Sensitivity of ALOS/PALSAR imagery to forest degradation by fire in northern Amazon

Abstract

We evaluated the sensitivity of the full polarimetric Phased Array type L-band Synthetic Aperture Radar (PALSAR), onboard the Advanced Land Observing Satellite (ALOS), to forest degradation caused by fires in northern Amazon, Brazil. We searched for changes in PALSAR signal and tri-dimensional polarimetric responses for different classes of fire disturbance defined by fire frequency and severity. Since the aboveground biomass (AGB) is affected by fire, multiple regression models to estimate AGB were obtained for the whole set of coherent and incoherent attributes (general model) and for each set separately (specific models). The results showed that the polarimetric L-band PALSAR attributes were sensitive to variations in canopy structure and AGB caused by forest fire. However, except for the unburned and thrice burned classes, no single PALSAR attribute was able to discriminate between the intermediate classes of forest degradation by fire. Both the coherent and incoherent polarimetric attributes were important to explain AGB variations in tropical forests affected by fire. The HV backscattering coefficient, anisotropy, double-bounce component, orientation angle, volume index and HH-VV phase difference were PALSAR attributes selected from multiple regression analysis to estimate AGB. The general regression model, combining phase and power radar metrics, presented better results than specific models using coherent or incoherent attributes. The polarimetric responses indicated the dominance of VV-oriented backscattering in primary forest and lightly burned forests. The HH-oriented backscattering predominated in heavily and frequently burned forests. The results suggested a greater contribution of horizontally arranged constituents such as fallen trunks or branches in areas severely affected by fire.