Snow grain size estimation in Himalayan snow covered region using advanced synthetic aperture radar data

Abstract

The measurement of snow parameters is important for hydrological modeling. Spatial and temporal changes in snow grain size can help us to characterize the thermal state of snow pack and to estimate the timing and spatial distribution of snowmelt. This paper discusses the methodology of Advanced Synthetic Aperture Radar (ASAR) data analysis for estimating snow grain size. In this investigation, we have used ENVISAT-ASAR image mode SLC data in HH-polarization with incidence angle range 39.1 °- 42.8 ° of 31 st January 2006. Survey of India (SOI) topographical sheet (52H3) in 1:50,000 scale is used for preparation of digital elevation model (DEM) and for the registration of satellite data. Field data were measured synchronous with satellite pass. Envisat-advanced synthetic aperture radar single polarized, single look complex (SLC) data have been processed for backscattering coefficient image generation. Incidence angle image was extracted from the ASAR header data using interpolation method. These images were multi-looked 5 times in azimuth and 1 time in range direction. ASAR Backscattering coefficient images have been calibrated. The scattering and absorption efficiencies of an ice particle are only weakly dependent on the shape of the particle. A Snowflake, although non-spherical in shape, may be treated using the Rayleigh expression for a spherical particle of the same mass provided the Rayleigh condition applies. This study has been done using Rayleigh scattering condition based model. The effect of snow grain size on backscattering coefficient is studied in detail. The comparison of ASAR C-band estimated value with field grain size measurement shows an absolute error of 0.045 mm and relative error 9.6%. Backscattering coefficient increases as the grain size increases with elevation.