Validation of SCA from MOD10A1 and MODSCAG

Over the past 20 years, many algorithms for mapping snow have been developed to map snow in the binary sense and in the fractional sense from optical multi-spectral imagers and imaging spectrometers. These algorithms include band thresholds, band ratios, normalized band differences, empirical relationships with normalized band differences, relative spectral mixture analysis, and multiple endmember spectral mixture analysis. With the introduction of NASA Earth Observation System and its flagship instrument Moderate Resolution Imaging Spectroradiometer (MODIS) came the capacity to better characterize snow cover properties through improved algorithms. Unlike previous instrumentation, the surface reflectance bands of MODIS sample the spectrum of snow-covered surfaces in those wavelengths where the greatest variation occurs and without the saturation in visible wavelengths. The empirical methods of managing water, which are based on historical relationships between point measurements and runoff, are likely to become less accurate. Hence the utility of distributed snowmelt models based on a judicious integration of remotely sensed and surface measurements will consequently increase. However, as the analysis in this paper shows, we analysis the precise of MOD10A1 and MODSCAG based on the ground observation. The result show that 1)the MOD10A1 is mainly affected by cloud and the precise is 90.43% and 72.04% in clear condition and all condition respectly;2)the relationship between snow depth and the precise of both MOD10A1 and MODSCAG is evidently and the precise is 100% when the snow depth is more than 0.5m ;3)the precise is slightly affect by vegetation cover type at the given condition which have deep snow.