Snow wetness estimation from dual polarimetric coherent TerraSAR-X data

In this paper, a new snow wetness estimation methodology is proposed for dual-coherent polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering components in the wet-snow conditions. These components, with a limit of penetration depth of high frequency SAR, have been taken into account to estimate the snow-pack wetness. In this new methodology, snow surface wetness has been estimated using the IEM scattering model and snow volume wetness has been estimated under the Rayleigh scattering assumption. The estimated snow wetness is validated using the in-situ field measurements, which were collected synchronous with the satellite pass. In this study we have used dual-coherent TerraSAR-X data acquired over Solang, on 23 January 2009, Himachal Pradesh, India. Typically the snow wetness ranges from 0% to 15% by volume. On comparison with ground measurements, the proposed method shows that the mean absolute error in snow wetness inferred from the SAR imagery was 1.63% by volume.