Retrieval of snow depth in northeast China using FY-3B/MWRI passive microwave remote sensing data

Abstract

Comparing with optical remote sensing techniques, passive remote sensing data have been proved to be effective for observing snowpack parameters such as snow depth and snow water equivalent, which can penetrate snowpack without clouds interferences. The Microwave Radiation Imager (MWRI) loaded on the Chinese FengYun-3B (FY-3B) satellite is gradually used in the global environment research through November, 2011. In this paper, we proposed a snow depth retrieval algorithm to estimate snow depth in Northeast China using MWRI passive microwave remote sensing data. A decision tree method of snow identification was firstly designed to distinguish different snow cover conditions in order to eliminate other interference signals. After using the proposed decision tree method, the processing results were further used to retrieve the snow depth in Northeast China. Finally, the practical snow depth data and the MODIS data were collected for the accuracy assessment of the proposed snow depth retrieval method. The experimental results demonstrated that the RMSE of snow depth used the proposed method was approximately 3 cm in Northeast China.