Forest variable estimation from fusion of SAR and multispectral optical data

Radar and optical remote sensing data are used in a unified algorithm to estimate forest variables. The study site is the H. J. Andrews experimental forest in Oregon, which has significant topography and several mature and old-growth conifer stands with biomass values sometimes exceeding 1000 tons/ha. Polarimetric multifrequency Airborne Synthetic Aperture Radar (AIRSAR) backscatter, interferometric C-band Topographic Synthetic Aperture Radar (TOPSAR) coherence, and multispectral Landsat Thematic Mapper (TM) digital numbers are used in a regression analysis that relates them to forest variable measurements on the ground. Parametric expressions are derived and used to estimate the same variables(s) at other locations from the combination of AIRSAR and TM data. It is shown that the estimation accuracy is significantly improved when the radar and optical data are used in combination compared to estimating the same variable from a single data type alone.