Global DEM Product Generation by Correcting ASTER GDEM Elevation with ICESat-2 Altimeter Data

Abstract. Advancements in scientific inquiry and practical applications have put forward a higher demand for the accuracy of global digital elevation models (GDEMs), especially for GDEMs whose main data source is optical imagery. To address this challenge, integrating GDEM and satellite laser altimeter data (global coverage and high-accuracy ranging) is one of the important research directions, in addition to the technological enhancement of the main data source. In this paper, we describe the datasets and algorithms used to generate a GDEM product (IC2-GDEM) by correcting ASTER GDEM elevation data with ICESat-2 altimeter data. The algorithm scheme presents the details of the strategies used for the various challenges, such as the processing of DEM boundaries, the fusion of the different data, the geographical layout of the satellite laser altimeter data, etc. We used a high-accuracy global elevation control point dataset and multiple high-accuracy local DEMs as the validation data for a comprehensive assessment at a global scale. The results from the validation comparison present that the elevation accuracy of IC2-GDEM is evidently superior to that of the ASTER GDEM product. The root-mean-square error (RMSE) reduction ratio of the corrected GDEM elevation is between 16 % and 82 %, and the average reduction ratio is about 47 %. From the analysis of the different topographies and land covers, it was also found that this error reduction is effective even in areas with high topographic relief (>15°) and high vegetation cover (>60 %). ASTER GDEM has been in use for more than a decade, and many historical datasets and models are based on its elevation data. IC2-GDEM facilitates seamless integration with these historical datasets, which is essential for longitudinal studies examining long-term environmental change, land use dynamics, and climate impacts. Meanwhile, IC2-GDEM can serve as a new complementary data source to existing DEMs (Copernicus DEM, etc.) mainly sourced from synthetic aperture radar (SAR) observation. By cross-validating qualities, filling data gaps, conducting multi-scale analyses,etc., it can lead to more reliable and comprehensive scientific discoveries, thereby improving the overall quality and reliability of earth science research. IC2-GDEM product is openly released via https://doi.org/10.11888/RemoteSen.tpdc.301229 (Xie et al., 2024).