Fundamentals of Crime Mapping

Crime Mapping and Analysis Data

Often difficult with crime data If your analysis or crime map seeks to

understand robbery motivated homicides within city limits for a given time period, all known robbery-motivated homicides must be included in the analysis

If any are excluded, the analysis will be limited in its power to explain or predict these crimes.

Probability Sample

Fixing the problems in your data that can be done without diminishing the data quality or inserting error

Repair errors due to “commission”◦ Error upon entry of data element

Repair errors due to “omission”◦ This committed by lack of entry for a field or fields

Something most analysts do daily Being “intimate” with your data helps to

correct these issues

Data Cleaning

Kind of the “Big Picture” of crime mapping Large scale analysis (citywide), yields large scale

assumptions and cannot be reduced to say a block level and vice versa

Will control the accuracy needed in the data, both spatial and attribute accuracy◦ Eg; If we wanted to do an analysis of tornado damage along the

coast, the coast line graphic would not need to include every single cove and jut of the coastline, but if our analysis was of one small bay, then each rock, pier, and beach area might need to be drawn.

Units of analysis should be useful in the analysis being performed

Scale

Official Crime Data◦ Persons

Arrestees Parolees Traffic units

◦ Places Schools Businesses

◦ Things Evidence Vehicles

◦ Incidents Calls for service Reported crimes Traffic crashes

Sources of Data

FBI (http://www.fbi.gov/ucr/ucr.htm) Weaknesses:

◦ Only reports most serious crime at a location◦ Definitions may not be the same as state statutes◦ Voluntary compliance and reporting◦ UCR counts some crimes by number of victims instead of incidents◦ Was developed in 1930◦ Only crime reported to police are captured – self reporting not included

Strengths:◦ Most states do report◦ Allows comparison with like-sized agencies across the country◦ Provides a general picture of crime reported to police

Uniform Crime Reporting (UCR)

FBI (http://www.fbi.gov/ucr/ucr.htm) Weaknesses:

◦ Reports all crimes occurring at location◦ Only a few states report NIBRS data

Strengths:◦ Reports all crimes occurring at location◦ More robust definitions

National Incident Based Reporting System (NIBRS)

Citizen generated requests for police services Officer initiated activity

◦ Location citizen gave for call, may not be where incident actually happened

◦ Location may be an intersection and not a specific address

◦ Depending on how it is captured it may not geocode and can thus, not be mapped

◦ What the call came in as, may not be what the officer determines was the real problem

◦ Not necessarily a picture of “crime” but of citizen desire for police presence only

Calls for service (CFS)

Official Crime Data◦ Persons

Arrestees, or persons listed in police reports (victim, witnesses, suspects)

Parolees/probationers Traffic units/passengers

◦ Places Schools, hotels, police stations, massage parlors Businesses, etc

◦ Things Evidence Vehicles, guns, etc

◦ Incidents Calls for service Reported crimes Traffic crashes

Sources of Data

Can capture crime data not reported to police (much is not)◦ There is no way to verify if a respondent is

providing truthful and accurate information◦ Information on homicides is not collected. (“Dead

men can tell no tales”)◦ Crime victims under the age of 12 years are

unaccounted for Victimless crime is unaccounted for

National Crime Victimization Survey

Crime Funnel

Contextual data Data not collected by police departments,

but that can be used for crime mapping◦ US Census◦ City sales tax and licensing◦ Google, Yahoo, US West Dex Yellow Pages◦ Political boundaries from local, county and state◦ Local social agencies like Department of Economic

Security◦ GIS data at local universities◦ Other city departments◦ Etc.

Tools of the trade Microsoft

◦ Access – database◦ Excel – spreadsheet◦ Word – word processor◦ Powerpoint – presentation of information

Statistical Packages◦ Excel add-in Analysis toolpak◦ SPSS◦ SAS

CrimeStat III◦ Spatial statistics

Tools of the trade Off the shelf additional programs

◦ Crime View◦ Crime Analysis Tools◦ Hawthe’s Tools◦ Curve expert (regression curve analysis software)◦ Coplink◦ Oracle spatial ◦ SQL Server◦ ATAC◦ Etc

Data Sharing Criminals do not care about imaginary borders along

the roads dividing adjacent cities – why should we? Data sharing has increased since 911, but still have

a way to go Biggest problem is politics not technology right now Data sharing systems are inter-agency and can be

expensive We need more privacy impact assessments on all

the data that is being shared Movement toward NIEM

◦ http://www.niem.gov/

Knowing which data sources to use and how to share the completed analysis (whether in report or map form) is diverse and complex.

Understanding and clearly articulating the limitations of the data used is also necessary

Understanding the legal and ethical issues involved with distributing crime maps, data, and analysis is imperative for crime analysts

Conclusions