Impact and modeling of topographic effects on P-band SAR backscatter from boreal forests

P-band SAR backscatter has been proven to be useful for forest biomass prediction. However, there is a need for further studies on effects of topography on P-band backscatter. In this paper, two prediction models for backscatter are evaluated, one using only biomass as predictor and one which also includes topographic corrections. Data from the BioSAR 2007 and BioSAR 2008 campaigns are used to evaluate the models. A multi-scale error model which is able to handle data from several imaging directions is used. For HH, the slope correction on stand level used in this paper is unable to correct for topographic effects. This is consistent with previous results that within stand topographic variability has a significant impact on HH P-band backscatter. For HV and VV, the model which considers topography gives lower prediction errors than the model which does not include topography. Moreover, for these polarizations topographic the correction strongly reduce the variability in backscatter measurements between imaging directions for stands with ground slopes larger than about 5 degrees

Regression-Based Retrieval of Boreal Forest Biomass in Sloping Terrain using P-band SAR Backscatter Intensity Data

A new biomass retrieval model for boreal forest using polarimetric P-band synthetic aperture radar (SAR) backscatter is presented. The model is based on two main SAR quantities: the HV backscatter and the HH/VV backscatter ratio. It also includes a topographic correction based on the ground slope. The model is developed from analysis of stand-wise data from two airborne P-band SAR campaigns: BioSAR 2007 (test site: Remningstorp, southern Sweden, biomass range: 10-287 tons/ha, slope range: 0-4 degrees) and BioSAR 2008 (test site: Krycklan, northern Sweden, biomass range: 8-257 tons/ha, slope range: 0-19 degrees). The new model is compared to five other models in a set of tests to evaluate its performance in different conditions. All models are first tested on data sets from Remningstorp with different moisture conditions, acquired during three periods in the spring of 2007. Thereafter, the models are tested in topographic terrain using SAR data acquired for different flight headings in Krycklan. The models are also evaluated across sites, i.e., training on one site followed by validation on the other site. Using the new model with parameters estimated on Krycklan data, biomass in Remningstorp is retrieved with RMSE of 40-59 tons/ha, or 22-33% of the mean biomass, which is lower compared to the other models. In the inverse scenario, the examined site is not well represented in the training data set, and the results are therefore not conclusive