Date of Graduation

Summer 2014

Degree

Master of Science in Geospatial Sciences

Department

Geography, Geology and Planning

Committee Chair

Xiaomin Qiu

Keywords

methamphetamine production, remote sensing, vegetation mapping, supervised classification, Normalized Difference Vegetation Index

Subject Categories

Botany | Criminology and Criminal Justice | Remote Sensing

Abstract

Methamphetamine abuse and manufacture is still a growing national problem. While the use of GIS and remote sensing techniques in law enforcement has increased over the last 30 years, most models are retrospective; they are not as predictive as they are informative. In many of the models used in GIS for crime prevention, the variables used are broad and there is not a specific indicator that would definitively target an undiscovered methamphetamine lab. While such retrospective mapping endeavors are beneficial, with the proper approach, vegetative mapping has the potential ability to detect signs of methamphetamine production and introduce a more proactive methodology to law enforcement problem solving and crime prevention. Utilizing classification techniques to identify spectra of phytotoxic vegetation in known meth lab sites and extrapolating the data over rural areas would be a useful method to locate regions that share similarity. This research involved collecting data on known methamphetamine locations and determining if there was any difference between the vegetation at the methamphetamine site and a control site of healthy vegetation. That information was then extrapolated over a broader area using classification methods to find areas with similar vegetative characteristics.

Copyright

© Mellora L. Hall

Campus Only

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