This paper investigates domain-adversarial transfer learning for small-area crime forecasting around the Sur-rey-Langley SkyTrain (SLS) expansion in British Columbia, Canada. A two-stage pipeline is proposed: it first trains a Domain-Adversarial Neural Network (DANN) on multi-city data (Surrey and Coquitlam) to learn domain-invariant representations from seasonal-average crime outcomes, coupled with rich covariates: socioeconomic and demographic indicators, transit accessibility, and region-popularity. The pipeline then freezes the extracted features and fits a LightGBM model to predict spatiotemporal crime patterns in the target city (Langley). Timeforward, cross-city evaluations show that DANN-derived features yield better generalization than city-specific models, pooled nonadversarial baselines, and LightGBM trained on raw inputs. Finally, scenario-based forecasts were executed for Langley under simulated post-SLS transit accessibility, producing fine-grained risk maps that highlight potential shifts near the future corridor and station areas. The results indicate that pairing adversarially learned, domain-robust representations with a strong tabular learner offers an effective strategy for transferring knowledge across municipalities and forecasting infrastructure-induced changes in urban safety. A key contribution of this work lies in demonstrating that such a transfer-learning pipeline can support planning decisions for data-scarce municipalities preparing for major transit expansions, where no local historical analogue exists.

Crime Pattern Theory predicts that crime concentrates along socioeconomic boundaries where routine activities overlap and informal guardianship is weak. Existing studies typically require boundaries to be specified in advance through land-use classifications or administrative divisions, introducing bias and sensitivity to arbitrary thresholds.This paper presents a topology-driven approach for detecting socioeconomic boundaries directly from urban data using persistent homology. Vancouver city blocks are represented as a weighted graph whose edge weights encode differences in property value, building age, and zoning composition. The method identifies persistent socioeconomic boundaries without requiring a pre-specified similarity threshold while preserving geographic interpretability.Applied to 2020 Vancouver Police Department Break & Enter records, boundary streets identified by the topological pipeline exhibit approximately 63% higher crime incidence per segment than interior streets (p < 0.0001 under 10,000 permutations). Sensitivity analysis shows that the effect is stable across parameter choices and is driven primarily by land-use transitions rather than by property value or building age alone. To our knowledge, this is the first application of persistent homology to empirical boundary detection in environmental criminology.

Commercial break and enters are of concern to Vancouver businesses. The proximity to rapid transit stations creates easy access to commercial buildings. This study investigates the impact of transit station proximity on crime rates, particularly focusing on the new Broadway Subway extension to the metro system. Grounded in environmental criminology theories, this research combines network analysis with machine learning and econometric methods to extract historical data and provide crime forecasts. This approach utilizes panel data to observe junctions over multiple years, then a double machine learning framework is applied to accurately measure the effect of transit station proximity on crime rates. These findings are used to forecast future crime occurrences in the neighbourhoods where the Broadway Subway extension will occur. This analysis also provides valuable insights for urban planning and public safety strategies.

In this article, we discuss the role of urban planning professionals in situational crime prevention. We begin by examining their role as city “shapers” and the reasons behind their frequent neglect of crime-related factors in their decision-making process. We also explore why criminology tends to underestimate the influence of urban planning professionals on the urban environment, a factor crucial for effective crime prevention. To highlight the disconnection between urban planning and crime prevention, we present findings from a survey conducted with urban planners and safety experts in 290 Swedish municipalities. The article concludes with future research and practice recommendations, stressing the urgent need for improved communication and collaboration between urban shapers and environmental criminologists and a more comprehensive understanding from all parties involved.

As access to public transportation expands, people increasingly find themselves able to travel to unfamiliar areas. Routing systems may assist people in navigating to unfamiliar locations by identifying the most efficient and safe paths for their journeys. However, most routing systems are optimized for vehicles and do not find the best routes for pedestrians. Additionally, pedestrians with mobility impairments have specific requirements that must be met for a route to be safe and traversable. These requirements may be different for each individual user. To address these issues, this study presents a sidewalk-based routing system that allows users to create accessibility profiles which the router uses to provide safe and accessible routes for that user.

Despite environmental criminologists emphasizing the role that both space and time play in the occurrence of crime, there is still only a small literature on the temporal rhythms of criminal behavior, especially those of sexual violence. Drawing from routine activities theory, this research uses circular statistics to investigate the temporal patterns of 2,260 sexual offenses from a Canadian police database at the seasonal-, monthly-, daily-, and hourly-levels, as well as their consistency over time. Findings suggest that there is a distinct temporal pattern when the unit of analysis is at the seasonal-, monthly-, and hourly-levels, but not at the daily-level. Furthermore, these temporal patterns are relatively consistent from year-to-year. These conclusions support the legitimacy of including a temporal element into current geographically-based sexual offender policies and practices. Pragmatically, these findings may also be used to better inform policing and situational crime prevention efforts to reduce the incidence of sexual crimes.

