Journal
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
Volume 12, Issue 10, Pages 3712-3718Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSTARS.2019.2947088
Keywords
Aboveground biomass (AGB); hybrid polarimetric (Hybrid Pol) SAR; RISAT-1
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Forest plays an important role in carbon sequestration and biosphere-atmosphere interaction. Knowledge of forest biomass content helps in assessing its sustainability and thus mitigating climate change. The advancement in remote sensing technology provides the capability of estimating biomass at a large scale. Hybrid polarimetry has gained significant attention among other radar missions due to its fundamental advantages. In this article, the potential of hybrid polarimetricSARis evaluated for the efficient forest aboveground biomass (AGB) estimation for Barkot Forest, Uttarakhand, India. Forest biomass is calculated by means of the extended water cloud model. Scattering parameters are derived using two widely used hybrid polarimetric decomposition techniques, m-delta and m-chi decompositions. Potential insight into the efficacy of these decomposition techniques toward biomass estimation is brought forth. The modeled AGB estimates were compared with fully polarimetric data-based estimated AGB. The estimation based on the m-chi and m-delta decomposition resulted in biomass estimation with an accuracy of 75.8% and 73.4%, respectively.
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