crime pattern theory
TRANSCRIPT
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
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Crime Pattern Theory
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
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Understanding Patterns
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Crime Pattern Theory
• 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
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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
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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.
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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.
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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.
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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
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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
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Shopping &
EntertainmentShopping &
Entertainment
Work
Home
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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.
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Potential Targets
Crime Template
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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.
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W1 W2
W3
H1H2
H3
S&E1 S&E2
S&E3
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W3W1
W2
H1
H3
H2High
Occurrence
Low
Occurrence
S&E
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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.
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Amsterdam Realtime:project by Waag Society together with Esther Polak and Jeroen Kee.
http://www.waag.org/realtime/
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Nice weather cyclist
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Marathon Runner
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Snapshot of one week
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Understanding Patterns
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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
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Katie Wuschke- Major Paths and
Nodes
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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
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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
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Results: Phase I
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Nick Malleson- Leeds
• Only burglary from properties in awareness space
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Agent Movements
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Space SyntaxTools for the Analysis of Spatial Configurations in the Built Environment
Dr. Patricia Brantingham, Jordan Ginther
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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
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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
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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
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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
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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
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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
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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
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Digitizing People’s Perception of Crime
All polygons from the 1997
survey
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Perceptions of Crime Commercial Dr.
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Kernel Density Analysis
Kernel density estimation
Percent volume contour
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Topological transformations common maps to cartograms
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Thanks!