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

dc.contributor.advisor	Haack, Barry N
dc.contributor.author	Hammann, Mark Gregory
dc.creator	Hammann, Mark Gregory
dc.date.accessioned	2017-01-29T01:16:37Z
dc.date.available	2017-01-29T01:16:37Z
dc.date.issued	2016
dc.identifier.uri	https://hdl.handle.net/1920/10597
dc.description.abstract	The 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.extent	176 pages
dc.language.iso	en
dc.rights	Copyright 2016 Mark Gregory Hammann
dc.subject	Remote sensing	en_US
dc.subject	Geographic information science and geodesy	en_US
dc.subject	Geography	en_US
dc.subject	Data Fusion	en_US
dc.subject	Land Cover Classification	en_US
dc.subject	Remote Sensing	en_US
dc.subject	SAR	en_US
dc.subject	Satellite Imagery	en_US
dc.subject	Synthetic Aperture RADAR	en_US
dc.title	Land Cover Classification Accuracy from Electro-Optical, X, C, and L-Band Synthetic Aperture Radar Data Fusion
dc.type	Dissertation
thesis.degree.level	Ph.D.
thesis.degree.discipline	Geoinformatics and Geospatial Intelligence
thesis.degree.grantor	George Mason University