Species level mapping of forest canopy height in Nepal using GEDI with Sentinel-1 and Sentinel-2

Forest canopy height mapping is critical for mapping and modeling bio-geophysical and ecological factors, including forest aboveground biomass, carbon reserves, forest carbon emissions, habitat diversity, forest degradation, and restoration success. The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne Light Detection and Ranging (LiDAR) sensor designed specifically to collect data on forest ecosystems worldwide. However, the information obtained by GEDI is not wall-to-wall, requiring data fusion approaches to map spatially continuous canopy heights. This study, for the first time, presents canopy height models for the entire country of Nepal based on interpolated GEDI tree heights fusing Sentinel-2 multispectral imagery with Sentinel-1 synthetic aperture radar (SAR), creating species-specific continuous canopy height models for Nepal at 10 m resolution. Forest plot field data, collected from a nationwide campaign, provided data on species identity, which was used for species mapping and accuracy evaluation. Differences in canopy-architecture and leaf-level traits mean that species-specific models are needed to interpolate GEDI tree heights using the Sentinel optical and SAR data. The national forest height map was compared with an independent set of GEDI data (RMSE = 2.4 m, R 2 = 0.92, intercept (c) = 0.53 m and slope (m) = 0.98) and fully independent field data (RMSE = 3.7 m, R 2 = 0.74, c = 4.1 m, and m = 0.89). The developed forest type map and canopy height models have the potential to aid in both operational monitoring and hindcasting of historical forest height and its dynamics. Local and national forest management initiatives and international climate and sustainable development projects require this kind of capacity.

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Publication Details

Journal
Frontiers in Remote Sensing
Published
2026-01-28
DOI
https://doi.org/10.3389/frsen.2026.1725509
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Species level mapping of forest canopy height in Nepal using GEDI with Sentinel-1 and Sentinel-2

Him Lal Shrestha, Abid Nazir, Niall P. Hanan, Hammad Gilani
Frontiers in Remote Sensing
Remote Sensing and LiDAR Applications
article

Species level mapping of forest canopy height in Nepal using GEDI with Sentinel-1 and Sentinel-2

Him Lal Shrestha, Abid Nazir, Niall P. Hanan, Hammad Gilani
article en

Abstract

Forest canopy height mapping is critical for mapping and modeling bio-geophysical and ecological factors, including forest aboveground biomass, carbon reserves, forest carbon emissions, habitat diversity, forest degradation, and restoration success. The Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne Light Detection and Ranging (LiDAR) sensor designed specifically to collect data on forest ecosystems worldwide. However, the information obtained by GEDI is not wall-to-wall, requiring data fusion approaches to map spatially continuous canopy heights. This study, for the first time, presents canopy height models for the entire country of Nepal based on interpolated GEDI tree heights fusing Sentinel-2 multispectral imagery with Sentinel-1 synthetic aperture radar (SAR), creating species-specific continuous canopy height models for Nepal at 10 m resolution. Forest plot field data, collected from a nationwide campaign, provided data on species identity, which was used for species mapping and accuracy evaluation. Differences in canopy-architecture and leaf-level traits mean that species-specific models are needed to interpolate GEDI tree heights using the Sentinel optical and SAR data. The national forest height map was compared with an independent set of GEDI data (RMSE = 2.4 m, R 2 = 0.92, intercept (c) = 0.53 m and slope (m) = 0.98) and fully independent field data (RMSE = 3.7 m, R 2 = 0.74, c = 4.1 m, and m = 0.89). The developed forest type map and canopy height models have the potential to aid in both operational monitoring and hindcasting of historical forest height and its dynamics. Local and national forest management initiatives and international climate and sustainable development projects require this kind of capacity.

Frontiers in Remote SensingVol. 7
New Mexico State University (US), National University of Science and Technology (ZW), Kathmandu University (NP)
National Aeronautics and Space Administration, Nuclear Safety and Security Commission
Openalex Percentile: Top 77%
Remote Sensing and LiDAR Applications
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