ARTICLES

Estimation of Aboveground Biomass in Arid Region with ASAR Data and TM Data:A Case Study over the Reed Vegetation of Wutumeiren Prairie, Qinghai Province

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  • School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China

Received date: 2013-04-02

  Revised date: 2013-04-23

  Online published: 2014-03-10

Abstract

Grasslands are important renewable resources in ecosystems of arid areas. As one of the important components of prairie ecosystems, aboveground biomass is the key indicator of health status of the prairie ecosystems. Comparing to the significant limitations of the traditional method of biomass, the satellite remote sensing provides a unique effective and efficient means in biomass monitoring and assessment. In this paper, we proposed a retrieval methodology for herbaceous vegetation biomass based on the vegetation structure characteristic and Michigan Microwave Canopy Scattering (MIMICS) model using the ASAR and TM data. A two-layer canopy reflectance model (ACRM) was used to inverse the Leaf Area Index (LAI) which can be easily retrieved from the optical remote sensing data. Then LAI was used to get the number of plants per unit area. The aboveground biomass served as an input parameter was input into the adaption of MIMICS model which adopted for characterizing the backscatter from herbaceous vegetation by deleting the scatter component associated with ground-trunks. Then, based on established equations which used the dual-polarized radar data, the aboveground biomass was calculated using the lookup table. The method was applied to retrieve the biomass of Wutumeiren prairie, Qinghai Province. Results indicated that the method was of the operational potential in aboveground biomass of the herbaceous vegetation in arid region. And a good accuracy of the biomass retrieval was achieved (R2=0.8562, RMSD=0.6263). Finally, we analyzed the error sources of biomass estimation using this method. The sources of error might be come from two aspects, i.e. error of the input model parameters, and the ill-posed inversion problem, for which, the mean value was used as the inverse results when the solution is not unique.

Cite this article

XING Minfeng, HE Binbin . Estimation of Aboveground Biomass in Arid Region with ASAR Data and TM Data:A Case Study over the Reed Vegetation of Wutumeiren Prairie, Qinghai Province[J]. Journal of Geo-information Science, 2014 , 16(2) : 335 -340 . DOI: 10.3724/SP.J.1047.2014.00335

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