Information about forest structures is becoming crucial to earth's global carbon cycle, forest habitats, and biodiversity. The Global Ecosystem Dynamics Investigation (GEDI) provides 25-m diameter footprints of the surface for 3-D structure measurements. The main goal of this study is to compare 12 031 footprints of GEDI data with other airborne and spaceborne digital elevation models (DEMs) for Southwest Spain. Ground elevation differences [elevation of the lowest mode (ELM)] are analyzed by comparing GEDI measurements with airborne laser scanning (ALS) LiDAR- and TanDEM-X-derived DEMs. The vertical structure (RH100) is compared to the ALS LiDAR measurement. Ten zones are analyzed, considering different degrees of coverage and slopes. We achieved a root mean square error (RMSE) of 6.13 m for the ELM when comparing GEDI and LiDAR data and an RMSE of 7.14 m when comparing GEDI and TanDEM-X data. For some of the studied areas, these values were considerably smaller, with RMSE values even lower than 1 m. For the RH100 metric, an RMSE of 3.56 m was achieved when comparing GEDI and LiDAR data, but again with a minimum value of 2.09 m for one zone. The results show a clear relation to coverage and slope, especially for the latter. This work also evaluates the positional uncertainty of GEDI footprints, shifting them ±10 and ±5 m along and across the track of the satellite orbit and their intermediate angular positions. The outcomes reveal a strong tendency to obtain better results in the ELM when setting the footprint to 270° and displacing it within 10 m of its positional uncertainty in comparison with the LiDAR and TanDEM-X data.

中文翻译：

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GEDI 高程精度评估：西班牙西南部案例研究


有关森林结构的信息对于地球的全球碳循环、森林栖息地和生物多样性变得至关重要。全球生态系统动力学调查 (GEDI) 提供直径 25 米的表面足迹，用于 3D 结构测量。本研究的主要目标是将 GEDI 数据的 12 031 个足迹与西班牙西南部的其他机载和星载数字高程模型 (DEM) 进行比较。通过将 GEDI 测量值与机载激光扫描 (ALS) LiDAR 和 TanDEM-X 衍生的 DEM 进行比较，分析地面高程差异 [最低模式 (ELM) 的高程]。将垂直结构 (RH100) 与 ALS LiDAR 测量进行比较。考虑不同的覆盖程度和坡度，分析了十个区域。在比较 GEDI 和 LiDAR 数据时，我们获得的 ELM 均方根误差 (RMSE) 为 6.13 m；在比较 GEDI 和 TanDEM-X 数据时，我们获得的 RMSE 为 7.14 m。对于一些研究区域，这些值要小得多，RMSE 值甚至低于 1 m。对于 RH100 指标，比较 GEDI 和 LiDAR 数据时获得的 RMSE 为 3.56 m，但一个区域的最小值为 2.09 m。结果表明覆盖率和坡度之间存在明显的关系，尤其是后者。这项工作还评估了 GEDI 足迹的位置不确定性，将其沿着卫星轨道及其中间角位置移动 ±10 和 ±5 m。结果表明，与 LiDAR 和 TanDEM-X 数据相比，当将足迹设置为 270° 并将其位移在其位置不确定性的 10 m 范围内时，ELM 中获得更好结果的强烈趋势。