Dependence of Forest Biomass on the order of parameter of K-distribution of High Resolution Airborne Polarimetric SAR Images of Forests

Abstract

A summary is presented on the study of searching parameters that describe the relation between high-resolution SAR images and forest parameters. The results are based on the non-Gaussian texture analysis of the polarimetric airborne NICT/JAXA Pi-SAR data acquired in November 2002 over the Tomakomai forests in Hokkaido, Japan. The RCS (radar cross section) in terms of tree biomass is first analyzed. The image amplitudes distributions are then investigated; and among Rayleigh, log-normal, Weibull and K-distributions, the K-distribution is found to fit best to the data of all polarizations, although the Weibull distribution fits equally well. Further, there is a strong correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images. A remarkable feature of this result is that the order parameter increases consistently with biomass to approximately 100 tons/ha and possibly above, which is well beyond the saturation limits of the radar cross section (approximately 40 tons/ha for L-band RCS). Thus, the order parameter of the K-distribution can be an effective parameter to estimate tree biomass from high-resolution SAR data in a much wider range than the conventional RCS method.