Chapter 1 Reading: Comprehensive Study Guide: Fundamentals of Crime Mapping, Spatial Analysis, and Environmental Criminology
Conceptual Framework of Crime as a Criminal Event
Multi-Dimensional Perspective:
Traditional criminology historically focused almost exclusively on a single point of view, such as understanding the motivation of the offender without integrating victim attributes or environmental variables.
Viewing crime as a criminal event (Sacco & Kennedy, 2002) expands this view by studying crime across three interconnected dimensions: offenders, victims, and the immediate environment.
This approach examines not only offender motivations and victim behaviors, but specifically how offenders and victims interact with each other and their surroundings.
Spatial Context and Environmental Cues:
The immediate spatial environment provides varying opportunities for criminal behavior.
Environmental properties offer specific cues to both offenders and victims that directly impact their decision-making processes.
Properties of immediate physical space in and around a criminal event act as contributing factors to victimization and cannot be excluded from criminological research.
Scope of Spatial Analysis:
Understanding the historical context of crime mapping is essential for evaluating current practices and future developments in the discipline.
Spatial analysis relies on fundamental cartographic terminology, distinct map visual formats, specialized software applications, and analytical methodologies.
Theoretical Perspectives on Crime and Geography
Foundational Criminological Concepts:
Criminology is defined as the formal study of crime and criminal behavior.
There is no single, universally accepted theory that accounts for all criminal events within a society.
Consensus Perspectives: Conceptualize crime as a normal, predictable, and healthy component of a functioning society.
Conflict Perspectives: View crime as an inevitable byproduct of group conflict, social inequality, and unequal distributions of power.
Levels of Theoretical Application:
Macro-Level Theories: Focus on societal-level variables, including structural elements of government, macroeconomic conditions, and systemic socio-economic factors. They aim to explain crime rates across large geographical entities such as cities, states, nations, or global regions.
Micro-Level Theories: Focus on individual-level characteristics, such as intelligence quotient (IQ), psychological state, temperament, biological factors, and personal finances, to explain an individual's decision to commit a crime.
Theoretical Disconnect: Empirical findings at the macro level do not always translate to the micro level, and vice versa.
The Paradigm Shift Toward Crime as an Event:
Historically, criminological models focused strictly on the offender or offender groups while ignoring contextual contributors.
Theorists expanded explanations to incorporate victim behaviors (Cohen & Felson, 1979; Clarke & Felson, 1993) and the physical environment (Brantingham & Brantingham, 1981, 1993).
This expanded view treats crime as an event resulting from dynamic interactions between victims, offenders, and physical space over time.
The adoption of geographic information systems (GIS) and widespread spatial-temporal data collection transformed crime mapping into a vital tool for theoretical development and crime prevention policy.
Social Disorganization Theory:
Formulated by Shaw and McKay (1942), building on earlier ecological research by Park (1915) and Burgess (1925).
Core Premise: The economic composition of a community impacts neighborhood social order, directly influencing juvenile delinquency rates.
Neighborhood Dynamics: High-crime urban areas suffer from poverty, high population density, high population mobility, and residential instability. These conditions degrade physical appearance and weaken local social structures.
Convergence of Factors: Socially disorganized neighborhoods foster environments where high concentrations of motivated offenders and suitable targets coexist with minimal or non-existent guardianship.
Key Finding: Delinquency rates remained consistently high in specific disorganized neighborhoods over time, regardless of which ethnic group resided there (including Italian, Russian, Cape Verdean, or Cuban populations). This demonstrated that the area itself is criminogenic, rather than the specific ethnic or demographic groups living within it.
Environmental Criminology Framework:
Serves as an umbrella theoretical framework housing Routine Activities Theory, Rational Choice Theory, and Crime Pattern Theory.
Cone of Resolution: Conceptualized by Brantingham, Dyreson, and Brantingham (1976) to examine regional variation in crime rates across spatial scales.
Four Key Elements of Crime: Brantingham and Brantingham (1981) asserted that understanding crime requires analyzing four essential dimensions:
The Law
The Offender
The Target
The Place
Analytical Focus: Evaluates features of physical space, including land use patterns, accessibility, and visual line-of-sight, to identify locations conducive to criminal behavior.
Practical Applications: Provides actionable strategies through Situational Crime Prevention and Crime Prevention Through Environmental Design (CPTED) (Crowe, 2000; Rosenbaum, Lurigio, & Davis, 1998).
