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

Satellite remote sensing can be used to investigate spatially distributed hydrological states for use in modeling, assessment, and management. However, in the visual wavelengths, cloud cover can often obscure significant portions of the images. This study develops a rule-based, multistep method for...

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Published in:Hydrology and earth system sciences 2013-05, Vol.17 (5), p.1809-1823
Main Authors: López-Burgos, V, Gupta, H. V, Clark, M
Format: Article
Language:English
Subjects:
Clouds
Freshwater
Hydrology
Interpolation
Methods
MODIS
Satellite remote sensing
Satellites
Snow
Snow cover
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description Satellite remote sensing can be used to investigate spatially distributed hydrological states for use in modeling, assessment, and management. However, in the visual wavelengths, cloud cover can often obscure significant portions of the images. This study develops a rule-based, multistep method for removing clouds from MODIS snow cover area (SCA) images. The methods used include combining images from more than one satellite, time interpolation, spatial interpolation, and estimation of the probability of snow occurrence based on topographic information. Applied over the upper Salt River basin in Arizona, the method reduced the degree of cloud obscuration by 93.8%, while maintaining a similar degree of image accuracy to that of the original images.
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source Publicly Available Content Database (Proquest) (PQ_SDU_P3); DOAJ Directory of Open Access Journals
subjects Clouds
Freshwater
Hydrology
Interpolation
Methods
MODIS
Satellite remote sensing
Satellites
Snow
Snow cover
title Reducing cloud obscuration of MODIS snow cover area products by combining spatio-temporal techniques with a probability of snow approach
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