Estimating Forest Above-Ground Biomass in Central Amazonia Using Polarimetric Attributes of ALOS/PALSAR Images

Polarimetric synthetic aperture radar (SAR) images are essential to understand forest structure and plan forest inventories with the purpose of natural resource management and environmental conservation efforts. We developed a method for estimating above-ground biomass (AGB) from power and phase-radar attributes in L-band images. The model was based on the variables P-v (from Freeman-Durden decomposition) and s degrees(HH), complemented by the attributes of Touzi decomposition a(S)(2), t(m), f(S)(3), and f(S)(2). The analyses demonstrated the contribution of volumetric, multiple, and direct scattering resulting from the interaction between the signal and the random structure of canopies and their forest biomass. The proposed model had good predictive capacity and a positive correlation (R-2 = 0.67 and = 0.81, respectively), with Syx = 56.9 Mg ha(-1) and a low average estimation error of 7.5% at R-2 = 0.81 in the validation. An additional exploratory analysis of the parallel polarimetric responses did not reveal a defined pattern for the different phytophysiognomies-although all indicated a predominance of multiple and/or volumetric scattering. This fact can be related to the floristic and structural variation in the primary forest units, the degree of human intervention in legal logging, and the differences among succession stages.

Automated summary

We developed a method for estimating above-ground biomass (AGB) from polarimetric SAR images. The model used power and phase-radar attributes, as well as attributes from Touzi decomposition. The proposed model showed good predictive capacity and a positive correlation with the validation results.