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Estimation of vertical accuracy of Digital Elevation Models over complex terrains of Indian subcontinent

机译:印度次大陆复杂地形上的数字高程模型垂直精度的估计

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Complex terrains (mountains) of varying elevations cover approximately 25% of the total global land area wherein nearly 26% of the world's population resides. Complex terrains offer difficulty in accurate owing to their inaccessibility and location constraint to carry out ground based survey. Digital Elevation Model (DEM) offers a reliable alternative to study the orography from remote sensing measurements. Mountainous surfaces and dense vegetation covers offer large DEM errors as compared to flat terrains owing to the terrain characteristics. The reliability of DEMs for watershed modeling is often hinged on their vertical accuracies. In the present study, the vertical accuracies of three DEM from three sources namely, Shuttle Radar Topography Mission (SRTM), Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) and CARTOSAT are examined over the complex terrains of the Indian subcontinent. The spatial variability using geostatistics is assessed over 440 triangulated benchmark stations procured from the Survey of India Department toposheets. It is observed that the RMS error for SRTM DEM is less as compared to the other sources. The value of mean error increases continuously with the rise in the elevation showing the effect of terrain morphology on the accuracy of the DEM. The mean error for ASTER, SRTM and Cartosat is 42.75 m, 36.84 m and 37 m respectively. SRTM DEM shows better results for the morphometric analysis by generating large drainage networks over Upper Bhima Basin. For the future these results can be highly useful in various hydrological modeling over the different river basins.
机译:不同海拔高度的复杂地形(山脉)覆盖了全球总土地面积的25%,其中近26%的世界人口居住在该地区。复杂的地形由于其难以接近和位​​置限制而难以进行地面测量,因此很难提供准确的测量结果。数字高程模型(DEM)提供了一种可靠的替代方案,可以通过遥感测量研究地形学。由于地形特征,与平坦的地形相比,多山的表面和茂密的植被覆盖提供了较大的DEM误差。用于分水岭建模的DEM的可靠性通常取决于其垂直精度。在本研究中,在印度次大陆的复杂地形上,研究了来自三个来源的三个DEM的垂直精度,即航天飞机雷达地形任务(SRTM),先进的星载热发射和反射辐射计(ASTER)和CARTOSAT。使用地统计法对空间变异性进行了评估,该评估是从印度调查局的地形表中获得的440个三角基准站进行的。可以看出,与其他信号源相比,SRTM DEM的RMS误差要小。平均误差值随着海拔的升高而连续增加,这表明地形形态对DEM精度的影响。 ASTER,SRTM和Cartosat的平均误差分别为42.75 m,36.84 m和37 m。 SRTM DEM通过在上比哈马盆地上空建立大型排水网络,显示出更好的形态分析结果。将来,这些结果在不同流域的各种水文模拟中将非常有用。

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