Examples: Enhancing lighting or restricting vehicle entry points in parking lots reduces automobile thefts; installing well-lit walkways and emergency call boxes reduces personal violent crimes on university campuses.
Routine Activities Theory:
Developed by Cohen and Felson (1979).
Core Equation: Crime occurs when three core elements converge simultaneously in space and time:
A motivated offender
A suitable target
The absence of a capable guardian
Micro-Level Application: An individual walking alone through a dark park late at night displaying an expensive iPod faces high victimization risk; conversely, a couple walking a large dog in the same park without visible valuables presents low target suitability and high guardianship.
Macro-Level Shifts: Macro-level changes in societal routine activities alter overall victimization trends. For example, according to the Bureau of Labor Statistics (2011), the labor force participation rate for civilian, non-institutionalized women aged 16 and older rose from in 1970 to in 2009 (with a projected increase between 2008 and 2018). This macro-level shift left a significantly higher proportion of residential homes unattended during daytime hours, providing opportunities for daytime residential burglaries.
Crime Pattern Theory:
Proposed by Brantingham and Brantingham (1993).
Integrates concepts from Environmental Criminology, Rational Choice Theory, and Routine Activities Theory to model how offenders navigate space and encounter targets during their daily routines.
The Problem Analysis Triangle and Emergence Perspective
Spatial Typologies of Criminal Events:
Private Spaces: Homes or domestic settings (e.g., residential burglary, domestic violence).
Semi-Public Spaces: Workplaces or educational institutions (e.g., workplace assault, embezzlement).
Public Spaces: Roads, paths, public parks, entertainment districts (e.g., street robbery, stranger assault, riots).
Removing any single element (target, offender, or spatial convergence) significantly decreases the likelihood of a criminal event.
The Problem Analysis Triangle (Crime Triangle):
Expanded by Clarke and Eck (2005) from Routine Activities Theory by adding specific "Controllers" for each core element:
Inner Triangle: Offender, Target/Victim, Place.
Outer Triangle (Controllers):
Handlers: Individuals who exert control over motivated offenders through informal social control (e.g., parents, family members, teachers, friends) or formal social control (e.g., probation officers, parole officers).
Guardians: Individuals or mechanisms protecting targets/victims (e.g., targets protecting themselves, bystanders, police officers, private security guards).
Managers: Entities possessing operational or legal responsibility for managing human behavior within a specific physical space (e.g., homeowners managing their property, teachers managing classrooms, bar owners/managers controlling behavior in licensed establishments).
The Emergence Perspective:
Advanced by McGloin, Sullivan, and Kennedy (2012) in When Crime Appears: The Role of Emergence.
Posits that crime analysis must move beyond static mapping of existing high-density crime areas to analyze how crime emerges across complex environments.
Core Analytical Requirements: Criminologists must evaluate the individual, the situation, the interaction between individual and situation, the role of learning on future behavior, and non-linear methodologies to capture complex dynamics.
Methodological Premise: Crime emergence is non-linear, does not follow rigid traditional linear statistical patterns, and is not bound to a single theoretical perspective.
Analytical Rigor and Hypothesis Testing:
Mapping raw data is only an initial step; raw spatial data requires analytical processing to extract actionable intelligence.
Analysts generate and test hypotheses (empirically testable statements derived from theoretical models).
Analytical Inquiries: Evaluating whether linked incidents share a single perpetrator, examining similarities in method of operation (MO), and determining temporal/spatial relationships across incident clusters.
Categorization of Law Enforcement Analysis
Three Core Branches of Law Enforcement Analysis:
Identified by Bruce (2004) and Gottlieb, Arenberg, and Singh (1994) as: Crime Analysis, Criminal Intelligence Analysis, and Criminal Investigative Analysis.
Formal Definitions of Crime Analysis:
Boba (2005): The systematic study of crime and disorder problems as well as other police-related issues—including sociodemographic, spatial, and temporal factors—to assist police in criminal apprehension, crime and disorder reduction, crime prevention, and evaluation.
International Association of Crime Analysts (IACA, 2005): A type of law enforcement analysis focused on the study of criminal incidents; the identification and analysis of patterns, trends, and problems; and the dissemination of information that helps a police agency develop tactics and strategies to solve patterns, trends, and problems.
Integrated Data Inputs: Uses incident records, arrest data, calls for service (CFS), traffic citations, motor vehicle crashes, demographic census data, weather patterns, traffic movements, and partner agency records (such as probation and parole data).
