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利用升降轨sentinel-1A提取昆明DEM及其精度分析 被引量:5

Analysis on the precision of Kunming DEM extracted by Sentinel-1A
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摘要 昆明位于低纬度高海拔区域,海拔在2 000 m左右,为了分析利用INSAR技术提取昆明城区的DEM精度。文中利用升降轨模式下的sentinel-1A获取昆明区域DEM,然后通过相关系数值法和均值法分别对升降轨DEM进行数据融合,对两种融合方法得到的DEM进行对比,结果显示前者比后者得到DEM的精度高。再将相干系数法融合得到DEM与SRTM3 DEM在相同区域采用叠加分析的相减法得到高程异差图,最后由检查点法和剖面法分别对高程异差图进行精度分析。结果表明,融合DEM有效的消除雷达叠掩、透视收缩等引起的"空洞"现象,更好显示地面起伏和纹理特征。其高程异差值统计标准差为±29. 50 m,高程异差值的绝对值小于30 m的区域占84. 5%。 Kunming is located at a low latitude and high altitude,with an altitude of about 2000 meters. In order to analyze the DEM accuracy by using INSAR technology in Kunming City,in the paper,DEM was got using descending mode Sentinel-1A,and then the data fusion of DEM was carried out by the correlation coefficient value method and the average method respectively. Comparing the DEM obtained by the two fusion methods,the results showed that the former had higher precision than the latter. Then the coherence coefficient method was combined to obtain the elevation difference map by the subtraction method of DEM and SRTM3 DEM in the same region. Finally,the checkpoint method and the profile method were used to analyze the accuracy of the elevation heterodyne map. Results showed that the fusion of DEM effectively eliminated the " hollow" phenomenon caused by the radar mask stack,the foreshortening and so on,better displaying the surface relief and the texture feature. The statistical standard deviation of the elevation difference was ± 29. 50 m,and the area where the absolute value of the elevation difference was less than 30 m accounted for 84. 5%.
作者 张建柱 麻源源 麻卫峰 Zhang Jianzhu;Ma Yuanyuan;Ma Weifeng(Ningxia Water Resources & Hydropower Survey Design & Research Institute Co.,Ltd.,Yinchuan 750004,China;Faculty of Land Resource Engineering of Kunming University of Science and Technology,Kunming 650093,China;School of Tourism and Geography Science,Yunnan Normal University,Kunming 650000,China)
出处 《矿山测量》 2018年第6期34-40,共7页 Mine Surveying
基金 云南省高校工程研究中心建设计划资助
关键词 sentinel-1A 相关系数值法 均值法 数据融合 高程异差图 sentinel-1 A correlation coefficient method average method data fusion elevation difference diagram
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