Forests plays a crucial role in storing carbon and are of paramount importance in maintaining global carbon cycle. Assessment of forest biomass at regional and global level are vital for understanding and monitoring health of both tree species and entire forest cover. The changes in forest biomass are caused as a consequence of human activities, natural factors and variations in climate. Thus, forest biomass quantification is necessary for gauging the changes in forest ecosystems. Remote sensing techniques have become an indispensable tool for mapping forest biophysical parameters. The focus of this research is to map Aboveground Biomass (AGB) over Barkot forest range in Dehradun, India, utilising microwave remote sensing techniques along with the retrieval of PolInSAR based scattering information for the estimation of AGB. Radarsat-2 fully polarimetric C-band data and a semi-empirical Extended Water Cloud Model (EWCM) is utilized for AGB estimation in Barkot forest area since it takes into account the ground-stem interactions which are not modelled in Water Cloud Model (WCM). The open source tool PolSAR pro has been utilized for SAR image processing and retrieval of EWCM parameters namely, ground stem backscatter, ground backscatter, vegetation backscatter, total forest backscatter and empirically defined coefficient for the estimation of AGB. The POA shift compensation is implemented over the PolInSAR pair to minimize the overestimation and underestimation problem. The results shows that coefficient of determination (R2) value of 0.47, root mean square error (RMSE) of 56.18 (t ha-1) and accuracy of 72% has been obtained with the modelled biomass against the field biomass. It can be inferred from the obtained results that PolInSAR technique, in combination with semi-empirical modelling approach, can be implemented for estimating forest biomass. The research highlights the huge potential of PolInSAR based scattering retrieval for semi-empirical modelling (EWCM) for modelling the AGB in a tropical forest.
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