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Crime Hot Spot Forecasting with Data from the Pittsburgh [Pennsylvania] Bureau of Police, 1990-1998 (ICPSR 3469)

Released/updated on: 2015-08-07
Geographic coverage: United States, Pennsylvania, Pittsburgh
Time period: 1990-01-01--1998-01-01

This study used crime count data from the Pittsburgh, Pennsylvania, Bureau of Police offense reports and 911 computer-aided dispatch (CAD) calls to determine the best univariate forecast method for crime and to evaluate the value of leading indicator crime forecast models.

The researchers used the rolling-horizon experimental design, a design that maximizes the number of forecasts for a given time series at different times and under different conditions. Under this design, several forecast models are used to make alternative forecasts in parallel. For each forecast model included in an experiment, the researchers estimated models on training data, forecasted one month ahead to new data not previously seen by the model, and calculated and saved the forecast error. Then they added the observed value of the previously forecasted data point to the next month's training data, dropped the oldest historical data point, and forecasted the following month's data point. This process continued over a number of months.

A total of 15 statistical datasets and 3 geographic information systems (GIS) shapefiles resulted from this study.

The statistical datasets consist of

  • Univariate Forecast Data by Police Precinct (Dataset 1) with 3,240 cases
  • Output Data from the Univariate Forecasting Program: Sectors and Forecast Errors (Dataset 2) with 17,892 cases
  • Multivariate, Leading Indicator Forecast Data by Grid Cell (Dataset 3) with 5,940 cases
  • Output Data from the 911 Drug Calls Forecast Program (Dataset 4) with 5,112 cases
  • Output Data from the Part One Property Crimes Forecast Program (Dataset 5) with 5,112 cases
  • Output Data from the Part One Violent Crimes Forecast Program (Dataset 6) with 5,112 cases
  • Input Data for the Regression Forecast Program for 911 Drug Calls (Dataset 7) with 10,011 cases
  • Input Data for the Regression Forecast Program for Part One Property Crimes (Dataset 8) with 10,011 cases
  • Input Data for the Regression Forecast Program for Part One Violent Crimes (Dataset 9) with 10,011 cases
  • Output Data from Regression Forecast Program for 911 Drug Calls: Estimated Coefficients for Leading Indicator Models (Dataset 10) with 36 cases
  • Output Data from Regression Forecast Program for Part One Property Crimes: Estimated Coefficients for Leading Indicator Models (Dataset 11) with 36 cases
  • Output Data from Regression Forecast Program for Part One Violent Crimes: Estimated Coefficients for Leading Indicator Models (Dataset 12) with 36 cases
  • Output Data from Regression Forecast Program for 911 Drug Calls: Forecast Errors (Dataset 13) with 4,936 cases
  • Output Data from Regression Forecast Program for Part One Property Crimes: Forecast Errors (Dataset 14) with 4,936 cases
  • Output Data from Regression Forecast Program for Part One Violent Crimes: Forecast Errors (Dataset 15) with 4,936 cases.
  • The GIS Shapefiles (Dataset 16) are provided with the study in a single zip file: Included are polygon data for the 4,000 foot, square, uniform grid system used for much of the Pittsburgh crime data (grid400); polygon data for the 6 police precincts, alternatively called districts or zones, of Pittsburgh(policedist); and polygon data for the 3 major rivers in Pittsburgh the Allegheny, Monongahela, and Ohio (rivers).
Curated

CrimeMapTutorial Workbooks and Sample Data for ArcView and MapInfo, 2000 (ICPSR 3143)

Released/updated on: 2001-04-12
Geographic coverage: United States
CrimeMapTutorial is a step-by-step tutorial for learning crime mapping using ArcView GIS or MapInfo Professional GIS. It was designed to give users a thorough introduction to most of the knowledge and skills needed to produce daily maps and spatial data queries that uniformed officers and detectives find valuable for crime prevention and enforcement. The tutorials can be used either for self-learning or in a laboratory setting. The geographic information system (GIS) and police data were supplied by the Rochester, New York, Police Department. For each mapping software package, there are three PDF tutorial workbooks and one WinZip archive containing sample data and maps. Workbook 1 was designed for GIS users who want to learn how to use a crime-mapping GIS and how to generate maps and data queries. Workbook 2 was created to assist data preparers in processing police data for use in a GIS. This includes address-matching of police incidents to place them on pin maps and aggregating crime counts by areas (like car beats) to produce area or choropleth maps. Workbook 3 was designed for map makers who want to learn how to construct useful crime maps, given police data that have already been address-matched and preprocessed by data preparers. It is estimated that the three tutorials take approximately six hours to complete in total, including exercises.
Curated

