GEDTM30: global ensemble digital terrain model at 30 m and derived multiscale terrain variables

作者：Yu-Feng Ho, Carlos Henrique Grohmann, John B. Lindsay, Hannes Isaak Reuter, Leandro Parente, Martijn Witjes, Tomislav Hengl · 发表于：PeerJ · 年份：2025 · DOI：10.7717/peerj.19673 · 被引用次数：19 · 研究领域：Hydrology and Watershed Management Studies、Cryospheric studies and observations、Soil erosion and sediment transport

Production and validation of an open global ensemble digital terrain model (GEDTM30) and derived terrain variables at 1 arc-s spacing grid ($\sim$30 m spatial resolution) is described. Copernicus DEM, ALOS World3D, and object height models were combined in a data fusion approach to generate a globally consistent digital terrain model (DTM). This DTM was then used to compute 15 standard terrain variables across six scales (30, 60, 120, 240, 480 and 960 m). A global-to-local transfer learning model framework with 5° × 5° tiling leveraged globally distributed lidar datasets: ICESat-2 ATL08 (best-fit terrain height) and GEDI02 (lowest mode elevation), totaling over 30 billion training points. A global model was initially fitted using ICESat-2 and GEDI, followed by locally optimized models per tile, ensuring both global consistency and local accuracy. Independent validation shows that GEDTM30 reduces Copernicus DEM RMSE by about 25.4% in built-up areas, 10.0% in regions with 10–50% tree cover, and 27.3% in areas with over 50% tree cover. Compared to state-of-the-art DTMs (MERIT DEM, FABDEM and FathomDEM), GEDTM30 achieves the lowest vertical errors when assessed with GNSS station records, yielding a standard deviation of 7.77 m, an RMSE of 10.69 m, and a mean error of 7.34 m. FathomDEM exhibited the lowest vertical RMSE when validated against independent reference DTMs. GEDTM30 was further used to generate multiscale variables of topography and hydrology through an optimized tilin...