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Simultaneous field data collections and Advanced Land Observing Satellite/Phased Array type L-band Synthetic Aperture Radar (PALSAR) full polarimetry observations were performed in Ulaanbaatar (Mongolia) and Alaska (USA). Permafrost is present at the Alaska test sites. Backscattering copolarization ( σco-pol0) values derived from the PALSAR data were compared with those calculated using the integrated equation method (IEM) model, a popular theoretical model describing surface scattering. PALSAR data taken in Ulaanbaatar matched the IEM model results to within a few decibels, whereas data taken in Alaska were 5 to 7 dB lower than those calculated using the IEM model. On the other hand, the σcross-pol0 (σVH0) components estimated from the Oh model were well matched to the PALSAR data in both Ulaanbaatar and Alaska. Moisture levels of the sphagnum moss layer in Alaska were estimated to be about 10% while moisture levels of the underlying organic and mineral layers were 25% to 79%; the moisture values of the organic and mineral layers were factored into the IEM and Oh models. When surface moisture levels of 10% were assumed for Alaska ground conditions, the σco-pol0 values calculated using the IEM model and those derived from the PALSAR data were well matched. From these observations, we conclude that the sphagnum moss layer, which is a seasonally unfrozen layer that occurs above permafrost, plays an important role in radar backscattering processes in permafrost regions and is a main contributor to the σco-pol0 backscattering component; the underlying organic and mineral layers contribute mainly to the σcross-pol0 backscattering component. A two-layer model was applied to the data from a test site in Alaska; the model described the co- and cross-polarization backscatter (σ0) derived from PALSAR data with off-nadir angles of 21.5° and 34.3°. [ABSTRACT FROM AUTHOR]

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the L-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and K-distributions, the K-distribution is found to fit best to the L-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the K-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the L-band RCS. Thus, the order parameter of the K-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method [ABSTRACT FROM PUBLISHER]