Abstract
Annual events like Oktoberfest , Mardi Gras, and Halloween are very popular among young crowds, especially in college towns , and a significant part of the celebration consists of alcohol consumption . Binge drinking during such celebrations often results in alcohol-related crime , assaults , vandalism, and even fatal accidents. Yet, in crime studies, little research has been conducted to investigate the impact of such events on dynamics of crime and underage drinking in the local communities. The present study aims to analyze the influence of Oktoberfest on spatiotemporal pattern of underage drinking in college town of La Crosse in southwest Wisconsin. The study uses 5 years (2008–2012) of liquor law citation records and GIS techniques to explore the spatiotemporal pattern of underage drinking during the week of Oktoberfest and a week before and after the festival. Analysis conducted using grid thematic maps and local information showed that the local celebration of Oktoberfest results in an increased number of liquor law violations citations which coincided with increased number of fatal accidents, alcohol-related crimes , and public nuisance. Knowledge gained from results of grid thematic mapping was used to create a multi-criteria evaluation (MCE) that helped to identify a probability surface for high concentration of liquor law violation and thus underage drinking in certain parts of the town. Validation of the resultant map shows that 85–97 % of the citation location in last 5 years falls within the high probability zone delineated by our map. This type of mapping approach is useful to the local law enforcement officials and volunteer watch groups to provide focused deployment of intervention measures and increased vigilance to restrict alcohol consumption of underage youths and prevent associated crime and accidents.
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References
Alaniz ML, Cartmill RS, Parker RN (1998) Immigrants and violence: the importance of neighborhood context. Hisp J Behav Sci 20:155–176
Andresen MA, Tong W (2012) The impact of the 2010 Winter Olympic games on crime in Vancouver. Can J Criminol Crim Justice 54(3):333–361
Bennett T (1995) Identifying, explaining and targeting burglary “hot spots”. Eur J Crim Policy Res 3(3):113–123
Block RL, Block CR (1995) Space, place and crime: hot spot areas and hot places of liquor-related crime. Crime Prev Stud 4
Boba R (2001) Introductory guide to crime analysis and mapping. Office of Community Oriented Policing Services, Washington, DC
Bowers KJ, Johnson SD (2005) Domestic burglary repeats and space-time clusters the dimensions of risk. Eur J Criminol 2(1):67–92
Britt H, Carlin B, Toomey T et al (2005) Neighborhood level spatial analysis of the relationship between alcohol outlet density and criminal violence. Environ Ecol Stat 12:411–426
Centers for Disease Control and Prevention (CDC) (2012) Atlanta, GA: fact sheets: http://www.cdc.gov/alcohol/fact-sheets/underage-drinking.htm. Accessed Sept 22 2013
Chainey S, Tompson L, Uhlig S (2008) The utility of hotspot mapping for predicting spatial patterns of crime. Secur J 21:4–28
Chang W, Zeng D, Chen H (2008) A stack-based prospective spatio-temporal data analysis approach. Decis Support Syst 45:697–713
Eaton DK, Kann L, Kinchen SA et al (2012) Youth risk behavior surveillance—United States, CDC. CDC Morb Mortal Surveill Summ 61(SS-04):1–162
Eck JE, Chainey S, Cameron JG, et al (2005) Mapping crime: understanding hot spots. National Institute of Justice Special Report, Office of Justice Programs, U.S. Department of Justice
Eckley DC, Curtin KM (2013) Evaluating the spatiotemporal clustering of traffic incidents. Comput Environ Urban Syst 37:70–81
Felson M, Poulsen E (2003) Simple indicators of crime by time of day. Int J Forecast 19:595–601
Goodchild MF, Anselin L, Appelbaum RP et al (2000) Towards spatially integrated social science. Int Reg Sci Rev 23(2):139–159
