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A method for combining SRTM DEM and ASTER GDEM2 to improve topography estimation in regions without reference data
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2018-06-01 , DOI: 10.1016/j.rse.2018.03.026
Hung T. Pham , Lucy Marshall , Fiona Johnson , Ashish Sharma

Abstract Digital Elevation Models (DEMs) such as Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Models (ASTER GDEM), or Shuttle Radar Topography Mission DEM (SRTM) are widely used in remote areas and non-industrial countries because of their availability rather than their accuracy. Although a global DEM can be considerably enhanced using additional reference information such as higher resolution DEMs or ground truth points, improving accuracy in areas without reference data remains a challenge. This paper develops an approach to improve the accuracy of the estimated topography by combining two complementary DEMs (ASTER GDEM 1 arc-second and SRTM DEM 1 arc-second) in regions missing reference data. The combination approach is based on formulating relationships between slopes and weights in sites with reference data. Then the developed relationships are applied to sites with similar geomorphology to determine the combination weight for each DEM without using reference data. The results indicate that combined DEMs offer significant improvements of 47% and 20% in mean bias over a mountainous site, and 16% and 58% at a low-relief site when compared with the SRTM and ASTER GDEM products, respectively. DEM-derived drainages were also found to be more accurate for the combined DEMs than the near-global DEMs in areas where reference data is not available.

中文翻译:

一种结合 SRTM DEM 和 ASTER GDEM2 以改进无参考数据区域地形估计的方法

摘要 数字高程模型 (DEM),例如先进的星载热发射和反射辐射计全球数字高程模型 (ASTER GDEM) 或航天飞机雷达地形任务 DEM (SRTM),因其可用性而被广泛应用于偏远地区和非工业国家。比他们的准确性。尽管使用其他参考信息(例如更高分辨率的 DEM 或地面实况点)可以显着增强全局 DEM,但在没有参考数据的区域中提高准确性仍然是一个挑战。本文开发了一种通过在缺少参考数据的区域中组合两个互补 DEM(ASTER GDEM 1 弧秒和 SRTM DEM 1 弧秒)来提高估计地形精度的方法。组合方法是基于参考数据制定站点中坡度和权重之间的关系。然后将开发的关系应用于具有相似地貌的站点,以在不使用参考数据的情况下确定每个 DEM 的组合权重。结果表明,与 SRTM 和 ASTER GDEM 产品相比,组合 DEM 在山区站点上的平均偏差分别显着提高了 47% 和 20%,在低地势站点上分别提高了 16% 和 58%。在参考数据不可用的地区,还发现 DEM 衍生的排水对于组合 DEM 比近全球 DEM 更准确。结果表明,与 SRTM 和 ASTER GDEM 产品相比,组合 DEM 在山区站点上的平均偏差分别显着提高了 47% 和 20%,在低地势站点上分别提高了 16% 和 58%。在参考数据不可用的地区,还发现 DEM 衍生的排水对于组合 DEM 比近全球 DEM 更准确。结果表明,与 SRTM 和 ASTER GDEM 产品相比,组合 DEM 在山区站点上的平均偏差分别显着提高了 47% 和 20%,在低地势站点上分别提高了 16% 和 58%。在参考数据不可用的地区,还发现 DEM 衍生的排水对于组合 DEM 比近全球 DEM 更准确。
更新日期:2018-06-01
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