Estimation of Forest Canopy Closure Based on Spaceborne LiDAR ICESat–2/ATLAS Data

Wei Zhiyue; Li Hao; Shu Qingtai; Xi Lei; Song Hanyue; Qiu Shuang; Yang Zezhi

doi:10.11929/j.swfu.202211067

Journal of Southwest Forestry University > 2024 > 44(2): 127-134. > DOI: 10.11929/j.swfu.202211067

Wei Zhiyue, Li Hao, Shu Qingtai, Xi Lei, Song Hanyue, Qiu Shuang, Yang Zezhi. Estimation of Forest Canopy Closure Based on Spaceborne LiDAR ICESat–2/ATLAS Data[J]. Journal of Southwest Forestry University, 2024, 44(2): 127-134. DOI: 10.11929/j.swfu.202211067

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Estimation of Forest Canopy Closure Based on Spaceborne LiDAR ICESat–2/ATLAS Data

1.
College of Forestry, Southwest Forestry University, Kunming Yunnan 650233, China
2.
United Front Work Department of the Party Committee, Southwest Forestry University, Kunming Yunnan 650233, China

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Received Date: November 21, 2022
Revised Date: February 15, 2023
Accepted Date: April 22, 2023
Available Online: April 25, 2023
Published Date: March 19, 2024

Graphical Abstract

Abstract

Abstract

Taking Shangri-La City, Yunnan Province as the research area, based on ICESat‒2 / ATLAS data, the remote sensing forest canopy density estimation models were established by random forest regression, gradient boosting tree regression and nearest neighbor regression, respectively. The optimal model was selected to invert the forest canopy closure within the study area spots. The results showed that random forest modeling was the best method to estimate forest canopy closure, the coefficient of determination(R²) was 0.9446, mean square error (RMSE) was 0.0560 and the prediction accuracy(P) was 90.60%. The predicted values of canopy closure corresponding to 74873 effective forest spots in Shangri-La City were obtained, and the spatial distribution map of canopy closure of all forest spots in the city was obtained by combining the spot center coordinates. The results can provide a reference for remote sensing estimation of forest canopy closure at low-high altitude areas.
- LiDAR,
- ICESat–2,
- canopy closure,
- random forest

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References (38)

References

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