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ANALYSIS OF DEM COMBINATION METHODS USING HIGH RESOLUTION OPTICAL STEREO IMAGERY AND INTERFEROMETRIC SAR DATA

机译:使用高分辨率光学立体图像和干涉式SAR数据分析DEM组合方法

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Digital elevation models (DEM) from satellite data are generated mainly from two types of datasets using completely different methods: photogrammetry for optical stereo images (e.g. SPOT5, CARTOSAT) and interferometry for Synthetic Aperture Radar data (InSAR, e.g. ERS-Tandem, SRTM). Both generation methods show advantages and disadvantages but have similar accuracy values in comparison to a reference DEM. The paper aims at showing the potential for combined usage of several DEM (derived with different sensors and methods) to provide a "gap-less" DEM and improve the overall accuracy. Some results are given for three combination methods: DEM fusion utilizing height error maps for each DEM; DEM integration, where single point information from another DEM is inserted during the triangulation process; and the delta surface fill method. The quality of the DEM derived from one source and of the combined DEM depends on the steepness of the terrain and on the land cover type. For flat terrain or moderate hilly landscapes, a height accuracy in the order of 5 meters (RMSE) or better can be achieved for the mentioned sensors. Two test areas are chosen, where many different data sets are available and much knowledge exists from previous studies. The first test area is a region in the south-eastern part of Bavaria comprising a mostly hilly, post-glacial landscape. The second test area is located in Catalonia, Spain including also a mostly hilly terrain with some steep slopes. The received DEM are compared qualitatively and quantitatively to the reference DEM with superior quality by looking at profiles and statistics. The results show an improvement of the combined DEM that can be quantitatively measured. Although overall statistics for larger regions show only a slight improvement, local errors and blunders are reduced significantly and the overall accuracy of the combined DEM is higher.
机译:来自卫星数据的数字高度模型(DEM)主要由使用完全不同的方法的两种类型的数据集产生:光学立体图像的摄影测量(例如,Spot5,Cartosat)和合成孔径雷达数据的干涉测量(Insar,例如ERS-Tandem,SRTM) 。两种生成方法都显示出优点和缺点,但与参考DEM相比具有相似的精度值。本文旨在显示多个DEM的组合使用潜力(衍生在不同的传感器和方法),以提供“较少”的DEM,提高整体精度。一些结果是三种组合方法:DEM Fusion利用每个DEM的高度错误映射; DEM集成,其中在三角测量过程中插入来自另一个DEM的单点信息;和达达表面填充方法。来自一个来源和组合DEM的DEM的质量取决于地形的陡峭和陆地覆盖类型。对于平坦的地形或适度的丘陵景观,可以为上述传感器实现5米(RMSE)或更好的高度精度。选择两个测试区,其中许多不同的数据集可用,并且来自以前的研究存在许多知识。第一个测试区是巴伐利亚东南部的一个地区,包括大多数丘陵,冰川后景观。第二个测试区位于西班牙加泰罗尼亚,包括一些陡峭的地形,有一些陡峭的斜坡。通过观察配置文件和统计,定性地和定量地与参考DEM定量和定量进行比较。结果表明可以在可以定量测量的组合DEM的改进。虽然较大地区的整体统计数据仅略有改善,但局部误差和漏洞显着降低,组合DEM的整体精度更高。

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