Irvine Lab for the Study of Space and Crime
You can now access an online first article by Dr. John R. Hipp, Dr. James C. Wo, & Young-An Kim in the Social Science Research entitled, “Studying neighborhood crime across different macro spatial scales: The case of robbery in 4 cities”. The article examines crime variation across macro-environments & micro-geographic units four cities.
Get it here:
http://www.sciencedirect.com/science/article/pii/S0049089X16307931
In the Southern California Crime Study (SCCS), the researchers made an effort to contact each police agency in the Southern California region and request address-level incident crime data for the years 2005-2012. Many of the agencies were willing to share their data with us. As a consequence, we have crime data for 2,740 of the 3,852 tracts in the region, which cover 219 of the 341 cities and 83.3 percent of the region’s population.
. The data come from crime reports officially coded and reported by the police departments. We classified crime events into six Uniform Crime Report (UCR) categories: homicide, aggravated assault, robbery, burglary, motor vehicle theft, and larceny. Crime events were geocoded for each city separately to latitude–longitude point locations using ArcGIS 10.2, and subsequently aggregated to various units such as blocks, block groups, and census tracts. The average geocoding match rate was 97.2% across the cities, with the lowest value at 91.4%. These data have been used in several prior studies (Kubrin and Hipp 2016; Hipp and Kubrin Forthcoming).
In December 2016 ILSSC faculty John Hipp and graduate student Young-an Kim had a journal article published in Journal of Quantitative Criminology entitled, “Measuring Crime Concentration across Cities of Varying Sizes: Complications Based on the Spatial and Temporal Scale Employed.” The article raises conceptual and methodological challenges to measuring the concentration of crime in cities.
Crime events are not random. They cluster in space. In other words, certain blocks, neighborhoods, and cities have higher crime rates than others. The goal of spatial analysis of crime is not just to display where crimes occur but to understand why crimes occur where they do- and more specifically, why crime rates cluster where they do.
Criminologists who spatially analyze crime rates examine various characteristics of areas–most frequently factors such as poverty, racial/ethnic composition, and land use–in order to determine if these factors play a role in predicting where crime is more likely to happen.
The fundamental question we seek to answer is: how do the social and physical characteristics of locations relate to the levels of crime in those areas?
Crime events are not random. They cluster in space. In other words, certain blocks, neighborhoods, and cities have higher crime rates than others. The goal of spatial analysis of crime is not just to display where crimes occur but to understand why crimes occur where they do- and more specifically, why crime rates cluster where they do. Criminologists who spatially analyze crime rates examine various characteristics of areas–most frequently factors such as poverty, racial/ethnic composition, and land use–in order to determine if these factors play a role in predicting where crime is more likely to happen. The fundamental question we seek to answer is: how do the social and physical characteristics of locations relate to the levels of crime in those areas?
2011 is the most recent year for which we have the most crime data for our range of cities in the Southern California region from the Southern California Crime Study. The 1/2 mile radius represent the common distance people will walk to various amenities. A 2-mile radius is useful since it gives a broader perspective (e.g., of where people drive) so the two can be compared. Currently, we do not have crime data for every single city in the Southern California region (although we have the majority of cities).The cities for which we have crime data are outlined in blue.
