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dc.contributor.authorLove, Kimberly Raeen_US
dc.date.accessioned2014-03-14T20:19:42Z
dc.date.available2014-03-14T20:19:42Z
dc.date.issued2007-12-03en_US
dc.identifier.otheretd-12032007-231251en_US
dc.identifier.urihttp://hdl.handle.net/10919/29900
dc.description.abstractGeographic information systems (GISs) are a highly influential tool in today's society, and are used in a growing number of applications, including planning, engineering, land management,and environmental study. As the field of GISs continues to expand, it is very important to observe and account for the error that is unavoidable in computerized maps. Currently, both statistical and non-statistical models are available to do so, although there is very little implementation of these methods. In this dissertation, I have focused on improving the methods available for analyzing error in GIS vector data. In particular, I am incorporating Bayesian methodology into the currently popular G-band error model through the inclusion of a prior distribution on point locations. This has the advantage of working well with a small number of points, and being able to synthesize information from multiple sources. I have also calculated the boundary of the confidence region explicitly, which has not been done before, and this will aid in the eventual inclusion of these methods in GIS software. Finally, I have included a statistical point deletion algorithm, designed for use in situations where map precision has surpassed map accuracy. It is very similar to the Douglas-Peucker algorithm, and can be used in a general line simplification situation, but has the advantage that it works with the error information that is already known about a map rather than adding unknown error. These contributions will make it more realistic for GIS users to implement techniques for error analysis.en_US
dc.publisherVirginia Techen_US
dc.relation.haspartDissertation.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectDouglas-Peuckeren_US
dc.subjectGISen_US
dc.subjectvector dataen_US
dc.subjectBayesian statisticsen_US
dc.subjectpositional erroren_US
dc.titleModeling Error in Geographic Information Systemsen_US
dc.typeDissertationen_US
dc.contributor.departmentStatisticsen_US
dc.description.degreePh. D.en_US
thesis.degree.namePh. D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineStatisticsen_US
dc.contributor.committeememberTerrell, George R.en_US
dc.contributor.committeememberPrisley, Stephen P.en_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12032007-231251/en_US
dc.contributor.committeecochairSmith, Eric P.en_US
dc.contributor.committeecochairYe, Keyingen_US
dc.date.sdate2007-12-03en_US
dc.date.rdate2008-01-09
dc.date.adate2008-01-09en_US


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