Characterization of Forests in Western Sayani Mountains, Siberia from SIR-C SAR Data

This paper examines the use of space-borne radar data to map forest types and logging in the mountainous Western Sayani area in central Siberia. L- and C- band HH-, HV-, and VV-polarized images from the Shuttle Imaging Radar–C instrument were used in the study. Techniques to reduce topographic effects in the radar images were investigated. These included radiometric correction using illumination angle inferred from a digital elevation model and reducing apparent effects of topography through band ratios. Forest classification was performed after terrain correction utilizing typical supervised techniques and principal component analyses. An ancillary data set of local elevations was also used to improve the forest classification. Map accuracy for each technique was estimated for training sites based on Russian forestry maps, satellite imagery, and field measurements. The results indicate that it is necessary to correct for topography when attempting to classify forests in mountainous terrain. Radiometric correction based on a digital elevation model improved classification results but required reducing the synthetic aperture radar resolution to match the digital elevation model. Using ratios of synthetic aperture radar channels that include cross-polarization improved classification and had the advantages of eliminating the need for a digital elevation model and preserving the full resolution of the synthetic aperture radar data.