文献类型：期刊文献

英文题名：Development of forest aboveground biomass estimation, its problems and future solutions: A review

作者：Ma, Taiyong[1] Zhang, Chao[2] Ji, Liping[3] Zuo, Zheng[4] Beckline, Mukete[5] Hu, Yang[6,7,8,9] Li, Xiaojuan[8,9] Xiao, Xiangming[10]

第一作者：Ma, Taiyong

通信作者：Hu, Y[1];Xiao, XM[2]

机构：[1]Ningxia Univ, Coll Forestry & Prataculture, Yinchuan 750021, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forestry Policy & Informat, Beijing 100091, Peoples R China;[3]State Owned Forest Farm & Forest Tree Seedling Wor, Yinchuan 750021, Peoples R China;[4]Henan Acad Forestry, Zhengzhou 450008, Henan, Peoples R China;[5]Agrosyst Grp, Res & Dev Unit, POB 76, Tiko, Southwest Regio, Cameroon;[6]Breeding Base State Key Lab Land Degradat & Ecol R, Yinchuan 750021, Peoples R China;[7]Minist Educ, Key Lab Restorat & Reconstruct Degraded Ecosyst No, Yinchuan 750021, Peoples R China;[8]Ningxia Univ, Sch Ecol & Environm, Yinchuan 750021, Peoples R China;[9]Ningxia Helan Mt Forest Ecosyst Orientat Observat, Yinchuan 750021, Peoples R China;[10]Univ Oklahoma, Ctr Earth Observat & Modeling, Sch Biol Sci, Norman, OK 73019 USA

年份：2024

卷号：159

外文期刊名：ECOLOGICAL INDICATORS

收录：;EI(收录号：20240715537939);Scopus(收录号：2-s2.0-85184520477);WOS:【SCI-EXPANDED(收录号:WOS:001185795500001)】；

基金：This paper was supported by the Key Project of Research and Development of Ningxia, China (2022BEG03050, 2021BEB04061) , and the National Natural Science Foundation of China (32101524) .

语种：英文

外文关键词：Aboveground biomass; Remote sensing; Manual survey; Overlap; UAV LiDAR

摘要：Forest aboveground biomass (AGB) is crucial as it serves as a fundamental indicator of the productivity, biodiversity, and carbon storage of forest ecosystems. This paper presents a targeted literature review of advancements in AGB estimation methods. We conducted an extensive review of published literature using Web of Science, ResearchGate, Semantic Scholar, and Google Scholar. Our findings highlight the importance of accurate AGB estimation in the studies of terrestrial carbon cycle, forest ecosystem management, and climate change. Moreover, AGB estimation contributes valuable ecological knowledge and supports effective natural resource management. Unfortunately, during the data collection process for AGB estimation, we have identified two critical yet often overlooked issues: (1) the reliability of manual survey accuracy, and (2) the impact of overlap between ground plots and remote sensing pixels on AGB estimation. Drawing on existing technologies and literature analysis, we propose a potentially effective solution to address these challenges. In conclusion, accurate estimation and mapping of forest parameters, such as AGB, will remain a priority in forestry research for the foreseeable future. To ensure the practical applicability of AGB research findings, our future research efforts will focus on understanding manual survey accuracy and determining the optimal overlap between plots and pixels.