Spatial Wavelet Statistics of SAR Backscatter for Characterizing Degraded Forest: A Case Study From Cameroon

摘要: Forest degradation is an important issue in global environmental studies, albeit not yet well defined quantitative terms. The present work addresses the problem, by starting with assumption that forest spatial structure can provide indication of process degradation, this being reflected statistics synthetic aperture radar (SAR) backscatter observations. capability characterizing landcover classes, such as intact and degraded (DF), tested supervised analysis ENVISAT ASAR ALOS PALSAR statistics, provided wavelet frames. test conducted a closed semideciduous Cameroon, Central Africa. Results showed variance scaling signatures, which are measures SAR two-point combined space-scale domain, able to differentiate classes capturing their distribution. Discrimination between DF was found be enabled functional signatures C-band data. Analytic parameters, describing form when fitted third-degree polynomial, resulted statistically significant difference DF. results PALSAR, on other hand, were significant. technique sets stage for promising developments tracking disturbance, especially future availability data ESA Sentinel-1.