Descriptive Spatial Analysis
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Definition of Crime Mapping
Single Symbol Mapping
Buffers
Chart Mapping
Graduated Mapping
Hotspot Analysis
Practical Examples
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Definition of Crime Mapping
 Crime analysis is …
 A geographic information system (GIS) is a set of computerbased tools that allow a person to modify, visualize, query,
and analyze geographic and tabular data.
 Consequently, computerized crime mapping is the process of
using a geographic information system in combination with
crime analysis techniques to focus on the spatial context of
criminal and other police activity.
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Source: Boba, R. (Forthcoming). Crime mapping. In Encyclopedia of criminology. Chicago: Fitzroy Dearborn Publishers.
Police Foundation, 2003: Grant #2002-CK-WX-0303
Single Symbol Mapping
 Uses individual symbols to represent point, line,
and polygon features.
 Allows for a detailed analysis of small amounts of
data.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example: Too Much Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example: Tabular Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example: Geographic Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example: Geographic Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Buffers
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A buffer is a zone of a specified distance around a
feature.
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Points, lines, and polygons can be buffered.
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Buffers are useful for proximity analysis and can be
designated at one or many intervals (e.g., 500 feet,
1,000 feet, 1 mile).
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Buffers: Point Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Buffers: Line Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Buffers: Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Chart Mapping
 A chart map allows for the display of the
values of many data attributes at once with
either a pie or a bar chart.
 The mapping program takes the values for
numerous variables and displays them in a
pie or a bar chart on the designated location
on the map.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Chart Mapping: Pie Chart Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Chart Mapping: Bar Chart Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Size Mapping
 Data are summarized so that symbols (point or line
features) are altered in size to reflect the
frequencies in the data.
 Reflect more incidents at a given location with a
larger symbol or a thicker line.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example: Too Much Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Size Point Mapping Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Size Line Mapping Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Color Mapping
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Point, line, or polygon features are shaded according to a
statistical formula, custom setting, or unique value. Also
called choropleth mapping.
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Most Commonly Used: Unique Value, Natural Breaks
(default), Custom.
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Others: Quantile, Equal Area, Equal Interval, Standard
Deviation.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Points Shaded by Unique Value: Geographic Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Points Shaded by Unique Value: Geographic Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Points Shaded by Unique Value: Tabular Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Points Shaded by Unique Value: Tabular Data
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Natural Breaks
 The default classification method in most GIS programs.
 Identifies natural break points between classes using a statistical formula.
Graduated Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Custom
 Ranges can be determined by the user and are not based on the data.
 Important for comparing the same type of data over time.
Graduated Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Quantile
Each class contains the same number of features (data points).
Graduated Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Equal Interval
 Divides the range of attribute values into equal sized sub-ranges.
 Features are then classified based on the sub-ranges.
Graduated Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Standard Deviation
The GIS determines the mean value and then places class breaks above and
below the mean based on the standard deviation.
Graduated Polygon Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Use of Classifications
 Classifications are the descriptive statistics of spatial analysis. Thus,
they should be controlled by the analyst and carefully applied.
 A danger is that the GIS has defaults (natural breaks into five categories)
and analysts do not change them.
Guidelines:
 Use most, if not all, of the classifications in the beginning of the analysis
to determine the nature of the data and its distribution.
 Experiment with number of categories and classifications to see how the
maps change.
 Determine the purpose of the analysis and choose the best classification.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Exercise
Scenario:
You are a member of a problem-solving team
tasked with addressing an ongoing robbery
problem in the city. You have been asked to
bring an analysis of robbery to the first meeting.
What type of map would you bring?
How much data?
Which unit of analysis?
Which classification?
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Points
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Color Polygons: Natural Breaks
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Graduated Color Polygons: Standard Deviation
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Exercise
Scenario:
As part of an impact evaluation for a problem
analysis project to reduce commercial burglary,
you are asked to prepare a map that compares
before and after (same amount of time) the
response by block group.
How would you present this in two maps?
In one map?
