Estimation of above-ground biomass using MODIS satellite imagery of multiple land-cover types in China. Issue 12 (1st December 2016)

• Record Type: Journal Article
• Authors: Yuan, Xiuliang; Li, Longhui; Tian, Xin; Luo, Geping; Chen, Xi
• Is Part Of: Remote sensing letters. Volume 7:Issue 12(2016)
• Page Start: 1141
• Page End: 1149
• Publication Date: 2016-12-01
• Subjects: Remote sensing -- Periodicals; Remote sensing; Periodicals; 621.3678
• DOI: 10.1080/2150704X.2016.1219458
• Languages: English
• ISSNs: 2150-704X

Abstract

ABSTRACT: 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 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.