Environmental Modelling & Software · 2024 · 10 citations · 96 references
Natural SciencesEarth SciencesForestryDigital Elevation ModelingGeographic Information SystemsRemote SensingLand Surface ModelingLand Surface MonitoringRemote Sensing For Forest InventoryRemote Sensing Image AnalysisTerrain ModelingVegetation MonitoringCanopy Height MappingEcosystem DynamicsForest Height MappingForest MonitoringForest Resource InventoryGeospatial Big DataRemote Sensing-based Height EstimationTime Windows
Spatially and temporally discontinuous canopy height footprints collected by NASA's GEDI (Global Ecosystem Dynamics Investigation) mission are accessible on the Google Earth Engine (GEE) cloud computing platform. This study introduces an open-source, user-friendly, code-free GEE web application called Canopy Height Mapper (CH-GEE), available at https://ee-calvites1990.projects.earthengine.app/view/ch-gee, which automatically generates (10 m) high-resolution canopy height maps for a specific area by integrating GEDI with multi-source remote sensing data: Copernicus and topographical data from the GEE data catalogue. CH-GEE generates local-to-country scale calibrated canopy height maps worldwide using machine learning algorithms and leveraging the GEE platform's big data and cloud computing capabilities. CH-GEE allows customization of geographic area, algorithms and time windows for GEDI and predictors. Canopy heights generated by CH-GEE were validated using the Italian National Forest Inventory across 110,000 km2 at multiple scales (Country-based R-squared = 0.89, RMSE = 17%). CH-GEE's accuracy and scalability make it suitable for forest monitoring.
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