Gorman DM, Speer PW, Gruenewald P et al (2001) Spatial dynamics of alcohol availability, neighbourhood structure and violent crime. J Stud Alcohol 62(5):628–36
Groff E, Weisburd D, Morris NA (2009) Where the action is at places: examining spatio-temporal patterns of juvenile crime at places using trajectory analysis and GIS. In: Weisbard D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place. Springer, New York, pp 61–86
Gruenewald P (2007) The spatial ecology of alcohol problems: niche theory and assortative drinking. Addiction 102:870–878
Gruenewald P, Millar PJ, Treno AJ et al (1996) The geography of availability and driving after drinking. Addict Sci 91:967–983
Hoover L, Zhang Y, Zhao J (2010) Geographic Information Systems and their effects on police efficacy: Campbell Systematic Review. Accessed from http://campbellcollaboration.org/lib/project/146/
Huckle T, Huakau J, Sweetsur P et al (2008) Density of alcohol outlets and teenage drinking: living in an alcogenic environment is associated with higher consumption in a metropolitan setting. Addiction 103:1614–1621
Imperial College London (ICL) (2010) Alcohol most harmful drug based on multicriteria analysis, November 1. http://www3.imperial.ac.uk/newsandeventspggrp/imperialcollege/newssummary/news_1-11-2010-15-43-18. Accessed 25 Dec 2012
Jiang H, Eastman JR (2000) Application of fuzzy measures in multi-criteria evaluation in GIS. Int J Geogr Inf Sci 14(2):173–184
Johnson SD, Bowers KJ (2004a) The burglary as clue to the future the beginnings of prospective hot-spotting. Eur J Criminol 1(2):237–255
Johnson SD, Bowers KJ (2004b) The stability of space-time clusters of Burglary. Br J Criminol 44(1):55–65
Khan G, Santiago-Chaparro K, Qin X et al (2009) Application and integration of lattice data analysis, network K-functions, and geographic information system software to study ice-related crashes. Transp Res Rec 2136:67–76
Kulldorff M (2001) Prospective time periodic geographical disease surveillance using a scan statistic RID H–4282-2011. J R Stat Soc A Stat Soc 164:61–72
Kulldorff M, Athas W, Feuer E et al (1998) Evaluating cluster alarms: a space-time scan statistic and brain cancer in Los Alamos, New Mexico RID H-4282-2011. Am J Public Health 88(9):1377–1380
Kulldorff M, Heffernan R, Hartman J et al (2005) A space-time permutation scan statistic for disease outbreak detection RID H-4282–2011. PLoS Med 2(3):216–224
La Crosse Tribune (2011) Oktoberfest roundup: Mob will mean more police for 2012, reported by Anne Jungen, September 27. http://lacrossetribune.com/news/local/oktoberfest-roundup-mob-will-mean-more-police-for/article_c5b3c2a4-e89f-11e0-ac71-001cc4c03286.html. Accessed 31 Dec 2012
Leitner M, Guo D (2013) The impact of hurricanes on crime using a data mining and visual analytics approach. In Proceedings of 26th International Cartographic Conference, Dresden, Germany, August 25–30
Leitner M, Helbich M (2011) The impact of Hurricanes on crime: a spatio-temporal analysis in the city of Houston, TX. Cartogr Geogr Inf Sci 38(2):214–222
Leitner M, Barnett M, Kent J et al (2011) The impact of Hurricane Katrina on reported crimes in Louisiana: a spatial and temporal analysis. Prof Geogr 63(2):244–261
Levine N (2010) CrimeStat: a spatial statistics program for the analysis of crime incident locations (v 3.3). Ned Levine & Associates, Houston; National Institute of Justice, Washington, DC
Malczewski J (2004) GIS-based land-use suitability analysis: a critical overview. Prog Plann 62:3–65
Malczewski J (2006) GIS-based multicriteria decision analysis: a survey of the literature. Int J Geogr Inf Sci 20(7):703–726
Malizia N (2012) The effect of data inaccuracy on tests of space-time interaction (Working paper # 10). GeoDa Center for Geospatial Analysis and Computation, Arizona State University, Phoenix
Mantel N (1967) The detection of disease clustering and a generalized regression approach. Cancer Res 27(2 Part 1):209–220
Mantel N, Bailar JC (1970) A class of permutational and multinomial tests arising in epidemiological research. Biometrics 26(4):687–700
