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Investigating the Influence of GEDI Vegetation Penetration on Canopy Height Estimation

IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
This paper evaluates GEDI's canopy height estimation accuracy in dense tropical forests located in Mayotte Island. It examines GEDI's ability to penetrate canopies and detect the ground, which is crucial for reliable estimates. The study tests the use of a single GEDI height metric (rh_95) in comparison with regression models using various GEDI metrics
Lahssini, Kamel   +4 more
openaire   +1 more source

High-resolution mapping of forest canopy height using machine learning by coupling ICESat-2 LiDAR with Sentinel-1, Sentinel-2 and Landsat-8 data

International Journal of Applied Earth Observation and Geoinformation, 2020
Wang Li, Zheng Niu, Rong Shang
exaly  

Forest canopy height variation in relation to topography and forest types in central Japan with LiDAR

Forest Ecology and Management, 2022
Farhadur Rahman   +2 more
exaly  

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