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

V. Lopez-Burgos, H. V. Gupta, M. Clark

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1809-1823
Number of pages15
JournalHydrology and Earth System Sciences
Volume17
Issue number5
DOIs
StatePublished - Aug 26 2013

ASJC Scopus subject areas

  • Water Science and Technology
  • Earth and Planetary Sciences (miscellaneous)

Fingerprint Dive into the research topics of 'Reducing cloud obscuration of MODIS snow cover area products by combining spatio-temporal techniques with a probability of snow approach'. Together they form a unique fingerprint.

Cite this