crime pattern theory

Institute for Canadian Urban Research Studies

Crime Pattern Theory

P. L. Brantingham, RCMP University Professor of Computational CriminologyP. J. Brantingham, RCMP University Professor of Crime Analysis



Man is not a circle with a single centre; he is an ellipse with

two foci: Facts are one, ideas are the other.

Victor Hugo; Les Miserables

Science is built up with facts, as a house is with stones. But a collection of facts is no more a science than a heap of stones is a house.

Henri Poincaré; La Science et l’Hypothèse


Understanding Patterns



• Complexity of the criminal event

• Crime is not random

• Criminal opportunities are not random

• Offenders and victims are not pathological in their use of time and space


Crime opportunities and events:

• Routine Activities

▫ The daily rhythm, Activity Space

• Awareness space

▫ Around Activity Space

• Social Networks

▫ Family, friends, repeat contacts

• Urban Structure

▫ Nodes, paths, edges


Rule 1: As individuals move through a series of

activities they make decisions. When activities are

repeated frequently, the decision process becomes

regularized. This regularization creates an abstract

guiding template. For decisions to commit a crime this

is called a crime template.


Rule 2: Most people do not function as individuals, but have a

network of family, friends and acquaintances. These linkages

have varying attributes and influence the decisions of others in

the network.


Rule 3: When individuals are making their decisions

independently, individual decision processes and crime

templates can be treated in a summative fashion, that is,

average or typical patterns can be determined by combining

the patterns of individuals.


Rule 4: Individuals or networks of individuals commit

crimes when there is a triggering event and a process

by which an individual can locate a target or a victim

that fits within a crime template. Criminal actions

change the bank of accumulated experience and alter

future actions.

Individual Triggering EventCrime

Attempted

Success/

Failure

Past experiences

Range of motivations

Range of opportunities


Rule 5: Individuals have a range of routine daily activities.

Usually these occur in different nodes of activity such as

home, work, school, shopping, entertainment or time with

friends that are nodes of activity and along the normal

pathways between these nodes.

Home

Work

Shopping and Entertainment


Shopping &

EntertainmentShopping &

Entertainment

Work

Home


Rule 6: People who commit crimes have normal

spatio-temporal movement patterns like everyone else.

The likely location for a crime is near this normal

activity and awareness space.


Potential Targets

Crime Template


Target and Victim Locations

Rule 7: Potential targets and victims have passive or active

locations or activity spaces that intersect the activity spaces of

potential offenders. The potential targets and victims become

actual targets or victims when the potential offender’s

willingness to commit a crime has been triggered and when the

potential target or victim fits the offender’s crime template.


W1 W2

W3

H1H2

H3

S&E1 S&E2

S&E3


W3W1

W2

H1

H3

H2High

Occurrence

Low

Occurrence

S&E


Urban Backcloth

Rule 8: The prior rules operate within the built urban form.

Crime generators are created by high flows of people through

and to nodal activity points. Crime attractors are created

when targets are located at nodal activity points of individuals

who have a greater willingness to commit crimes.


Amsterdam Realtime:project by Waag Society together with Esther Polak and Jeroen Kee.

http://www.waag.org/realtime/


Nice weather cyclist


Marathon Runner


Snapshot of one week


Understanding Patterns


Data

• Linked crimes and people for 5 yrs in BC

• All lots in Greater Vancouver

• Detailed street information

• Many possibilities

• A few research projects mentioned here


Katie Wuschke- Major Paths and

Nodes


Motor Vehicle Theft (a)

Buffer (meters)

% of Crimes Contained by

Buffer

% of Area Contained by

Buffer

% of Road Distance

Contained by Buffer

Ratio: %Crime /

%Area

Ratio: %Crime / %

Road Distance

50 27.57 14.19 25.37 1.94 1.09

100 34.68 17.48 29.54 1.98 1.17

150 43.52 20.02 33.21 2.17 1.31 200 51.59 22.09 36.56 2.34 1.41

250 58.51 23.92 40.19 2.45 1.46

300 63.97 25.54 43.26 2.50 1.48


Assaults (b)

Buffer (meters)

% of Crimes Contained by

Buffer

% of Area Contained by

Buffer

% of Road Distance

Contained by Buffer

Ratio: %Crime /

%Area

Ratio: %Crime / %

Road Distance

50 31.47 14.19 25.37 2.22 1.24 100 38.73 17.48 29.54 2.22 1.31

150 46.88 20.02 33.21 2.34 1.41 200 54.40 22.09 36.56 2.46 1.49

250 61.11 23.92 40.19 2.55 1.52

300 66.11 25.54 43.26 2.59 1.53


Results: Phase I


Nick Malleson- Leeds

• Only burglary from properties in awareness space


Agent Movements


Space SyntaxTools for the Analysis of Spatial Configurations in the Built Environment

Dr. Patricia Brantingham, Jordan Ginther


Depthmap MeasuresClustering Coefficient• Used to detect junction

points in space

• Areas of high “junctioness” represent pause points where people may stop to scan the environment

• These areas, for example, would be ideal for the placement of security guards who need to be able to see large areas from one point


Depthmap MeasuresControl• For each point, represents a

summation of the inverse connectivity of each connected cell (how many cells it can “see”)

• Cells with lower connectivity are given a higher weight, therefore cells with high control “see” a lot of cells which see relatively little

• Good areas to place security cameras, for example


Depthmap MeasuresMean Depth• The average number of

steps (turns) required to reach the current location from any point on the map

• Environments with overall low mean depth are generally easy to navigate

• Placement of fire extinguishers and alarms in areas of low mean depth would allow quick access in case of emergency


Depthmap MeasuresIntegration• Identifies the level of

accessibility at any given point in the environment

• Pedestrian movement tends towards areas of high integration as they are easier to navigate

• These would be good areas to place advertising or increased lighting, for example


Depthmap ExampleKabul City Market• The highlighted area in the

image represents the open air market and surrounding neighbourhood in Kabul Afghanistan

• Obtained from Google maps, therefore analysis was limited to the quality of the photo


Depthmap ExampleKabul City Market• The areas in purple are

representations of buildings which occupy the region

• All areas in yellow are considered “open space” navigable on foot


Depthmap ExampleKabul City Market• This image represents the

measure Control as determined by analysis of the open air market

• A measure based on connectivity, or how much a cell can “see”

• In order for a point to be controlling it should be able to see a large number of spaces which see relatively little

• The red and orange areas depicted in this image identify areas with high control


Digitizing People’s Perception of Crime

All polygons from the 1997

survey


Perceptions of Crime Commercial Dr.


Kernel Density Analysis

Kernel density estimation

Percent volume contour


Topological transformations common maps to cartograms


Thanks!

crime pattern theory

Documents

open air market

rcmp university

nodal activity

crimes contained

crime template

commit crimes

understanding

image represents