Biophysical properties and mapping of aquatic vegetation during the hydrological cycle of the Amazon floodplain using JERS-1 and Radarsat

Field measurements were combined with Synthetic Aperture Radar (SAR) images to evaluate the use of radar for estimating biomass changes and mapping of aquatic vegetation in the lower Amazon. Field campaigns were conducted concomitant to the acquisition of Radarsat and JERS-1 images at five different stages of the hydrological cycle. The temporal variability of the SAR data for aquatic vegetation shows a dynamic range of 5 dB, however this is due dominantly to the significant differences (p<0.05) between the low water season when vegetation is small and just emerging and other seasons when vegetation is fully developed. The spatial variability of the above-water biomass is detectable with radar data. Significant correlation (p<0.05) exist between backscattering coefficients and both above-water dry biomass and height of the plants. The logarithmic relationship between backscattering coefficients and biomass suggests that (1) at low biomass, high transmissivity of the microwave radiation through the vegetation canopy occurs and the backscattering is a result of quasi-specular reflection of both C and L bands and a minor contribution of canopy volume scattering from C band; (2) at intermediate levels of biomass, moderate changes in backscattering values occur and the saturation point of backscattering is reached; and (3) at high biomass, the transmissivity of C and L band radiation is equally attenuated and backscattering approaches similar values for both. A combination of Radarsat and JERS-1 images from high and low water periods were classified using a segmentation algorithm and had an accuracy higher than 97% for vegetated areas of the floodplain. Although further research is needed to better understand the saturation points for Radarsat and JERS-1 data, these findings clearly show that C and L bands can accurately map aquatic vegetation of the Amazon floodplain.