Assessment of methods for mapping snow cover from MODIS

Characterization of snow is critical for understanding Earth’s water and energy cycles. Maps of snow from MODIS have seen growing use in investigations of climate, hydrology, and glaciology, but the lack of rigorous validation of different snow mapping methods compromises these studies. We examine three widely used MODIS snow products: the ‘‘binary’’ (i.e., snow yes/no) global snow maps that were among the initial MODIS standard products; a more recent standard MODIS fractional snow product; and another fractional snow product, MODSCAG, based on spectral mixture analysis. We compare them to maps of snow obtained from Landsat ETM+ data, whose 30 m spatial resolution provides nearly 300 samples within a 500 m MODIS nadir pixel. The assessment uses 172 images spanning a range of snow and vegetation conditions, including the Colorado Rocky Mountains, the Upper Rio Grande, California’s Sierra Nevada, and the Nepal Himalaya. MOD10A1 binary and fractional fail to retrieve snow in the transitional periods during accumulation and melt while MODSCAG consistently maintains its retrieval ability during these periods. Averaged over all regions, the RMSE for MOD10A1 fractional is 0.23, whereas the MODSCAG RMSE is 0.10. MODSCAG performs the most consistently through accumulation, mid-winter and melt, with median differences ranging from 0.16 to 0.04 while differences for MOD10A1 fractional range from 0.34 to 0.35. MODSCAG maintains its performance over all land cover classes and throughout a larger range of land surface properties. Characterizing snow cover by spectral mixing is more accurate than empirical methods based on the normalized difference snow index, both for identifying where snow is and is not and for estimating the fractional snow cover within a sensor’s instantaneous fieldof-view. Determining the fractional value is particularly important during spring and summer melt in mountainous terrain, where large variations in snow, vegetation and soil occur over small distances and when snow can melt rapidly. 2012 Elsevier Ltd. All rights reserved.