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dc.contributor.advisorLudwig, Gail S.eng
dc.contributor.authorWeber, Lloyd E.eng
dc.coverage.spatialMissouri -- Franklin Countyeng
dc.date.issued2006eng
dc.date.submitted2006 Springeng
dc.descriptionThe entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from title screen of research.pdf file (viewed on April 21, 2009.)eng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionThesis (M.A.) University of Missouri-Columbia 2006.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Geography.eng
dc.description.abstractIllicit methamphetamine, a synthetic, highly addictive drug, has gained national attention because of its destructive properties. Between 2002 and 2004 close to 400 clandestine methamphetamine labs were seized in Franklin County, Missouri. This study reviews documented methamphetamine production risk factors and examines a spatial model based on the reviewed risk factors. The risk factors include populations that are rural, white, impoverished, undereducated, unmarried and aged 25 - 29. The model is advanced by adding a component representing a clandestine landscape. Model output is validated using illicit meth lab seizure data supplied by Franklin County law enforcement. The model components are tested using both ordinary least squares and geographically weighted regression. This study found that the model is successful in indicating areas that have the potential to develop methamphetamine production problems. The model also was successful in indicating areas that would not likely develop a meth production problem. Ordinary least squares regression analysis indicates that every model component, with the exception of percent white and percent unmarried, are positively correlated with meth production in this case study. The results from the geographically weighted regression analysis show percent rural, percent poverty and percent clandestine landscape vary significantly across the county and indicate which areas these components have the most effect in developing and sustaining an illicit meth landscape.eng
dc.identifier.merlinb66800195eng
dc.identifier.oclc318901433eng
dc.identifier.urihttps://hdl.handle.net/10355/4513
dc.identifier.urihttps://doi.org/10.32469/10355/4513eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.subject.lcshMethamphetamine -- Risk assessment -- Geographic information systemseng
dc.subject.lcshMethamphetamineeng
dc.titleThe illicit methamphetamine landscape of Franklin County, Missouri: application and analysis of a GIS-based risk assessment modeleng
dc.typeThesiseng
thesis.degree.disciplineGeography (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.A.eng


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