ASSESSMENT OF CANOPY AND GROUND HEIGHT ACCURACY FROM GEDI LIDAR OVER STEEP MOUNTAIN AREAS

30 citations as recorded by crossref.

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6. Slope Filtering Improves GEDI LiDAR Canopy Height Predictions in Himalayan Tropical Forests R. Bodh et al. https://doi.org/10.1007/s12524-026-02553-4
7. Role of LiDAR remote sensing in identifying physiognomic traits of alpine treeline: a global review J. Mathew et al. https://doi.org/10.1007/s42965-023-00317-6
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14. Evaluating Lorenz entropy for tropical forest discrimination using GEDI and supervised machine learning approach N. Mashhadi & A. Sanchez-Azofeifa https://doi.org/10.1016/j.ecolind.2025.113374
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18. Quantification of GEDI Geolocation Error and Its Influence on Elevation and Canopy Height C. Yang et al. https://doi.org/10.1109/JSTARS.2024.3461843
19. Machine Learning-Based Analysis of Forest Vertical Structure Dynamics Using Multi-Temporal UAV Photogrammetry and Geomorphometric Indicators A. Yiğit https://doi.org/10.3390/f17020258
20. Application of Random Forest Method Based on Sensitivity Parameter Analysis in Height Inversion in Changbai Mountain Forest Area X. Wang et al. https://doi.org/10.3390/f15071161
21. Maximum tree height in European Mountains decreases above a climate-related elevation threshold P. Gelabert et al. https://doi.org/10.1038/s43247-024-01246-5
22. Use of GEDI Signal and Environmental Parameters to Improve Canopy Height Estimation over Tropical Forest Ecosystems in Mayotte Island K. Lahssini et al. https://doi.org/10.1080/07038992.2024.2351004
23. Accuracy assessment of GEDI terrain elevation, canopy height, and aboveground biomass density estimates in Japanese artificial forests H. Li et al. https://doi.org/10.1016/j.srs.2024.100144
24. Canopy height mapping in French Guiana using multi-source satellite data and environmental information in a U-Net architecture K. Lahssini et al. https://doi.org/10.3389/frsen.2024.1484900
25. Improving GEDI geolocation accuracy with ultra-high-resolution DTM data in Japan H. Li et al. https://doi.org/10.1080/15481603.2025.2601327
26. Forest Canopy Height Extraction Method Based on ICESat-2/ATLAS Data X. Huang et al. https://doi.org/10.1109/TGRS.2023.3240848
27. Forest Aboveground Biomass in the Annapurna Region, Himalaya, Derived From Ground-Based and Spaceborne Laser Scanning S. Das et al. https://doi.org/10.1659/mrd.2025.00031
28. Satellite-based mapping of canopy fuels at the pan-European scale E. Kutchartt et al. https://doi.org/10.1080/10095020.2024.2429376
29. Improving Ground Elevation Accuracy by Spaceborne LiDAR Waveforms Over Rugged Mountain Vegetated Areas H. Wang et al. https://doi.org/10.1109/TGRS.2026.3708981
30. How to get closer to actual forest stand height using GEDI? A case study in central European Scots pine stands W. Krawczyk & P. Wężyk https://doi.org/10.1080/22797254.2024.2399209