Forest height mapping using inventory and multi-source satellite data over Hunan Province in southern China

作     者：Wenli Huang Wankun Min Jiaqi Ding Yingchun Liu Yang Hu Wenjian Ni Huanfeng Shen 

作者机构：School of Resource and Environmental SciencesWuhan UniversityHubei430079China State Key Laboratory of Remote Sensing ScienceInstitute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing100101China College of Urban and Environmental SciencesPeking UniversityBeijing100871China Academy of Inventory and PlanningNational Forestry and Grassland AdministrationBeijing100714China School of Ecology and EnvironmentNingxia UniversityYinchuan750021China Breeding Base for State Key Laboratory of Land Degradation and Ecological Restoration in Northwest ChinaNingxia UniversityYinchuan750021China Key Laboratory for Restoration and Reconstruction of Degraded Ecosystem in Northwest China of Ministry of EducationNingxia UniversityYinchuan750021China 

出 版 物：《Forest Ecosystems》 (森林生态系统（英文版）)

年 卷 期：2022年第9卷第1期

页      面：57-70页

核心收录：

学科分类：0710[理学-生物学] 0830[工学-环境科学与工程（可授工学、理学、农学学位）] 0907[农学-林学] 0829[工学-林业工程] 09[农学] 0903[农学-农业资源与环境] 0901[农学-作物学] 0833[工学-城乡规划学] 0713[理学-生态学] 0834[工学-风景园林学（可授工学、农学学位）] 

基　　金：This work was funded by the Open Fund of State Key Laboratory of Remote Sensing Science(OFSLRSS201904) National Natural Science Foundation of China(41901351) Start-up Program of Wuhan University(2019-2021) Natural Science Foundation of Ningxia Province(2021AAC03017) 

主　　题：Forest canopy height Hunan province Landsat ARD PALSAR-2 Sentinel-1 

摘      要：Background:Accurate mapping of forest canopy heights at a fine spatial resolution over large geographical areas is *** is essential for the estimation of forest aboveground biomass and the evaluation of forest *** current regional to national scale forest height maps were mainly produced at *** maps lack spatial details for decision-making at local *** advances in remote sensing provide great opportunities to fill this ***:In this study,we evaluated the utility of multi-source satellite data for mapping forest heights over Hunan Province in China.A total of 523 plot data collected from 2017 to 2018 were utilized for calibration and validation of forest height ***,the relationships between three types of in-situ measured tree heights(maximum-,averaged-,and basal area-weighted-tree heights)and plot-level remote sensing metrics(multispectral,radar,and topo variables from Landsat,Sentinel-1/PALSAR-2,and SRTM)were *** types of models(multilinear regression,random forest,and support vector regression)were *** variables were selected by two types of variable selection approaches(stepwise regression and random forest).Model parameters and model performances for different models were tuned and evaluated via a 10-fold cross-validation ***,tuned models were applied to generate wall-to-wall forest height maps for Hunan ***:The best estimation of plot-level tree heights(R2 ranged from 0.47 to 0.52,RMSE ranged from 3.8 to 5.3 m,and rRMSE ranged from 28%to 31%)was achieved using the random forest model.A comparison with existing forest height maps showed similar estimates of mean height,however,the ranges varied under different definitions of forest and types of tree ***:Primary results indicate that there are small biases in estimated heights at the province *** study provides a framework toward establishing regional to national scale maps of