Estimation of snow density using full-polarimetric Synthetic Aperture Radar (SAR) data. (2015) - Surendar, M.; Bhattacharya, A.; Singh, G.; Venkataraman, G.
Highlights: The use of full polarimetric SAR data. The use of generalized four component polarimetric decomposition. Estimation of snow density. Validation with near-real time in-situ measurements. Abstract: In this paper, a new snow density estimation methodology is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized volume parameter is utilized to invert snowpack dielectric constant using the Fresnel transmission coefficients. The snow density is then estimated using an empirical relationship. Six Radarsat-2 fine resolution full-polarimetric C-band datasets were acquired over Himachal Pradesh, India. The near-real time in-situ measurements were collected with the satellite pass to validate the proposed method. The mean absolute error (MAE) of the proposed method is 0.027 g cm −3 and the root mean square error (RMSE) is 0.032 g cm −3 . The snow density variation within a season were also analyzed using multi-temporal Radarsat-2 data.