 is China's first transmission-type stereo mapping satelliteapplied for both military and civilian,it is carrying with high resolution panchromatic sensor( resolution 2m) and 4-band multi-spectral sensor( resolution 10m).Based on Mapping Satellite-1 highresolution imagery,we choose HuairouReservoir( Beijing) as the experimental zone.Object-oriented information extraction technology was used to extract water bodies,based on the result of multi-resolution segmentation,we count spectrum,appearance factor and brightnessof features,after analysis and observation,thenbuild rules of water bodies for Mapping Satellite-1image to extract water bodies.For comparative research,we also select 2 same level foreign satellite( SPOT and Rapid Eye) images as comparative data,use the same method to extract water bodies,find and analysis the difference inboth experimentprocess and results amongthree images.Finally,we went to the experimental field select samples in June 2006,then analyze the vector map to access accuracy about the extraction results,Compare to the others,overall accuracy of Mapping Satellite-1 Imagery get better performance in the water extraction,but its details is a little fuzzy in the segmentation,and its main error is misidentification from wetland to water.Generally speaking,the study formulated water extraction method and rules adapted to Mapping Satellite-1 image,and analysis influence of differentfactors for the images' segmentation and classification.
分 类 号:P208[天文地球—地图制图学与地理信息工程]
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