🌍 The 2025 Global Tree Cover Loss Map update from the Global Land Analysis & Discovery laboratory at the University of Maryland (UMD GLAD) in collaboration with Global Forest Watch at the World Resources Institute is now available! This latest release provides valuable insights into global forest change, helping researchers, policymakers, and environmental practitioners better understand patterns of tree cover loss worldwide. Explore and download the data here: 🌲 Global Tree Cover Loss: https://lnkd.in/di3qhPN7 🔥 Global Tree Cover Loss Due to Fire: https://lnkd.in/ePrHuMpN Access to timely, high-quality forest monitoring data is essential for supporting conservation efforts, climate action, and sustainable land management. Take a look and explore the latest updates! #ForestMonitoring #TreeCoverLoss #Deforestation #RemoteSensing #GIS #ClimateAction #GLAD #GlobalForestChange #Sustainability #EarthObservation #GlobalForestWatch Department of Geographical Sciences at the University of Maryland
Hello, thank you for the contribution again ! GEE asset ID "UMD/hansen/global_forest_change_2025_v1_13" does not point to any image. Is the upload on GEE still ongoing ?
This dataset is one of the most important baselines in forest science. The question it naturally raises is what comes next: can we move from documenting where tree cover loss occurred to forecasting where it is likely to occur and why? Fire, pest outbreaks, compound drought-heat stress, and hurricane damage all leave signatures in this data, but they also have predictable precursors. And loss is not the end of the story. Forecasting recovery trajectories after disturbance, which landscapes regenerate and which do not, is just as critical for conservation planning and carbon accounting. Connecting retrospective loss maps to forward-looking risk and recovery models is where the next generation of forest monitoring tools needs to go.