Examination of Crime Guns and Homicide in Pittsburgh, Pennsylvania, 1987-1998 (ICPSR 2895)

Released/updated on: 2006-03-30
Geographic coverage: United States, Pennsylvania, Pittsburgh
This study examined spatial and temporal features of crime guns in Pittsburgh, Pennsylvania, in order to ascertain how gun availability affected criminal behavior among youth, whether the effects differed between young adults and juveniles, and whether that relationship changed over time. Rather than investigating the general prevalence of guns, this study focused only on those firearms used in the commission of crimes. Crime guns were defined specifically as those used in murders, assaults, robberies, weapons offenses, and drug offenses. The emphasis of the project was on the attributes of crime guns and those who possess them, the geographic sources of those guns, the distribution of crime guns over neighborhoods in a city, and the relationship between the prevalence of crime guns and the incidence of homicide. Data for Part 1, Traced Guns Data, came from the City of Pittsburgh Bureau of Police. Gun trace data provided a detailed view of crime guns recovered by police during a two-year period, from 1995 to 1997. These data identified the original source of each crime gun (first sale to a non-FFL, i.e., a person not holding a Federal Firearms License) as well as attributes of the gun and the person possessing the gun at the time of the precipitating crime, and the ZIP-code location where the gun was recovered. For Part 2, Crime Laboratory Data, data were gathered from the local county crime laboratory on guns submitted by Pittsburgh police for forensic testing. These data were from 1993 to 1998 and provided a longer time series for examining changes in crime guns over time than the data in Part 1. In Parts 3 and 4, Stolen Guns by ZIP-Code Data and Stolen Guns by Census Tract Data, data on stolen guns came from the local police. These data included the attributes of the guns and residential neighborhoods of owners. Part 3 contains data from 1987 to 1996 organized by ZIP code, whereas Part 4 contains data from 1993 to 1996 organized by census tract. Part 5, Shots Fired Data, contains the final indicator of crime gun prevalence for this study, which was 911 calls of incidents involving shots fired. These data provided vital information on both the geographic location and timing of these incidents. Shots-fired incidents not only captured varying levels of access to crime guns, but also variations in the willingness to actually use crime guns in a criminal manner. Part 6, Homicide Data, contains homicide data for the city of Pittsburgh from 1990 to 1995. These data were used to examine the relationship between varying levels of crime gun prevalence and levels of homicide, especially youth homicide, in the same city. Part 7, Pilot Mapping Application, is a pilot application illustrating the potential uses of mapping tools in police investigations of crime guns traced back to original point of sale. NTC. It consists of two ArcView 3.1 project files and 90 supporting data and mapping files. Variables in Part 1 include date of manufacture and sale of the crime gun, weapon type, gun model, caliber, firing mechanism, dealer location (ZIP code and state), recovery date and location (ZIP code and state), age and state of residence of purchaser and possessor, and possessor role. Part 2 also contains gun type and model, as well as gun make, precipitating offense, police zone submitting the gun, and year the gun was submitted to the crime lab. Variables in Parts 3 and 4 include month and year the gun was stolen, gun type, make, and caliber, and owner residence. Residence locations are limited to owner ZIP code in Part 3, and 1990 Census tract number and neighborhood name in Part 4. Part 5 contains the date, time, census tract and police zone of 911 calls relating to shots fired. Part 6 contains the date and census tract of the homicide incident, drug involvement, gang involvement, weapon, and victim and offender ages. Data in Part 7 include state, county, and ZIP code of traced guns, population figures, and counts of crime guns recovered at various geographic locations (states, counties, and ZIP codes) where the traced guns first originated in sales by an FFL to a non-FFL individual. Data for individual guns are not provided in Part 7.
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