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An Extended Approach for Biomass Estimation in a Mixed Vegetation Area Using ASAR and TM Data

Xing, Minfeng, He, Binbin, Quan, Xingwen, Li, Xiaowen
Photogrammetric engineering and remote sensing 2014 v.80 no.5 pp. 429-438
aboveground biomass, arid zones, models, phenology, remote sensing, spatial data, vegetation cover, vegetation types
<p><i>The use of microwave remote sensing for estimating vegetation biomass is limited in arid regions because of the heterogeneous distribution of vegetation, variable scattering mechanisms from different vegetation components, and the strong influence from underlying ground surface. In order to minimize this problem, a synergistic method of optical and microwave remote sensing data for the retrieval of aboveground biomass (AGB) based on the modified water cloud model (WCM) was developed in this paper. Vegetation coverage which can be easily estimated from optical data as additional information was combined in this method. Dimidiate pixel model (DPM) and phenological subtraction methodology (PSM) were used to estimate vegetation coverage and differentiate vegetation types in the sub-pixel domain, respectively. The percentage cover of unmixed vegetation was incorporated to minimize problems associated with heterogeneous vegetation and sparse vegetation cover. Finally, the accuracy and sources of error in this novel AGB retrieval method were evaluated. The results showed that the predicted AGB correlated with the measured AGB (R<sup>2</sup> = 0.8007; RMSE = 0.2808 kg/m<sup>2</sup>).</i></p>