Land Cover Classification Accuracy from Electro-Optical, X, C, and L-Band Synthetic Aperture Radar Data Fusion

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dc.contributor.advisorHaack, Barry N
dc.contributor.authorHammann, Mark Gregory
dc.creatorHammann, Mark Gregory
dc.date.accessioned2017-01-29T01:16:37Z
dc.date.available2017-01-29T01:16:37Z
dc.date.issued2016
dc.description.abstractThe fusion of electro-optical (EO) multi-spectral satellite imagery with Synthetic Aperture Radar (SAR) data was explored with the working hypothesis that the addition of multi-band SAR will increase the land-cover (LC) classification accuracy compared to EO alone. Three satellite sources for SAR imagery were used: X-band from TerraSAR-X, C-band from RADARSAT-2, and L-band from PALSAR. Images from the RapidEye satellites were the source of the EO imagery. Imagery from the GeoEye-1 and WorldView-2 satellites aided the selection of ground truth.
dc.format.extent176 pages
dc.identifier.urihttps://hdl.handle.net/1920/10597
dc.language.isoen
dc.rightsCopyright 2016 Mark Gregory Hammann
dc.subjectRemote sensing
dc.subjectGeographic information science and geodesy
dc.subjectGeography
dc.subjectData Fusion
dc.subjectLand Cover Classification
dc.subjectRemote Sensing
dc.subjectSAR
dc.subjectSatellite Imagery
dc.subjectSynthetic Aperture RADAR
dc.titleLand Cover Classification Accuracy from Electro-Optical, X, C, and L-Band Synthetic Aperture Radar Data Fusion
dc.typeDissertation
thesis.degree.disciplineGeoinformatics and Geospatial Intelligence
thesis.degree.grantorGeorge Mason University
thesis.degree.levelPh.D.

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