Subfields of Crime Analysis:
Tactical Crime Analysis:
Focuses on short-term, recent criminal incidents to identify immediate patterns, series, suspects, and leads (Boba, 2005).
Primarily targets crimes where victims and offenders are unknown to one another (stranger crimes).
Evaluates micro-level event characteristics: point of entry, method of entry, suspect actions, victim demographics, weapons used, and exact temporal/spatial stamps.
Integrates field intelligence: field interrogation (FI) cards, suspicious activity reports, criminal trespass notices, calls for service, and suspect descriptors (scars, marks, tattoos).
Uses spatial mapping to detect geographic clustering and predict future target locations for tactical surveillance deployment or geographic offender residence profiling.
Strategic Crime Analysis:
Examines long-term spatial and temporal crime patterns, long-standing problems, and evaluation of organizational responses (Boba, 2005).
Identifies underlying root causes of institutionalized crime problems to design sustainable problem-solving solutions (IACA, 2005).
Serves as the operational backbone for agency-wide crime reduction and prevention strategies.
Administrative Crime Analysis:
Focuses on conveying analytical findings, administrative statistics, and empirical research to internal executive leadership, government stakeholders, and the public (Bruce, 2004).
Examples: Compiling jurisdictional demographic transition reports, assembling statistical metrics for grant proposals, generating Uniform Crime Reporting (UCR) or National Incident-Based Reporting System (NIBRS) submissions, and maintaining public-facing safety dashboards.
Police Operational Analysis:
Evaluates internal agency operations, staffing allocations, shift scheduling, and spatial resource deployment to eliminate operational inefficiencies and maximize resource allocation (Bruce, 2004).
Distinctions from Related Analytical Disciplines:
Criminal Intelligence Analysis: Focuses on organized criminal networks, enterprise syndicates, and political security threats. Analyzes connections between individuals, organizations, properties, and events using non-incident data, including court-authorized wiretaps, financial statements, tax records, travel logs, surveillance reports, and social network associations (Boba, 2005).
Criminal Investigative Analysis: Focuses on serial, violent offender behavior across multi-jurisdictional incidents (Boba, 2005). Analyzes physical crime scene evidence, victimology, behavioral signatures, and offender patterns to construct behavioral and geographic profiles (Rossmo, 2000).
Operational Philosophies and Theoretical Frameworks:
CompStat: Emerged in the 1990s within the New York City Police Department, combining rapid crime data tracking, spatial analysis, targeted resource deployment, and executive management accountability.
The Geographic Approach: Conceptualized by Esri President Jack Dangermond (2007) as a methodology using spatial science supported by GIS technology to understand complex phenomena, guide human decision-making, and solve structural problems.
Historical Evolution of Crime Mapping
Early Foundations (1800s):
Adolphe Quetelet and A. M. Guerry conducted early spatial analyses of crime in France using demographic and legal datasets.
Established that crime is non-randomly distributed across space and clusters in specific geographic areas alongside socio-economic metrics like poverty and population density.
The Early to Mid-Twentieth Century:
Early 1900s: Major urban police departments (including the New York Police Department) introduced manual pin maps using single-symbol pushpins on wall maps to track crime locations.
1920s–1930s: Sociologists at the University of Chicago created hand-drawn, labor-intensive graduated area maps linking juvenile delinquency to urban structural factors (such as poverty).
Mainframe and Early Computerization (1960s–1980s):
1960s–1970s: Transitioned to mainframe computers. These systems were expensive, restricted to large agencies, labor-intensive, and produced low-resolution graphics unfit for daily police operations.
1980s: Introduction of initial desktop mapping environments; limited by low processing speeds, inadequate system memory, and primitive print output capabilities.
The GIS Revolution (1990s–Present):
1990s: Desktop GIS software matured, enabling integration with digital police Record Management Systems (RMS), computer-aided dispatch (CAD) databases, and federal census metrics.
Growth Drivers: Expanded federal grant funding, standardized analytical training, hardware improvements, affordable desktop computing, and post-9/11 intelligence-led policing mandates.
Institutional Adoption Patterns: Research demonstrates varying levels of GIS adoption across agencies (Chamard, 2006; Mamalian et al., 1999; Paynich, Cooke, & Mathews, 2007):
Large Agencies: Fully integrated crime mapping into daily operations due to larger operating budgets, specialized analytics personnel, and complex spatial jurisdictions.
