## 4 Results
### Analysis of the Mechanism Responsible for the SZA Effect  
The mechanism responsible for the SZA effect was investigated using paired-date data points situated in the first quadrants of the aforementioned scatter plots. Data collected on 14 and 15 August 2004, during the snow-melting period, were chosen in this case. The SCA data for each day in same subwatershed were compared directly to calculate the amount of SCA on the second day. For each pixel of the overestimated area, the reflectance value differences between both days were plotted against the SZA differences for both days (Figure 5).  
Figure 5a shows that the Band-4 reflectance differences were negative, indicating that all such reflectance values decreased in the overestimated SCA following SZA increases. The average, maximum, and minimum values of the decreased reflectance were around \(-0.4\), \(0.0\), and \(-0.95\), respectively. The reflectance differences at Band 6 mainly ranged from \(-0.42\) to \(-0.1\), indicating that all such reflectances similarly decreased in the overestimated SCA when the SZA increased, although to a lesser degree. The average, maximum, and minimum values of the decreased reflectance at Band 6 were around \(-0.25\), \(-0.05\), and \(-0.51\), respectively. Thus, the magnitude of decrease was larger for Band 4 than for Band 6.  
Such unequal variation in reflectance between Bands 4 and 6 are interpreted as representing the spectral reflectance of snow being higher at green bands than at red bands, which has been corroborated by field-based experiments showing that different wavelengths produced different reflectances at different SZA values [29]. The Algorithm Theoretical Basis Document for the MODIS Snow and Sea Ice-Mapping of a non-Lambertian reflector states that snow's anisotropy might result in some errors  
Figure 5: Scatter plots of: (**a**) the reflectance difference between 15 August 2004 (Day 2), and 14 August 2004 (Day 1), at Band 4 versus that at Band 6 for increased sensor zenith angle (SZA); and (**b**) the normalized difference snow index (NDSI) value in overestimated snow cover area (SCA) on Day 2 versus that on Day 1 for increased SZA. The color bar indicates the corresponding increase of the SZA value on the overestimated snow cover pixels.  
when mapped at large view angles [30]. The optical path through the atmosphere increases with higher values of SZA and shorter wavelengths, producing a larger bias in the Lambert reflectance [31].  
The different magnitudes of change at Bands 4 and 6 revealed an increased NDSI value in each pixel. Figure 5b shows that the NDSI value on the first day was mainly between \(-0.6\) and \(0.4\), whereas on the second day, it was mainly between \(0.4\) and \(0.8\). It is known that the NDSI value is critical for SCA identification using MOD10A1 data because the algorithm defines snow-covered pixels as those with an NDSI value of \(>\)0.4. Such an NDSI increase on the second day erroneously labeled pixels as snow covered, when in reality, this could not be the case in an area where no previous snowfall had been documented on the previous day during the snow-melting period. We therefore concluded that the main reason for SCA overestimation was a false increase in NDSI values caused by the different responses of Bands 4 and 6 to MODIS data when the SZA increased.