A dense-medium insar correlation model with its application to the problem of snow characteristics retrieval

Snow characteristics, such as Snow Water Equivalent (SWE) and snow grain size, are essential to monitor the global hydrological cycle and thus an indicator of climate change. This paper demonstrates an InSAR scattering model for dense medium such as snow considering the multiple scattering effect through the use of Quasi-Crystalline Approximation (QCA) and Percus-Yevick pair distribution function. Based on the simplified versions of the model, simulated results are shown for the problem of snow characteristics retrieval. First, it is noticed that the Ka-band InSAR phase has better sensitivity to the snow grain size, while the L-band InSAR phase has better sensitivity to the snow depth. Then, the Ka- and L-band InSAR correlation measurements are utilized to retrieve the snow volume parameters along with the ground parameters simultaneously. The InSAR scattering model and the retrieval approach proposed in this paper can be a complimentary tool for other techniques of retrieving snow characteristics.