Snow Depth Retrieval Based on a Multifrequency Passive Microwave Unmixing Method for Saline-Alkaline Land in the Western Jilin Province of China

Abstract

Passive microwave data of a snow-covered land surface received by a passive microwave radiometer is composed of microwave radiation from the snow cover and the underlying surface. The western Jilin Province of China is an important area with seasonal snow. Here, the land cover types mainly include characteristically saline-alkaline farmland and grassland. The main aim of this paper is to obtain more accurate snow depth (SD) data in the western Jilin Province of China. First, a multifrequency passive microwave unmixing method is proposed for the study area. Second, based on Fengyun-3B microwave radiation imagery (MWRI) data and advanced microwave scanning radiometer 2 (AMSR2) data, the SD retrieval results are evaluated using four methods: using MWRI data with Foster's algorithm and with the standard MWRI algorithm, and using the AMSR2 data with Foster's algorithm and with the standard AMSR2 algorithm. The experimental results demonstrate that using MWRI data with the standard MWRI algorithm yields the highest accuracy for SD retrieval, with average bias and root-mean-square-error (RMSE) values of approximately 6.9 and 7.5 cm, respectively. Finally, we combined the unmixing method with the optimal SD retrieval method, and obtained more accurate SD data for the study area. Using MWRI data with the standard MWRI algorithm, the average bias and RMSE improved by approximately 9.7% and 7% when using the unmixed pixels compared with using the original mixed pixels.