Integration of Multi-Source Images for Improving Spatial Resolution of Snow Depth Detection in Western China

Snow depth is one of the most important parameters in snow cover studies. Although passive microwave remote sensing imagery has been widely used for detecting snow depth in a large area, the accuracy is limited due to the coarse spatial resolution especially in complex terrain areas. This paper aims to improve the spatial resolution of snow depth detection by integrating multi-source remote sensing data, such as optical snow extent and passive microwave brightness temperature data. With the assist of snow extent product with higher spatial resolution, a linear unmixing method is adopted for improving mixed pixel problem in passive microwave images. Snow extent is not only utilized for identifying the proportion of different components in a mixed pixel but also for indicating their spatial locations. Illustrated with a case study in western China, the spatial resolution of snow depth detection is increased with pixel size from 0.25 degree to 0.05 degree. The proposed method shows that integrating higher resolution optical product is an effective means for improving the spatial resolution of snow depth detection.