Multi-sensor Snow Cover Mapping and Emergency Assessment of the Snow Disaster in Xinjiang

Accurate and timely extraction of snow cover information is of great significance in the monitoring and assessment of snow disasters. However, remote sensing observations in snowing weathers were susceptible to the impacts of clouds and atmospheric water vapor, consequently snow parameters mapping from remote sensing data usually became difficult. This study presents an integrated approach for snow cover mapping by combining the two MODIS acquisitions and passive microwave sensor data collected in a day. For purposes of validation, the daily Terra and Aqua MODIS surface reflectance and AMSR-E brightness temperature data of January, 2010 were used in snow cover mapping and snow depth estimation in Xinjiang, China. Comparison between the results using the proposed approach and the observational data acquired in the metrological stations of Xinjiang indicates that the accuracy of the retrieval of snow parameters is 80.5%, and can combine the advantages of both optical and microwave remote sensors. Afterwards, the proposed approach was used to extract the snow covers and depth information in a typical heavy snow process in Xinjiang from Nov. 30 to Dec. 18, 2012. A simple assessment model was built based on the retrievals and used to evaluate the disaster situation. Field check in the north Xinjiang in January, 2013 showed that the results could be used in the early evaluation of the snow disaster management.