Preparation And Application Of MODIS No-cloud Snow Cover Products In China

The seasonal snow cover in China is an important water supply for many large rivers,and the wide range of snow cover affects the climate and environment changed in China.Therefore the snow cover is an important input factor for many hydrological and climate models.The new sixth version of MODIS(V6),released by the National Snow and Ice Data Center(NSIDC),offers the Normalized Snow Index(NDSI).Users can set thresholds according to the demand to produce the products.But the complex and varied land cover types influences the NDSI thresholds and the single NDSI threshold does not accurately identify snow in the vegetation concentration area;In addition,cloud is also an important factor to affect the snow cover acquisition.So V6 products can't meet the need of users.Based on the above reasons,this study mainly based on MODIS data,using land cover types to prepare the L1 level products,then to fill a large amount of data gaps to prepare L2 level products-a long time series no-cloud snow cover products in China.It has higher accuracy and is not affected by cloud,which has more important significance for hydrology and climate research.Specific research contents and major innovations are as follows:(1)Preparation of MODIS daily products in the no-cloud snow cover of China.1)we use Landsat data to extract snow pixel and non-snow pixel as a true value data,extract and optimize the NDSI and NDVI threshold under different land cover types of forest area and non-forest area,then to preparation L1 level products.2)we use the gap value fill method to preparation L2 level products.The study based on Terra and Aqua satellite synthesis method,HMRF model and snow cover equivalent product interpolation method to fill gap and preparation L2 level products-a set of MODIS daily products in the no-cloud snow cover of China.(2)The validation of L1 level and L2 level product.1)The snow depth data of meteorological stations and Landsat image data to use to validate the accuracy of L1 level products based on clear sky conditions.The research results showed that the overall accuracy of MOD?OPT?SCA and MYD?OPT?SCA snow products is 92.44%,92.80% and 84.73%,80.61%,respectively.The the overall accuracy of MOD?V6?SCA and MYD?V6?SCA Snow Cover products is 90.54%,92.58% and 82.88%,73.99%,respectively.Combined with the snow depth data of meteorological stations,the overall accuracy of no cloud snow cover of L2 level products is evaluated.The result shows that the L2 level products can basically meet the needs of users beasuse the overall accuracy reach more than 90%.(3)Based on the no cloud MODIS Snow Cover products,the temporal and spatial changes of China's snow cover,snow cover days and snow cover trend in2000-2018 were analyzed.In this paper,only for different land cover types to optimize the single snow thresholds,the influencing factors are too single;In addition,combining HMRF snow model to reclassify the cloud pixels of MODIS Snow Cover products,only combining the temporal and spatial information to distinguish may lead to inaccurate classification.In view of these problems,the following aspects can be considered in future research: terrain,different snow depth,altitude difference and other factors can be considered for snow threshold;spectral information and environmental factors can be added to HMRF snow model.