Spatial Patterns of Larceny and Aggravated Assault in Miami-Dade County, 2007-2015

• Published in: The Professional geographer Vol. 70; no. 1; pp. 34 - 46
• Main Authors: Bunting, Ryan J., Chang, Oliver Yang, Cowen, Christopher, Hankins, Richard, Langston, Staci, Warner, Alexander, Yang, Xiaxia, Louderback, Eric R., Roy, Shouraseni Sen
• Format: Journal Article
• Language: English
• Published: Washington Routledge 02-01-2018; Taylor & Francis Ltd
• Subjects: aggravated assault; análisis de puntos calientes emergentes; asalto agravado; Assaults; Censuses; Clustering; Crime; crimen; emerging hot spots analysis; Enforcement; Gardens & gardening; Geographic information systems; geographically weighted regression; hurto; larceny; Law enforcement; Law enforcement agencies; Mapping; Multiculturalism & pluralism; Neighborhoods; Poverty; Prevention programs; Prone; Property offences; Proximity; regresión geográficamente ponderada; Regression analysis; Regression models; Sociodemographics; Socioeconomic factors; Socioeconomic status; Socioeconomics; Spatial analysis; Temporal patterns; Violence; 加重伤害; 地理加权迴归; 浮现的热点分析; 窃盗; United States > US; Miami-Dade County Florida
• ISSN: 0033-0124; 1467-9272
• DOI: 10.1080/00330124.2017.1310622

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.