Estimation of wetland vegetation biomass in the Poyang Lake area using Landsat TM and Envisat ASAR data

Qing Wang; Jingjuan Liao

doi:10.1117/12.873263

3 November 2010 Estimation of wetland vegetation biomass in the Poyang Lake area using Landsat TM and Envisat ASAR data

Qing Wang, Jingjuan Liao

Proceedings Volume 7841, Sixth International Symposium on Digital Earth: Data Processing and Applications; 78411D (2010) https://doi.org/10.1117/12.873263
Event: The Sixth International Symposium on Digital Earth, 2009, Beijing, China

Abstract

The sensitivity of near-infrared band to biomass decreases with the increase of vegetation density, while there is no significant change in red spectral reflectivity. Using SAR data to quantify the biomass usually suffers from the influence of soil humidity, surface conditions, especially those areas with low and middle biomass, resulting in the phenomenon that different biomass have the same or approximate total radar backscattering coefficient. In this paper, we have done research on the sensitivity to the biomass for three kinds of vegetation indices NDVI, RVI and DVI, and improved parameters of MIMICS model to simulate scattering components, setting up the simulation database of all backscattering components. And then we used Landsat TM and ENVISAT ASAR alternating polarization data with their reciprocal advantages, selecting the difference vegetation index DVI=0.45 as the threshold to divide the wetland plant into two parts. For DVI<0.45, we apply the statistical analysis methods to build a linear regression model with samples. For DVI>=0.45 the areas with high leaf density, it can be estimated by using C-band approximate microwave scattering models. Finally the entire wetland biomass of Poyang Lake is approximately 2.1×10⁹ kg.

Citation Download Citation

Qing Wang and Jingjuan Liao "Estimation of wetland vegetation biomass in the Poyang Lake area using Landsat TM and Envisat ASAR data", Proc. SPIE 7841, Sixth International Symposium on Digital Earth: Data Processing and Applications, 78411D (3 November 2010); https://doi.org/10.1117/12.873263

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