Snow cover is an important part on earth surface, 3/4 of the fresh water on earth exits in the form of snow and ice. In winter, 80% of the Eurasia and North America is covered by snow, and the average snow cover area of the hemisphere in January is about 46500000 km2, and 3800000 km2 in August. In high latitude area, snow is the main source of river and underground water.
Snow is also an important parameter for meteorology, hydrology and climate studies, and plays an important role in the earth’s water and energy circulation.
Microwave can penetrate the snow cover on land, moreover, the microwave has high transmissivity in the atmosphere, so this made the monitoring of snow depth information using passive microwave observations possible. When snow exists on land, there are scatterings and absorptions of the microwave emission signal of soil surface and snow cover, so that the brightness temperature sensed by the microwave radiometer onboard satellites contains information referring to snow, such as the snow density, snow temperature, depth, grain size and grain size distribution.
The monitoring of snow using passive microwave remote sensing begins with the SMMR onboard the Nimbus-7 satellite in 1978, and then spaceborne passive microwave sensors such as SSM/I and AMSR-E are used for global snow monitoring. The passive microwave model of snow covered terrain can predict the brightness temperature sensed by the radiometer based on the snow parameters, soil parameters and sensor parameters.
Snow parameters retrieval can be achieved based on backscattering observation of snow covered terrain based on SAR or scatterometers. The active microwave model of snow covered terrain can predict the backscattering coefficient of the snow-soil system.
Due to the light scattering in snow, the snow surface reflectance changes with snow parameters. The optical remote sensing of snow can be used for snow grain size retrieval. The optical snow remote sensing model can predict the albedo and BRDF based on snow parameters.
