Reducing cloud obscuration of MODIS snow cover area products by combining spatio-temporal techniques with a probability of snow approach

摘要

Satellite remote sensing can be used to investigate spatially distributedhydrological states for use in modeling, assessment, and management. However,in the visual wavelengths, cloud cover can often obscure significantportions of the images. This study develops a rule-based, multistep methodfor removing clouds from MODIS snow cover area (SCA) images. The methodsused include combining images from more than one satellite, timeinterpolation, spatial interpolation, and estimation of the probability ofsnow occurrence based on topographic information. Applied over the upperSalt River basin in Arizona, the method reduced the degree of cloudobscuration by 93.8%, while maintaining a similar degree of image accuracyto that of the original images.