Snow cover monitoring and snow density estimation using ALOS-PALSAR data

Snow cover mapping is a very important parameter for snowmelt runoff modeling and forecasting. Snow cover information is also useful for managing transportation and avalanche forecasting. This study will discuss the capability of full polarimetric L-band ALOS PALSAR data for snow classification. Therefore, Polarimetric decomposition and the complex Wishart classifier will be applied on ALOSPALSAR data. Results will be compared with the optical data simultaneously. For snow density estimation, IEM model based inversion model will be adopted. Inversion model requires HH and VV polarization combination data. The radar backscattering from a vegetated surface will have the integrated effect of the vegetation and underlying snow. To improve the results obtained from the inversion model in vegetated area, vegetation correction will be applied to inversion model. For this purpose, HV polarization data is essential. Hence, ALOS PALSAR full polarimetric data will be used for this study. Survey of India (SOI) topographical sheet in 1: 50000 scale will be used for preparation of elevation, road and settlement maps and for the registration of satellite data. A number of maps viz: DEM, slope, aspect etc. will be derived based on respective thematic maps using GIS techniques. Field data will be collected synchronous with satellite passes. The PALSAR backscattering coefficient and incidence angle will be used in the inversion model. The inversion model gives the snow dielectric constant which can further be related to snow density using Looyenga’s semi-empirical formula.