Mennis J (2010) Multidimensional map algebra: design and implementation of a spatio-temporal GIS processing language. Trans GIS 14(1):1–21
Mountrakis G, Gunson K (2009) Multi-scale spatiotemporal analyses of moose–vehicle collisions: a case study in northern Vermont. Int J Geogr Inf Sci 23:1389–1412
Nakaya T, Yano K (2010) Visualising crime clusters in a space-time cube: an exploratory data-analysis approach using space-time kernel density estimation and scan statistics. Trans GIS 14(3):223–239
Norström T (2000) Outlet density and criminal violence in Norway 1960–95. J Stud Alcohol 61
Pei T, Zhou C, Zhu A-X et al (2010) Windowed nearest neighbor method for mining spatio-temporal clusters in the presence of noise. Int J Geogr Inf Sci 24:925–948
Ratcliffe JH (2004a) The hotspot matrix: a framework for the spatio-temporal targeting of crime reduction. Police Pract Res 5(1):05–23
Ratcliffe JH (2004b) Geocoding crime and a first estimate of a minimum acceptable hit rate. Int J Geogr Inf Sci 18(1):61–72
Scribner R, Cohen D, Kaplan S et al (1999) Alcohol availability and homicide in New Orleans: conceptual considerations for small area analysis of the effect of alcohol outlet density. Alcohol Drugs 60(3)
Snowden A (2012) Alcohol outlets and assaults in a College Town: accounting for social organization and land use. Paper presented at the ASC Annual Meeting, Washington Hilton, Washington, DC (http://www.allacademic.com/meta/p517139_index.html)
Spelman W (1995) Criminal careers of public places. In: Eck JE, Weisburd D (eds) Crime and place: crime prevention studies. Willow Tree, Monsey, p 4
StarTribune (2012) Oktoberfest in La Crosse: a party town tries to sober up, reported by Larry Oaks, October 1. http://www.startribune.com/local/171948771.html. Accessed 31 Dec 2012
Taylor R (1999) Crime, grime, fear, and decline: a longitudinal look, Research in brief. National Institute of Justice, Washington, DC
Townsley M (2008) Visualizing space time patterns in crime: the hotspot plot. Crime Patterns Anal 1(1):61–74
Townsley M, Homel R, Chaseling J (2000) Repeat burglary victimisation: spatial and temporal patterns. Austr N Z J Criminol 33(1):37–63
Treno A, Grube J, Martin S (2003) Alcohol availability as a predictor of youth drinking and driving: a hierarchical analysis of survey and archival data. Alcohol Clin Exp Res 27:835–840
U.S. Census Bureau (2010) Census. Profile of general population and housing characteristics. http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=DEC_10_DP_DPDP1. Accessed 31 Dec 2012
Watts RK, Rabow J (1983) Alcohol availability and alcohol related consumption in 213 Californian cities. Alcohol Clin Exp Res 7:47–58
Weisburd D, Bushway S, Lum C et al (2004) Trajectories of crime at place: a longitudinal study of street segments in the city of Seattle. Criminology 42(2):283–321
Weitzman E, Folkman A, Folkman K et al (2003) The relationship of outlet density to heavy and frequent drinking and drinking-related problems among college students at eight universities. Health Place 9:1–6
Zhu L, Gorman DM, Horel S (2004) Alcohol outlet density and violence: a geospatial analysis. Alcohol Alcohol 39(4):369–375
Acknowledgments
We would like to thank the University of Wisconsin-La Crosse Police Department and La Crosse Police Department for providing us data and insights about policing during Oktoberfest. We would also like to extend our gratitude to Professors Cynthia Berlin (Dept. of Geography and Earth Science) and Kim Vogt (Dept. of Sociology) of University of Wisconsin-La Crosse for their valuable suggestions and guidance.
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Chaudhuri, G., Oxley, S., Wenzlaff, S. (2014). Mapping Spatiotemporal Patterns of Liquor Law Violation Citations During Oktoberfest in College Town of La Crosse, Wisconsin. In: Elmes, G., Roedl, G., Conley, J. (eds) Forensic GIS. Geotechnologies and the Environment, vol 11. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8757-4_10
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