Reducing cloud obscuration on MODIS Snow Cover Area products by applying spatio-temporal techniques combined with topographic effects.

Persistent Link:
http://hdl.handle.net/10150/193442
Title:
Reducing cloud obscuration on MODIS Snow Cover Area products by applying spatio-temporal techniques combined with topographic effects.
Author:
Lopez-Burgos, Viviana
Issue Date:
2010
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
Rapid population growth in Arizona is leading to increasing demand and decreasing availability of water, requiring a detailed quantification of hydrological processes. The integration of detailed spatial water fluxes information from remote sensing platforms, and hydrological models is one of the steps towards this goal. One example step is the use of MODIS Snow Cover Area (SCA) information to update the snow component of a land surface model (LSM). Because cloud cover obscures the images, this project explores a rule-based method to remove the clouds. The rules include: combination of SCA maps from two satellites; time interpolation method; spatial interpolation method; and the probability of snow occurrence in a pixel based on topographic variables. The application in sequence of these rules over the Upper Salt River Basin for WY 2005 resulted in a reduction of cloud obscuration by 93.7878% and the resulting images' accuracy is similar to the accuracy of the original SCA maps. The results of this research will be used on a LSM to improve the management of reservoirs on the Salt River. This research seeks to improve SCA data for further use in a LSM to increase the knowledge base used to manage water resources. It will be relevant for regions were snow is the primary source of water supply.
Type:
text; Electronic Thesis
Keywords:
clouds; MODIS; obscuration; snow cover
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Hydrology; Graduate College
Degree Grantor:
University of Arizona
Committee Chair:
Gupta, Hoshin V.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleReducing cloud obscuration on MODIS Snow Cover Area products by applying spatio-temporal techniques combined with topographic effects.en_US
dc.creatorLopez-Burgos, Vivianaen_US
dc.contributor.authorLopez-Burgos, Vivianaen_US
dc.date.issued2010en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractRapid population growth in Arizona is leading to increasing demand and decreasing availability of water, requiring a detailed quantification of hydrological processes. The integration of detailed spatial water fluxes information from remote sensing platforms, and hydrological models is one of the steps towards this goal. One example step is the use of MODIS Snow Cover Area (SCA) information to update the snow component of a land surface model (LSM). Because cloud cover obscures the images, this project explores a rule-based method to remove the clouds. The rules include: combination of SCA maps from two satellites; time interpolation method; spatial interpolation method; and the probability of snow occurrence in a pixel based on topographic variables. The application in sequence of these rules over the Upper Salt River Basin for WY 2005 resulted in a reduction of cloud obscuration by 93.7878% and the resulting images' accuracy is similar to the accuracy of the original SCA maps. The results of this research will be used on a LSM to improve the management of reservoirs on the Salt River. This research seeks to improve SCA data for further use in a LSM to increase the knowledge base used to manage water resources. It will be relevant for regions were snow is the primary source of water supply.en_US
dc.typetexten_US
dc.typeElectronic Thesisen_US
dc.subjectcloudsen_US
dc.subjectMODISen_US
dc.subjectobscurationen_US
dc.subjectsnow coveren_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineHydrologyen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.chairGupta, Hoshin V.en_US
dc.contributor.committeememberMeixner, Thomasen_US
dc.contributor.committeememberMcIntosh, Jenniferen_US
dc.identifier.proquest11242en_US
dc.identifier.oclc752261086en_US
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