| Abstract | The presence of a snow cover affects the regional and global energy balance, having a significant impact on the climate system. Monitoring and forecasting snow melt is an essential activity, providing
knowledge of the hydrological cycle for flood prediction, water supply management, hydroelectric power facilities, and agricultural activities. Microwave remote sensing techniques have successfully monitored snow pack parameters, with its all-weather
imaging capabilities and sensitivity to changes in the dielectric constant within a snow pack. Backscatter values from active sensors and brightness temperatures from passive sensors respond to the snow state and structure, allowing the retrieval of
snow pack parameters. A variety of snow conditions, during the 1997-98 winter season, were captured by Synthetic Aperture Radar (SAR) and passive microwave radiometer airborne flights, over a study area in Eastern Ontario, Canada. A Total of four
dates of C-band SAR and five dates of the passive sensor (recording at 19, 37, and 85 GHz) data were collected over the season. This research initiative is a collaborative investigation between Atmospheric Environment Service (AES), a department of
Environment Canada and the Canada Centre for Remote Sensing (CCRS). The multi-temporal and multi-sensor data sets were analysed with respect to changes in radar backscatter and brightness temperatures as a function of snow pack parameters. Changes in
weather conditions and snow state resulted in some polarimetric parameters showing significant differences, while others resulted in little or no differences. Brightness temperatures and Snow Water Equivalent (SWE) algorithms did exhibit differences
between the two dates due to the differences in snow structure and temperature. Through the integration of passive and active microwave remote sensing techniques, a better understanding of the interaction of microwave radiation and snow pack
characteristics can be obtained. |