A Study of CPTED Principles and their Relationship to Crime Risk in Beaumont, Texas
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Crime Prevention Through Environmental Design (CPTED) is an approach to understanding crime which focuses on the built environment and geography instead of simply a potential offender’s behavior or socio-economic characteristics. The theory of CPTED proposes that characteristics of the built environment can lower or increase the risk of crime at a location, based on the principles of Natural Surveillance, Natural Access Control, Territoriality, and Image. For this study, I investigated how CPTED characteristics had an impact on the property crime rate in Beaumont, Texas. I observed six Beaumont neighborhoods, and their houses and other buildings were rated according to an audit list I developed, consisting of 12 quantifiable CPTED characteristics based on the four principles. The houses and buildings of the six neighborhoods were rated by their individual parcels, according to a 0-4 based scale. These rated parcels were aggregated to a combined total of 134 residential blocks in ArcGIS, with each block being assigned the average of the CPTED ratings of the combined parcels. Maps of the six neighborhoods and their blocks were created which showed their vulnerability to crime, based on CPTED characteristic ratings. In addition to the CPTED vulnerability maps, I also developed maps which showed actual crime rates, which rated residential blocks within neighborhoods based on the number of crimes per 1,000 houses. The maps and spreadsheet data from the audit were used to determine the relationship of CPTED characteristics to crime rate. The research hypothesis was that neighborhoods that exhibit comparatively more CPTED characteristics will have fewer instances of crime than neighborhoods that exhibit fewer CPTED characteristics. The null hypothesis was that neighborhoods that exhibit more CPTED characteristics will not show a significant difference in crime rate compared to neighborhoods with fewer CPTED characteristics. The data was collected by slowly traversing each neighborhood by car, and using high- definition video cameras to record each individual house. The recorded video was later played back, and the CPTED residential audit was completed for each house. Information from the audit was documented in a spreadsheet, and also entered into ArcGIS software in order to create the CPTED vulnerability maps. ArcGIS was also used to create crime rate maps, based on data from the Beaumont Police Department. The neighborhoods were ranked from highest CPTED rating down to lowest CPTED rating; and from lowest crime count to highest crime count, to see if there were similar rankings in which high CPTED rating is closely paired with low crime-count. In addition to the ranking method, the CPTED ratings and crime counts for each block of the six neighborhoods were also plotted on a graph, to determine if there is a valid linear regression in which crime rate is determined by the CPTED rating. The results show that the neighborhood with the highest CPTED rating had the second lowest crime density, and the neighborhood with the lowest CPTED rating had the highest crime density. The ranks of the neighborhoods according to CPTED rating and crime count show that there likely is some relationship between these two variables. A regression analysis shows that there is an inverse relationship (y = -550.49x + 1254.5) in which an increase in the CPTED rating corresponds to a decrease in crime rate per 1,000, with an R2 value of .1805. The Spearman-Rho test indicates that there is a moderate correlation (R = .447) between CPTED rating and crime rate per 1,000, at the .05 significance level with a P value of 0.00000007. When looking at the CPTED rating maps of these neighborhoods alongside the crime count maps, many values of blocks in the CPTED maps correspond to similar values in the crime count maps. This phenomenon can better be illustrated by determining where similar rank values in CPTED rating and crime rating "overlap." Although this process is more subjective compared to other methods, it is helpful in illuminating the areas in which the CPTED rating procedure most strongly predicted areas which are most at risk for crime, and which areas are most defended against crime. Even though this process of finding overlap is somewhat subjective, it was able to correctly predict 85 out of 134 blocks (63%) while the remaining 49 blocks (37%) do not show the relationship being sought, according to the hypothesis. The regression analysis and Spearman's test showed this relationship in a more objective manner than the maps, illustrating that crime rate falls as CPTED ratings rise.