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Police Foundation, 2003: Grant #2002-CK-WX-0303
First of two maps
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Second of two maps
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Police Foundation, 2003: Grant #2002-CK-WX-0303
In one map: Difference between Pre and Post
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Exercise
Scenario:
The chief asks you to examine aggravated assault and
simple assault in the city to see if there are
differences in the relative frequencies by block
group (or other polygon). That is, are there some
areas that are higher in aggravated assault than
others and are those the same that are higher in
simple assault?
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Using Standard Deviation: Aggravated Assault
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Using Standard Deviation: Simple Assault
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Using Quantile: Aggravated Assault
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Using Quantile: Simple Assault
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
In this context, the term hotspots refers to concentrations of events
confined to a particular geographic area that occur over a specific
time period. Hotspots are also referred to as clusters or
concentrations.
Methods for determining hotspots…
1. Graduated color maps
2. Map grids
3. Ellipses
4. Kernel density interpolation
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
Graduated Color Maps
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Point, line, or polygon
features are shaded
according to a statistical
formula, custom setting,
or unique value.
In this example, census
groups are shaded by the
number of incidents.
Note: incidents are placed on the
map at their address
location for reference.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
Map grids
 Each grid cell is shaded
according to the
number of incidents.
 Unlike the preceding
graduated color map,
this method allows for
smaller search areas.
 However, the grids are
arbitrary and may not
depict realistic
separation of land
areas.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
Ellipses
 Ellipses are drawn around the
most dense concentrations of
activity.
 Software such as S.T.A.C.
(Spatial and Temporal
Analysis of Crime), developed
by the Illinois Criminal Justice
Information Authority
(ICJIA), uses a statistical
method to find clusters.
2nd order cluster
1st order clusters
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
Kernel Density Method
 A grid is applied to the
map, and a “score” is
derived based on the
number of incidents within
each grid cell as well as the
distance to other incidents.
 Cell size and search radius
can be dictated by the user.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Hotspot Analysis
Factors to consider:
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Definition of a hotspot
Choice of variables
Number of hotspots
Scale
Grid size and search area
Visual display
Comparisons
There are many different methods of hotspot analysis, and each
technique will reveal different groupings and patterns
within the groups.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Practical Examples of Descriptive Mapping
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Police Foundation, 2003: Grant #2002-CK-WX-0303
To assist in resource allocation of ATF agents: analysis of gun tracing
incidents per county for numerous states.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
To assist in resource allocation of ATF agents: analysis of number of
agents per county for numerous states.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
To assist in resource allocation of ATF agents: analysis of gun tracing
incidents and number of agents per county for numerous states.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Problem Analysis Project Discussion
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Local Level Risk Assessment
for Homeland Security
 Various geographic data are used in combination
to assign a score to an area. The score is a
combination of values (weighted) that can be
based on either the presence/absence of features.
 The result is a thematic shading of polygons with
the darkest (highest score) implying a higher risk.
(Note that there is no probability assigned, only a
score.)
 This method can be used for other types of crime
(e.g., risk of auto theft, robbery, etc.)
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Features to Consider
 Nuclear power plants
 Ammonium nitrate
repositories
 Airports
 Amtrak
 Mass transit lines
 Amusement parks
 Malls
 Hydro Plants
 Landmarks
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Research laboratories
Dams
Petroleum refineries
Ports
Government buildings
Interstates
Rivers
Population levels
Major utility lines
Etc.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Example
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Zones containing some part of a government building or property (note polygons).
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Zones through which rivers flow.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Zones that border railroads.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Zones that contain schools.
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Police Foundation, 2003: Grant #2002-CK-WX-0303
All Zones within ½ mile of major research facilities (weighted).
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Total Risk Assessment
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Alternative method: Using arbitrary grids (same sized area).
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Caution
This method is not tested, and many decisions
are subjective (e.g., what data to include,
values given to the variables).
Also…
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What should the unit of analysis be? Beat? Grid?
If an arbitrary grid, what should the grid area be? What should the
grid cell size be?
Which of the many types of data available should be included and
when? (Different jurisdictions will include different types of data.)
How should the variables be scored in relation to one another? For
example, should nuclear facilities be weighted more than malls?
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Police Foundation, 2003: Grant #2002-CK-WX-0303
Problem Analysis Project Discussion
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