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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 17, issue 5
Hydrol. Earth Syst. Sci., 17, 1809–1823, 2013
https://doi.org/10.5194/hess-17-1809-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Statistical methods for hydrological applications

Hydrol. Earth Syst. Sci., 17, 1809–1823, 2013
https://doi.org/10.5194/hess-17-1809-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 13 May 2013

Research article | 13 May 2013

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

V. López-Burgos1,*, H. V. Gupta1, and M. Clark2 V. López-Burgos et al.
  • 1Hydrology and Water Resources, The University of Arizona, Tucson, AZ, USA
  • 2Hydrometeorological Applications Program, Research Applications Laboratory, Boulder, CO, USA
  • *now at: USDA Forest Service, Rocky Mountain Research Station, Boise, ID, USA

Abstract. 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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