Small to Mid-Sized Agencies: Slower adoption rates, historically limited by low incident volumes, staffing constraints, and equipment costs. However, falling hardware costs, cloud-based tools, and standardized training continue to expand adoption across smaller departments.
Cartographic Foundations and Map Information Systems
Basic Definitions and Concepts:
Map: A two-dimensional or flat-scale representation of the Earth's surface or a portion thereof (Rubenstein, 2003).
Cartography: The formal science and art of mapmaking.
Geographic Information Systems (GIS) Architecture:
Definition: High-performance software environments designed to collect, store, query, analyze, and display spatially referenced data.
Five Core Components: Hardware, Software, Data, Personnel, and Methods.
Overlay Concept (Virtual Layering):
Spatially referenced dataset attributes are organized in distinct digital overlay layers (e.g., police beat boundaries, street networks, school locations, violent crime points).
Analogy: Transparent anatomical overlays in a medical textbook showing individual bodily systems (skeletal, vascular, muscular) independently or stacked together to show systemic interactions.
Geoprocessing: Combining multiple spatial data layers to uncover underlying environmental and spatial relationships.
Projections and Spatial Reference Systems:
Projection: Mathematical transformations used to project the three-dimensional, spherical surface of the Earth onto a flat, two-dimensional surface.
Distortion: All projections introduce spatial distortion (area, shape, distance, or direction). Cylindrical and conical projections are commonly used, with distortion increasing over larger geographical areas.
Spatial Scale Impact: For localized police jurisdictions, projection distortion is minimal and often negligible (Harries, 1999). However, precise projection identification becomes vital when combining multi-agency datasets or conducting regional analyses.
Geocoding: The spatial process of assigning point locations on a map surface by converting physical street addresses or intersecting points into coordinate values (latitude and longitude).
Projections vs. Coordinate Systems: "Projections determine how the latitude and longitude grid of the earth is represented on paper. Coordinate systems provide the reference system to describe locations in two-dimensional space" (Harries, 1999, p. 14).
GIS Feature Types, Data Models, and Map Typologies
Vector Spatial Data Models:
Vector models represent features with discrete coordinate boundaries that do not continuously cover the entire map space.
Point Features: Discrete spatial points defined by single coordinate pairs (). Examples: incident locations, motor vehicle crashes, traffic signs, police facilities, cell towers.
Line Features: Linear spatial networks formed by connected coordinate sequences. Examples: street centerlines, railways, rivers, electrical powerlines, public transit bus routes.
Polygon Features: Multi-sided, closed area boundaries defined by enclosed coordinate loops. Examples: municipal boundaries, census tracts, census blocks, police patrol beats, neighborhood boundaries, gang territories, parks, individual building footprints.
Raster Spatial Data Models:
Raster models structure space as a continuous grid matrix of square cells (pixels), where every pixel contains a numerical attribute value.
Image Features: Aerial photogrammetry and satellite imagery converted into spatial pixel grids.
Hotspot Density Surfaces: Continuous statistical surface grids where pixel color values represent concentrations of underlying events.
Attribute Tables:
Every spatial vector or raster feature is explicitly linked to an underlying tabular dataset known as an attribute table.
Enables spatial querying, logical filtering, and statistical manipulation. Clicking a point on a spatial map opens its attribute record, displaying variables such as incident time, date, offense classification, victim/offender demographics, weapons used, and structural location descriptions.
Common Analytical Map Types:
Single-Symbol Point Maps (Pin Maps): Displays discrete spatial incident locations using uniform point symbols.
Choropleth Maps (Graduated Color Maps): Displays aggregated data across polygon boundaries (such as census tracts or police beats) using shaded color fills corresponding to statistical ranges or crime rates.
Hotspot Maps: Displays continuous spatial density concentrations to identify high-volume incident clusters.
Series/Pattern Maps: Maps chronologically connected offenses committed by a single offender or offender group across space.
Risk Terrain Maps: Advanced predictive models developed by Caplan and Kennedy (2011) that analyze multi-layered environmental risk factors (e.g., liquor stores, pawn shops, cash-checking businesses) to predict where future crime hotspots are likely to emerge.
Specialized Software, Analytic Tools, and Organizational Resources
Commercial and Desktop GIS Software:
ArcGIS: Developed by Esri (
www.esri.com), ArcGIS represents the most widely deployed commercial GIS platform among United States law enforcement agencies (Paynich et al., 2007).MapInfo: Developed by Pitney Bowes (
www.mapinfo.com), MapInfo is a leading commercial desktop mapping system widely used in public safety applications.CrimeView: An analytical extension software package developed by The Omega Group for ArcGIS. Automates hotspot generation, tracks threshold alert limits, and generates cyclical spatial reports.
