文献类型：期刊文献

英文题名：Evaluating Forest Aboveground Biomass Products by Incorporating Spatial Representativeness Analysis

作者：Wang, Yin[1,2,3] Wang, Xiaohui[1,2,4] Ji, Ping[1,2,4] Li, Haikui[1,2,4] Wei, Shengrong[1,2,4] Peng, Daoli[3]

第一作者：Wang, Yin

通信作者：Wang, XH[1];Wang, XH[2];Wang, XH[3]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Natl Forestry & Grassland Adm, Key Lab Forestry Remote Sensing & Informat Syst, Beijing 100091, Peoples R China;[3]Beijing Forestry Univ, State Key Lab Efficient Prod Forest Resources, Beijing 100083, Peoples R China;[4]Natl Forestry & Grassland Sci Data Ctr, Beijing 100091, Peoples R China

年份：2025

卷号：17

期号：16

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20253519069843);Scopus(收录号：2-s2.0-105014260929);WOS:【SCI-EXPANDED(收录号:WOS:001560077300001)】；

基金：This research was funded by the National Key R&D Program of China, grant number 2022YFF0711602 and National Key R&D Program of China, grant number 2023YFF1303905.

语种：英文

外文关键词：forest aboveground biomass; spatial representativeness analysis; the National Aeronautics and Space Administration's Global Ecosystem Dynamics Investigation; the European Space Agency's Climate Change Initiative; remote sensing; carbon cycle

摘要：Forest aboveground biomass (AGB) products serve as essential references for research on carbon cycle and climate change. However, significant uncertainties exist regarding forest AGB products and their evaluation methods. This study aims to evaluate AGB products in the context of discrepancies in plot size and product scales, while also investigate the applicability of large-scale AGB products at a regional level. The National Aeronautics and Space Administration (NASA)'s Global Ecosystem Dynamics Investigation (GEDI) and the European Space Agency (ESA)'s Climate Change Initiative (CCI) biomass data were evaluated using sample plots from the National Forest Inventory (NFI). The study was conducted in Jilin Province, located in Northeast China, which is predominantly covered by natural forests. Spatial representativeness evaluation indicators for sample plots were established, followed by a comprehensive representativeness assessment and the selection of sample plots based on the criteria importance through the intercriteria correlation (CRITIC) method. Additionally, the study conducted an overall evaluation of the products, as well as evaluations across different biomass ranges and various forest types. The results indicate that the accuracy metrics demonstrated improved performance when using representative plots compared to all plots, with the R-2 increasing by 15.38%. Both products demonstrated optimal accuracy and stability in the 50-150 Mg/ha range. GEDI and CCI biomass data indicated an overall underestimation, with biases of -25.68 Mg/ha and -83.95 Mg/ha, respectively. Specifically, a slight overestimation occurred in the <50 Mg/ha range, while a gradually increasing underestimation was observed in the >= 50 Mg/ha range. This study highlights the advantages of spatial representativeness analysis in mitigating evaluation uncertainties arising from scale mismatches and enhancing the reliability of product evaluation. The accuracy trends of AGB products offer significant insights that could facilitate improvements and enhance their application.