林业科学2025，Vol.61Issue(3)：16-26,11.DOI:10.11707/j.1001-7488.LYKX20240213
基于GEDI和Sentinel-2的内蒙古退耕还林地块树高估测
Estimation of Tree Height in the Grain for Green Program Stands of Inner Mongolia Based on GEDI and Sentinel-2
摘要
Abstract
[Objective]A tree height sample set suitable for Grain for Green Project(GGP)stands was constructed,and the machine learning methods were integrated with remote sensing data to estimate tree height in GGP plots,in order to provide a reference basis for monitoring the effectiveness of the new round of GGP.[Method]To accurately estimate the tree height of the new round of GGP stands in Inner Mongolia,this study proposed an optimized GEDI sample selection method,and constructed a high-quality tree height sample set suitable for the GGP stands in Inner Mongolia.With Sentinel-2 medium high spatial resolution remote sensing data and terrain data,the gradient boosting tree algorithm was applied to estimate the tree heights in the GGP stands,and analyze the tree height status in the GGP stands.[Result]Based on the GEDI and Sentinel-2 machine learning model,the tree heights in the GGP stands were able to be accurately estimated with a coefficient of determination(R2)of 0.73,an estimation accuracy(EA)of 72%,and a root mean square error(RMSE)of 1.82 m.The optimized selection of GEDI samples improved the estimation accuracy for tree height in the GGP stands,with an increase in model estimation accuracy R2 by 0.32,a decrease in RMSE by 0.83 m,and an increase in EA by 13%compared to the unselected samples.The red-edge normalized vegetation index,difference vegetation index,and elevation,slope,and aspect variables are of high importance,with a cumulative contribution of over 50%,proving that vegetation indices and terrain information are key factors for tree height estimation.The distribution of tree height intervals in Inner Mongolia's GGP stands ranges from 2.5-20 m,with an average height of 5.5 m,mainly distributed in the 5-10 m range,which accounts for 53.51%.[Conclusion]The GEDI sample optimization screening method proposed in this study can significantly improve the accuracy of tree height estimation in the GGP stands,demonstrating the effectiveness of tailoring the screening process to the specific characteristics of the GGP stands.Based on remote sensing data and machine learning,this study has achieved the estimation of tree height for the new round of GGP stands in Inner Mongolia,providing a feasible approach for tree height estimation in these regions.关键词
GEDI/内蒙古退耕还林/树高/梯度提升树/可持续森林管理Key words
GEDI/Grain for Green in Inner Mongolia/tree height/gradient boosting tree/sustainable forest management分类
测绘与仪器引用本文复制引用
格根塔娜,月亮高可,李晓松,姬翠翠,王建和,沈通,王天璨..基于GEDI和Sentinel-2的内蒙古退耕还林地块树高估测[J].林业科学,2025,61(3):16-26,11.基金项目
科技基础资源调查专项(2022FY202300). （2022FY202300）
