Machine learning-based estimates of aboveground biomass of subalpine forests using Landsat 8 OLI and Sentinel-2B images in the Jiuzhaigou National Nature Reserve,Eastern Tibet Plateau

作     者：Ke Luo Yufeng Wei Jie Du Liang Liu Xinrui Luo Yuehong Shi Xiangjun Pei Ningfei Lei Ci Song Jingji Li Xiaolu Tang Ke Luo;Yufeng Wei;Jie Du;Liang Liu;Xinrui Luo;Yuehong Shi;Xiangjun Pei;Ningfei Lei;Ci Song;Jingji Li;Xiaolu Tang

作者机构：College of Earth ScienceChengdu University of TechnologyChengdu 610059People’s Republic of China State Key Laboratory of Geohazard Prevention and Geoenvironment ProtectionChengdu University of TechnologyChengdu 610059People’s Republic of China Jiuzhaigou Nature Reserve AdministrationAba Tibetan and Qiang Autonomous PrefectureJiuzhai 623402People’s Republic of China College of Ecology and EnvironmentChengdu University of TechnologyChengdu 610059People’s Republic of China State Environmental Protection Key Laboratory of Synergetic Control and Joint Remediation for Soil&Water PollutionChengdu Univer-Sity of TechnologyChengdu 610059People’s Republic of China China RailwayEryuan Engineering Group Co.LtdChengdu 610031People’s Republic of China 

出 版 物：《Journal of Forestry Research》 (林业研究（英文版）)

年 卷 期：2022年第33卷第4期

页      面：1329-1340页

核心收录：

学科分类：0907[农学-林学] 09[农学] 0903[农学-农业资源与环境] 

基　　金：supported financially by the Specialized Fund for the Post-Disaster Reconstruction and Heritage Protec-tion in Sichuan Province(5132202019000128) the Everest Scientific Research Program of Chengdu University of Technology(80000-2021ZF11410) the Second Tibetan Plateau Scientific Expedition and Research Program(STEP,2019QZKK0307) the State Key Laborato-ry of Geohazard Prevention and Geoenvironment Protection Independent Research Project(SKLGP2018Z004) the key technologies of Mountain rail transit green construction in ecologically sensitive region based on Mountain rail transit from Dujiangyan to Mt.Siguniang anti-poverty project(2018-zl-08) Study on risk identification and countermeasures of Sichuan-Tibet Railway Major Projects(2019YFG0460) 

主　　题：Aboveground biomass Linear regression Random forest Extreme gradient boosting Landsat 8 OLI Sentinel-2B 

摘      要：Accurate estimates of forest aboveground biomass(AGB)are critical for supporting strategies of ecosystem conservation and climate change *** Jiuzhaigou National Nature Reserve,located in Eastern Tibet Plateau,has rich forest resources on steep slopes and is very sensitive to climate change but plays an important role in the regulation of regional carbon ***,an estimation of AGB of subalpine forests in the Nature Reserve has not been carried out and whether a global biomass model is available has not been *** provide this information,Landsat 8 OLI and Sentinel-2B data were combined to estimate subalpine forest AGB using linear regression,and two machine learning approaches–random forest and extreme gradient boosting,with 54 inventory *** of forest type,Observed AGB of the Reserve varied from 61.7 to 475.1 Mg hawith an average of 180.6 Mg *** indicate that integrating the Landsat 8 OLI and Sentinel-2B imagery significantly improved model efficiency regardless of modelling *** results highlight a potential way to improve the prediction of forest AGB in mountainous *** AGB indicated a strong spatial ***,the modelled biomass varied greatly with global biomass products,indicating that global biomass products should be evaluated in regional AGB estimates and more field observations are required,particularly for areas with complex terrain to improve model accuracy.