西南林业大学学报2025，Vol.45Issue(3)：159-168,10.DOI:10.11929/j.swfu.202401017
基于ICESat-2/ATLAS的景东彝族自治县森林生物量估测研究
Estimation of Forest Biomass Based on ICESat-2/ATLAS Data in Jingdong Yi Autonomous County
摘要
Abstract
In this study,Jingdong Yi Autonomous County of Yunnan Province was selected as the research area,and space-borne LiDAR ICESat-2/ATLAS was used as the main information source.On the basis of denois-ing and classifying ATLAS data,Kriging interpolation based on geostatistics realized the spatial expansion of the index points of ATLAS spot parameters from"point"to"surface".A forest biomass estimation model was estab-lished based on 265 biomass survey plots.The results showed as follows:Based on random forest importance ranking,the 5 parameters of ATLAS light spot with strong correlation with forest biomass are h_max_canopy_abs,h_mean_canopy,ph_ndx_beg,solar_elevation,and solar_azimuth.Variance function analys-is was performed on the 5 parameters,and the optimal variation function model is selected according to the de-termination coefficient and spatial autocorrelation.The spatial interpolation effect of the 3 parameters including h_max_canopy_abs,solar_elevation and solar_azimuth was the best using the spherical model,h_mean_canopy and ph_ndx_beg had better effects with the exponential model.Based on random forest regression,a remote sens-ing estimation model of forest biomass in the study area was established,with modeling accuracy R2=0.7941 and RMSE=23.0047 t/hm2,taking the above-ground biomass of 265 plots as explained variables and corresponding 5 parameters as explanatory variables.The model can be used as an estimation model of forest above-ground bio-mass in the study area.The forest biomass in the study area was estimated based on the verified RF model,and the estimated value was 31 269874.76 t.The forest biomass calculated by the 2019 ground survey group in the study area was 26674465.55 t as the reference truth value,with an estimated accuracy of 85.3％.The spatial distribu-tion is basically consistent with the actual calculation results.The results showed that the forest biomass estima-tion based on ICESat-2/ATLAS data had a good effect.关键词
ICESat-2/ATLAS/特征优选/变异函数/克里格插值/随机森林/生物量Key words
ICESat-2/ATLAS/feature optimization/variance function/Kriging interpolation/random forest/biomass分类
林学引用本文复制引用
饶昕,舒清态,王继雄,罗绍龙,杨正道..基于ICESat-2/ATLAS的景东彝族自治县森林生物量估测研究[J].西南林业大学学报,2025,45(3):159-168,10.基金项目
国家自然科学基金项目(31860205)资助 （31860205）
云南省农业联合专项重点项目(202301BD070001-002)资助. （202301BD070001-002）
