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Abstract
The combination of crime mapping and geospatial analysis methods has enabled law enforcement agencies to develop more proactive methods of targeting crime-prone neighborhoods based on spatial patterns, such as hot spots and spatial proximity to specific points of interest. In this article, we investigate the spatial and temporal patterns of the neighborhood crimes of aggravated assault and larceny in 297 census tracts in Miami–Dade County from 2007 to 2015. We use emerging hot spot analysis (EHSA) to identify the spatial patterns of emerging, persistent, continuous, and sporadic hot spots. In addition, we use geographically weighted regression to analyze the spatial clustering effects of sociodemographic variables, poverty rate, median age, and ethnic diversity. The hot spots for larceny are much more diffused than those for aggravated assaults, which exhibit clustering in the north over Liberty City and Miami Gardens and in the south near Homestead, and the ethnic heterogeneity index has a moderate and positive effect on the incidence of both larceny and aggravated assaults. The findings suggest that law enforcement can better target prevention programs for violent versus property crime using geospatial analyses. Additionally, the ethnic concentration of neighborhoods influences crime differently in neighborhoods of different socioeconomic status, and future studies should account for spatial patterns when estimating conventional regression models.
犯罪製图与地理空间方法的结合, 让法律执行单位能够根据诸如热点和对于特定兴趣点的空间距离之空间模式, 针对具有犯罪倾向的邻里, 发展更为先发制人的方法。我们于本文中, 探讨迈阿密—戴德县 2007 年至 2015 年之间, 在二百九十七个人口统计单元中, 加重伤害与窃盗的邻里犯罪之时空模式。我们运用浮现的热点分析 (EHSA) 来指认浮现、反覆、持续和零星的热点。此外, 我们运用地理加权迴归, 分析社会人口变因、贫穷率、年龄中位数和族裔多样性的空间集群效应。窃盗的热点, 较加重伤害更为分散, 并集中于自由城与迈阿密花园的北部, 以及邻近霍姆斯特德的南部, 而族裔异质性指标则同时对窃盗和加重犯罪事件具有中等与正向的影响。研究结果显示, 法律执行运用地理空间分析对暴力实施预防计画, 较财产犯罪效果更佳。此外, 邻里的族裔集中, 在不同社经地位的邻里中, 对犯罪产生不同的影响, 而未来的研究在评估传统迴归模型时, 应将空间模式纳入考量。
La combinación del mapeo del crimen y los métodos de análisis geoespacial ha habilitado a las agencias de aplicación de la ley a desarrollar métodos más proactivos para enfocar su mayor atención sobre barriadas con propensión criminal con base en patrones espaciales, tales como los puntos calientes y a la proximidad espacial a puntos de interés específico. En este artículo investigamos los patrones espaciales y temporales en la criminalidad vecinal de asalto agravado y hurto, en 297 distritos censales del Condado de Miami–Dade, de 2007 a 2015. Usamos el análisis de puntos calientes emergentes (EHSA) para identificar los patrones espaciales de puntos calientes emergentes, persistentes, continuos y esporádicos. Además, usamos regresión geográficamente ponderada para analizar los efectos de agrupamiento espacial de variables sociodemográficas, la tasa de pobreza, edad media y diversidad étnica. Los puntos calientes relacionados con hurto están mucho más dispersos que los relacionados con asalto agravado que exhiben agrupamiento en el norte sobre Liberty City y Miami Gardens y en el sur cerca a Homestead, y el índice de heterogeneidad étnica tiene un efecto moderado y positivo sobre la incidencia tanto de hurto como de asaltos agravados. Los hallazgos obtenidos sugieren que la aplicación de la ley debería enfocarse preferencialmente en programas de prevención del crimen violento contra el crimen contra la propiedad, usando análisis geoespaciales. Adicionalmente, la concentración étnica en los vecindarios influye el crimen de modo diferente en vecindarios de diferentes estatus socioeconómicos, y los estudios futuros deben tomar en cuenta los patrones espaciales cuando se esté operando con modelos convencionales de regresión.
Acknowledgments
The authors want to thank the two anonymous reviewers and the editor for constructive comments and suggestions, which vastly improved the article. The support of the Miami–Dade County Police Department for providing the data is also acknowledged.
Notes
1 Introduced in ArcGIS 10.3.2.
2 Although it is not the primary focus of this article, we investigate and report the temporal results from hourly scale daily analysis to show the differential patterns based on crime type. Our results are consistent with the body of substantive literature on the temporal patterning of crime (e.g., Hipp and Yates Citation2009; Linning, Andresen, and Brantingham Citation2016; Pereira, Andresen, and Mota Citation2016) and support a routine activity framework (Cohen and Felson Citation1979), which is interpreted in greater detail in the “Discussion” section.
3 Our findings that crime is higher in areas with a younger population (i.e., ages eighteen to twenty-eight) are consistent with research on criminal involvement across the life course (Laub and Sampson Citation2003), specifically that participation in crime tends to peak between eighteen and twenty-five among males. Drawing from routine activity theory (Cohen and Felson Citation1979; Rice and Smith Citation2002), because these individuals would likely be more motivated offenders, our findings on the spatial patterning of crime show that areas with more motivated offenders also have higher crime incidence.
Additional information
Notes on contributors
Ryan J. Bunting
RYAN J. BUNTING is an Environmental Specialist working in resource recovery. E-mail: [email protected]. He received his bachelor of science degree in Geological Sciences and Marine Sciences from the Department of Geography, University of Miami, Coral Gables, FL 33146. His research interests include geospatial analysis.
Oliver Yang Chang
OLIVER YANG CHANG is a PhD student in the Department of Computer Science at Rice University, Houston, TX 77005. E-mail: [email protected]. His research interests include machine learning and program synthesis.
Christopher Cowen
CHRISTOPHER COWEN is a Geographic Information Systems Specialist who graduated in 2016 with a degree in Geography and Mathematics from the Department of Geography, University of Miami, Coral Gables, FL 33146. E-mail: [email protected]. His research interests include the application of spatial statistical analysis in localized crime analysis.
Richard Hankins
RICHARD HANKINS is an undergraduate student in the Department of Geography, University of Miami, Coral Gables, FL 33146. E-mail: [email protected]. His research interests include geospatial analysis and urban geography.
Staci Langston
STACI LANGSTON is a Geographic Information Systems Analyst at the University of Miami's Center for Southeastern Tropical Advanced Remote Sensing (CSTARS), Miami, FL 33177. E-mail: [email protected]. Her work and research focuses on utilizing synthetic aperture radar imagery in conjunction with geographic information system applications.
Alexander Warner
ALEXANDER WARNER is an undergraduate student in the Department of Geography, University of Miami, Coral Gables, FL 33146. E-mail: [email protected]. His research interests include crime analysis and geospatial analysis.
Xiaxia Yang
XIAXIA YANG is a PhD student in the Department of Geography at the University of Washington, Seattle, WA 98195. E-mail: [email protected]. Her research interests include urban change and internal migration in China.
Eric R. Louderback
ERIC R. LOUDERBACK is a Doctoral Candidate in the Department of Sociology at the University of Miami, Coral Gables, FL 33146. E-mail: [email protected]. His research interests include multilevel and geospatial exploration of neighborhood crime data, sociotechnical analysis of cybercrime offending and victimization, and recent advances in quantitative methods and statistical methodology.
Shouraseni Sen Roy
SHOURASENI SEN ROY is an Associate Professor in the Department of Geography at the University of Miami, Coral Gables, FL 33146. E-mail: [email protected]. Her research interests include the spatial and temporal analysis of long-term trends in climate processes in the Global South.