Open-Source and Specialized Statistical Applications:
GeoDa: A free, standalone spatial analysis platform created by Dr. Luc Anselin (formerly at the University of Illinois) designed to introduce spatial econometrics and exploratory spatial data analysis.
CrimeStat: A free, standalone spatial statistics program developed by Dr. Ned Levine & Associates under research grants provided by the National Institute of Justice (NIJ) (Levine, 2003). It calculates spatial statistical routines (e.g., mean center, standard deviational ellipse, spatial autocorrelation, spatial kernel density estimation). Operational Requirement: CrimeStat produces numerical output tables and GIS layer files; it must be used alongside a visual mapping platform (such as ArcGIS or MapInfo) to visually render the spatial outputs on a map surface.
Federal and Professional Organizational Resources:
Mapping and Analysis for Public Safety (MAPS): A specialized research program operated within the National Institute of Justice (
www.nij.gov/nij/topics/technology/maps/welcome.htm).Office of Community Oriented Policing Services (COPS): Federal program providing grants, technical assistance, and spatial research resources (
www.cops.usdoj.gov/).Center for Problem-Oriented Policing (POP Center): Educational clearinghouse detailing problem-directed intervention guides using the Scanning, Analysis, Response, and Assessment (SARA) model (
www.popcenter.org/about/?p=sara).LeAnalyst Listserv: An international, web-based listserv community dedicated to professional crime analysts and spatial mappers (
http://sites.google.com/site/joinleanalyst/). Hosts technical discussions regarding software compatibility, advanced quantitative methods, data sourcing, and analytical workflows.
Comprehensive Chapter Glossary
Administrative Crime Analysis: The presentation of key findings of crime research and analysis to audiences within law enforcement, local government, and citizenry based on legal, political, and practical concerns.
Cartography: The formal science and art of mapmaking.
CompStat: The term generally associated with the New York model of policing, which includes accountability, crime mapping and analysis, and problem-solving processes by the police department to reduce crime; often utilized by other police departments in a variety of forms to help focus efforts in targeted areas in an organized, strategic manner.
CPTED: Acronym for Crime Prevention Through Environmental Design. Refers to strategies to reduce crime that incorporate making changes to the physical environment to limit the opportunity for crime to occur.
Crime Analysis: The study and analysis of crime and crime-related factors in efforts to inform and develop strategies to reduce crime and the fear of crime.
Criminal Intelligence Analysis: Examines organized criminal activity and seeks to link people, events, and property using specialized non-incident intelligence datasets.
Criminal Investigative Analysis: Focuses on serial offenders by studying victim characteristics and crime scene elements to discover behavioral patterns that link related crimes together.
Criminology: The formal study of crime and criminal behavior.
Geocoding: The process of positioning street addresses and geographic reference points onto a map using latitude and longitude coordinates for computer mapping and analysis.
Geographic Profiling: Developing a spatial profile of an offender's likely residential or operational anchor points based on crime scene locations and spatial case evidence.
Hypotheses: Empirically testable statements derived from theoretical framework assertions that can be evaluated to support or disprove theoretical assumptions.
Macro: Level of criminological theory focusing on societal-level variables, including governmental structures, national economies, and broad institutional forces across cities, states, countries, or regions.
Micro: Level of criminological theory focusing on individual-level variables, such as IQ, mental state, biological factors, and personal finances, to explain individual criminal decision-making.
Police Operational Analysis: Focuses on the internal operations of police agencies, including staffing models, shift efficiency, and spatial resource deployment.
Projection: The mathematical method used to transfer coordinate locations from the spherical, three-dimensional surface of the Earth onto a flat, two-dimensional map surface.
Scale: The mathematical ratio indicating how miniature a map representation is relative to actual ground distance; larger map scale displays smaller geographical area coverage in higher local detail.
Strategic Crime Analysis: The study of long-term crime trends, long-standing problems, and structural law enforcement issues to identify root causes and evaluate organizational problem-solving responses.
Tactical Crime Analysis: The daily examination of recent criminal events and potential criminal activity by analyzing how, when, and where incidents occur to establish operational patterns, series, suspect leads, and clearance strategies.