LAUSR

Evaluation of forest biomass is required for sustainable forest management, efficiency valuation and exploring variations in carbon resources. In this research, we studied the possibility of polarimetric synthetic aperture radar (PolSAR) features in order to approximation of forest biomass in Hyrcanian forests. Our study sought to resolve the following inquiries: (1) Does the relevance between aboveground biomass (AGB) and SAR features depend on forest type and structure? (2) Does the use of polarimetric decomposition components elevate the saturation point of SAR response to biomass? (3) What are the most impressive texture parameters for mapping Hyrcanian vegetation biomass? For this purpose, we recorded 115 circular sample plots with 0.1 ha area in four sites, with various forest structures and biomass. Quad-pol PALSAR-2 data were used to apply decomposition methods and investigate the relationship between AGB and PolSAR attributes. To measure the efficiency of PolSAR data for biomass estimation, we used regression analysis, in which second-order and linear models were fit to forecast biomass per hectare, as defined from the field computations. Our results indicated that decomposition features have a high ability to enhance the saturation point and can produce more favorable outcomes than the backscatter coefficients for biomass estimation. Experimental results showed that the response of backscattering coefficients to biomass is affected by the forest type and canopy structure. These findings confirmed that the HH polarization backscatter is better suited for sparse areas, while HV polarization backscatter is qualified for dense areas.