Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data Post author:Datasetly Post published:July 10, 2025 Post category:Climate, weather, drought, water resources / Environment / Satellites, Earth Observation, PNT Solutions LOGIN TO ACCESS DATASET INFORMATION Tags: AI, Big data, Dataset, Earth observation, Geospatial, Global science, Machine learning, Publication, Remote sensing, Research, Satellites, Technology Read more articles Previous PostCultivated-pasture dataset of the Tibetan Plateau from 1988 to 2021 Next PostMapping the world’s inland surface waters: an upgrade to the Global Lakes and Wetlands Database (GLWD v2) You Might Also Like GPS-derived gridded total water storage changes in South Africa from 2000 to 2021 June 4, 2025 Sand and gravel mining in the United States and related panel data (2000-2023) July 14, 2025 High-resolution maps of rice cropping intensity across Southeast Asia August 13, 2025
