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dc.contributor.advisorAllen, Edward B.
dc.contributor.authorShrestha, Bijay
dc.date2005
dc.date.accessioned2020-05-07T18:31:24Z
dc.date.available2020-05-07T18:31:24Z
dc.identifier.urihttps://hdl.handle.net/11668/17302
dc.description.abstractSpatio-temporal satellite image analysis is a technique for monitoring spatial and temporal changes of land cover and oceanic locations on earth. Temporal Map Algebra (TMA) is a novel technique developed by Jeremy Mennis and Roland Viger for analyzing a time series of satellite imagery using simple algebraic operators that treats time series of imagery as a threedimensional data set, where two dimensions encode planimetric position on earth surface and the third dimension encodes time. The high dimensionality of raster data leads to high computational cost, which is why parallel computation is attractive. This thesis describes the design, implementation, andmperformance evaluation of parallel compositing of vegetation indices derived from MODIS datasets using TMA.
dc.publisherMississippi State University
dc.subject.lcshRemote-sensing images.
dc.subject.lcshImage processing--Mathematical models.
dc.subject.lcshParallel processing (Electronic computers)
dc.subject.lcshAlgebra--Computer programs.
dc.subject.otherparallel processing
dc.subject.otherimage compositing
dc.subject.othertemporal map algebra
dc.titleParallel Compositing of Multi-Temporal Satellite Imagery using Temporal Map Algebra
dc.typeThesis
dc.publisher.departmentDepartment of Computer Science and Engineering.
dc.publisher.collegeBagley College of Engineering
dc.date.authorbirth1978
dc.subject.degreeMaster of Science
dc.subject.majorComputer Science
dc.contributor.committeeO'Hara, Charles
dc.contributor.committeeLuke, Edward A.
dc.date.defense2006-11-16


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