中文

Journal of Applied Sciences >

2025 , Vol. 43 >Issue 4: 694 - 708

DOI: https://doi.org/10.3969/j.issn.0255-8297.2025.04.011

Signal and Information Processing

Forest Canopy Height Inversion Method Based on GEDI, Sentinel-2 and Airborne LiDAR

  • JI Cuicui ,
  • YUE Lianggaoke ,
  • LI Xiaosong ,
  • SUN Bin
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  • 1. School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China;
    2. International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China;
    3. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
    4. Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China 5. Chongqing Institute of Geology and Mineral Resources, Chongqing 400042, China

Received date: 2024-06-11

  Online published: 2025-07-31

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Abstract

Large-scale monitoring of forest canopy height is essential for accurate estimation of forest carbon emissions and analysis of forest growth. In this study, we integrate canopy height metrics obtained from global ecosystem dynamics investigation (GEDI), Sentinel-2 image spectral information and ASTER GDEM terrain data to estimate canopy height in a forest area dominated by trees and shrubs in Xichang City, Sichuan Province. Random forest, gradient boosting decision tree, and multivariable linear regression algorithms are employed for canopy height inversion. Algorithm validation demonstrates that the combination of spectral information, vegetation index, and terrain information yields the highest inversion accuracy. The random forest algorithm performs best, achieving a coefficient of determination R2 of 0.58, a root mean square error RMSE of 4.78 m, and an estimation accuracy EA of 56%. Meanwhile, we use the RF algorithm to invert the canopy height and verify the accuracy with the laser point cloud data obtained by DJI UAV, resulting in R2 of 0.52, RMSE of 2.71 m, and EA of 85%. Overall, this study confirms that the small spot diameter and high-density spot of GEDI spaceborne full-waveform liDAR data offers potential for spatially continuous forest canopy height mapping. The findings contribute a theoretical basis for accurately grasping the growth analysis of forest degra-dation and restoration.

Key words： global ecosystem dynamics investigation (GEDI); Sentinel-2; canopy height; airborne LiDAR

Cite this article

JI Cuicui , YUE Lianggaoke , LI Xiaosong , SUN Bin . Forest Canopy Height Inversion Method Based on GEDI, Sentinel-2 and Airborne LiDAR[J]. Journal of Applied Sciences, 2025 , 43(4) : 694 -708 . DOI: 10.3969/j.issn.0255-8297.2025.04.011

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