文献类型：期刊文献

英文题名：Estimation of above-ground biomass using MODIS satellite imagery of multiple land-cover types in China

作者：Yuan, Xiuliang[1,2] Li, Longhui[1] Tian, Xin[3] Luo, Geping[1] Chen, Xi[1]

第一作者：Yuan, Xiuliang

通信作者：Li, LH[1]

机构：[1]Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi, Peoples R China;[2]Univ Chinese Acad Sci, Grad Sch, Beijing, Peoples R China;[3]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing, Peoples R China

年份：2016

卷号：7

期号：12

起止页码：1141-1149

外文期刊名：REMOTE SENSING LETTERS

收录：;EI(收录号：20163802829159);Scopus(收录号：2-s2.0-84987900129);WOS:【SCI-EXPANDED(收录号:WOS:000383873900004)】；

基金：This work was supported by the National Natural Science Foundation of China [41171094] National Basic Research Programs of China [2014CB460603] National Basic Research Program of China [2013CB733404]

语种：英文

外文关键词：Radiometers - Satellite imagery

摘要：Estimations of above-ground biomass (AGB) at various spatial and temporal scales remain a large uncertainty when quantifying the global carbon cycle. In this work, we assessed the ability of the Enhanced Vegetation Index (EVI), obtained from the Moderate-Resolution Imaging Spectroradiometer, for estimating AGB across multiple land cover types in China. Our results indicate that, with the exception of mixed forests at the site level, annual integrated EVI (iEVI) can be used for estimating AGB. We were also able to reduce the permissible margin of error for the total AGB of mixed forests at the biome level. Estimated total AGB for China was determined to be 21.19 Pg (1 Pg = 1 x 10(12) Kg), with 69.8% attributed to forests and 31.2% to non-forests. Overall, we concluded that iEVI has great potential for dynamically estimating spatial AGB. Here, we also describe the correspondence between analysed parameters.