Evaluation of MODIS Snow Products in Southwestern Xinjiang Using the Google Earth Engine

Google Earth Engine(GEE) is a cloud\|based geospatial processing platform that can analyze geospatial data to achieve parallel processing of massive remote sensing data on a global scale，providing support for remote sensing big data and large\|area research.MODIS snow cover mapping is a global snow cover product established using MODIS data and has been widely used in regional and global climate and environmental monitoring.In the GEE，millions of remote sensing images are stored，including MODIS daily snow products MOD10A1 V5 data and Landsat data.Taking the three research areas in southwestern Xinjiang as examples，the Landsat stored by the GEE were selected，and the NDSI was used to extract the snow cover as the true value of the land cover to evaluate the MOD10A1 accuracy.The results show that the average overall accuracy of MOD10A1 in the snow cover season in southwestern Xinjiang during the period from 2000 to 2016 is 82%，the average misjudgment rate is 2.9%，and the average missed rate is 58.8%.The overall accuracy of MOD10A1 can reach 98% under the clear sky conditions.The accuracy of MOD10A1 is effected by the terrain conditions and cloud cover in different regions.Therefore，the GEE can quickly and effectively filter high quality cloudless Landsat images，and evaluate the accuracy of the MOD10A1 in the snow area around the global regions，displaying intuitively the misjudgment and missed areas in the form of online maps.Meanwhile，GEE provides the Landsat simple cloud score function to calculate the regional cloud cover，which makes the influence of cloud cover on the MOD10A1 accuracy assessment more regionally representative.