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Tree Cover • Tree Height • Canpoy • Canopy Height • LIDAR • Forest • Rainforest
The Annual Tree Cover Height dataset maps global forest canopy height at 30-meter resolution. It was developed using GEDI lidar and Landsat time-series data. The model estimates forest height worldwide, including regions beyond GEDI coverage, through advanced regression modeling.
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This global forest canopy height dataset was developed at a 30-meter spatial resolution by integrating data from NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar instrument and Landsat time-series imagery.
GEDI, launched aboard the International Space Station in April 2019, collects high-resolution measurements of forest structure, including canopy height, across latitudes between 52°N and 52°S. The Global Land Analysis and Discovery (GLAD) team at the University of Maryland used GEDI data collected from April to October 2019 and combined it with 2019 Landsat data to produce the height estimates.
The GEDI RH95 (Relative Height at 95%) metric was used as a reference for training a regression tree ensemble model. Landsat data provided the predictor variables, capturing temporal patterns and landscape characteristics.
A “moving window” strategy was implemented to ensure locally accurate predictions, and the model was further extended to boreal forests outside of GEDI’s coverage zone to achieve global completeness.
Spatial Resolution
30m x 30m
The World Resources Institute (WRI) is a global research organization focused on sustainable development and environmental protection. WRI works on issues like climate, energy, food, and forests helping governments and businesses make informed, sustainable choices.
The Global Land Analysis and Discovery (GLAD) team at the University of Maryland focuses on monitoring global land cover and forest change using satellite data. Their work supports conservation, climate research, and sustainable land-use planning by providing high-resolution, timely environmental data.