Relating SAR image texture and backscatter to tropical forest biomass

Twenty six texture measures (derived from local statistics, grey-level co-occurrence matrix (GLCM), sum and difference histogram (SADH) and variograms) were calculated for simulated images and their ability to discriminate image texture independently of image contrast was determined. The seven texture measures able to discriminate texture independently of contrast (and therefore able to estimate biomass independently of backscatter) were entropy (derived from local statistics), contrast, entropy, correlation and chi-square (derived from the GLCM), mean of sum vector (derived from the SADH) and range (derived form the variogram). These measures were calculated for Japanese Earth Resources Satellite (JERS-1) Synthetic Aperture Radar (SAR) images and related to the biomass of regenerating forest and mature forest plots from two study areas in Brazilian Amazonia. It was hypothesised that texture (a measure of both biomass and canopy unevenness) could be related to tropical forest biomass up to and beyond the saturation of the backscatter/biomass relationship. The results showed that only GLCM derived contrast increased the correlation between backscatter and biomass. The combination of GLCM contrast with backscatter has the potential to increase the accuracy of biomass estimation over the use of backscatter alone.