Vaughan, A., Andresen, M.A., Bent, R.C., Verdun-Jones, S., Brantingham, P.L., Hewitt, A., Hodgkinson, T., Ly, M., & Campbell, A. (2017). Policing and mental health: An investigation into police interactions with emotionally disturbed persons, Final Report. Burnaby, BC: ICURS

Some urban spaces are associated with disproportionate numbers of criminal events, while other areas are relatively free from disorder and crime. The relationship between urban space and crime concentration has received increased attention in recent years, with the location quotient frequently presented as a tool to identify and quantify such concentration. This measure has several limitations, with one significant concern surrounding the choice of denominator with which to standardize local and global rate calculations. In response, we present a new methodological adaptation to the location quotient, improving the measurement of crime concentration along linear features. To test this adaptation, we measure how crime concentrates by road classification at both a macro and micro level within two Canadian suburban municipalities. Using transportation network data, we identify the road types that are associated with a disproportionate concentration of criminal events, and illustrate how these relationships change alongside the level of aggregation. Results support the use of the adapted location quotient, finding that criminal events concentrate along specific road types, and emphasize the importance of spatial scale in understanding local relationships between crime and the built urban landscape.

Analysis of crime hot spots (spatial concentrations) and burning times (temporal concentrations) has become a major component of the work of criminologists, crime analysts and crime prevention practitioners. This paper lays out several specific elements of a expanded model of crime hot spot formation grounded in crime pattern theory.

The structure of the urban setting determines the crime patterns. This research explores the street profile analysis which is a new method for analyzing crime in relation to street networks. Street profile analysis can be used to identify crime surges or heavy concentrations of crime along roadways. In this study, the street profile technique is combined with a discrete calculus approach to locate the boundaries of small criminal spaces in the City of Vancouver, British Columbia, Canada. This experimental technique utilizes open source property crime data from the Vancouver Police Department to analyze crime patterns within Vancouver. This computational crime analysis technique is described in detail and the utility of this technique explored. The new technique is a valuable tool for the intelligence and security informatics communities.

This chapter discusses advances in visualization for environmental criminology. The environment within which people move has many dimensions that influence or constrain decisions and actions by individuals and by groups. This complexity creates a challenge for theoreticians and researchers in presenting their research results in a way that conveys the dynamic spatiotemporal aspects of crime and actions by offenders in a clearly understandable way. There is an increasing need in environmental criminology to use scientific visualization to convey research results. A visual image can describe underlying patterns in a way that is intuitively more understandable than text and numeric tables. The advent of modern information systems generating large and deep data sets (Big Data) provides researchers unparalleled possibilities for asking and answering questions about crime and the environment. This will require new techniques and methods for presenting findings and visualization will be key.

Purpose: Using both crime pattern and social disorganization theories, the current study investigates the characteristics of those places that experience high counts of reported sexual crime to police. Methods: Socio-demographic factors, land use, specific sexual crime attractors, and ecological variables are used to predict dissemination areas with high counts of sexual crime within a large city using 2180 founded crime events retrieved from a Canadian police database. Results: Socio-demographic and ecological factors, as well as the presence of particular sexual crime attractors, characterize these neighborhoods. For example, dissemination areas that have higher percentages of female, male, and single residents, as well as higher counts of rental units, bars, and schools, experience more sexual crimes. Land use does not predict dissemination areas with high counts of sexual crime. Conclusions: Both crime pattern and social disorganization theories provide a framework within which the nature of sexual crime places can be better understood. This information could be used to empower community members as to the types of places that are the riskiest for crimes of this nature, as well as to create a conversation about interventions that could be put in place at both the secondary and tertiary levels to prevent future occurrences.

A co-offending network, the network of offenders who have committed crimes together, is a prime source for crime investigation. Analyzing co-offending networks contributes to crime reduction and prevention strategies and tactics at different levels by extracting meaningful patterns and relationships. On a different track, spatial analysis of crime has recently enriched understanding of criminal activity extensively. This study integrates spatial and social network analysis to understand the role of spatial distance in forming criminal collaborations. First, we extract co-offending networks from a police-reported database and present a comprehensive study of the spatial properties of co-offending networks. Then, using community detection approaches, we detect offender groups as denser sub graphs of some co-offending network. Finally, we study the geography of offender groups as an important characteristic of such groups. Recognizing if offender groups are geographically dispersed or geographically concentrated can help law enforcement and intelligence agencies to prioritize their preventative deployments and proactive investigations in combating crime. For the experimental evaluation, we use a real-world crime dataset comprising crime incidents in the time period 2001-2006 in the regions of British Columbia, Canada policed by the RCMP.

Purpose Investigating the day of week and hour of day temporal patterns of crime typically show that (late) nights and weekends are the prime time for criminal activity. Though instructive, mental-health-related calls for service are a significant component of police service to the community that have not been a part of this research. The purpose of this paper is to analyze calls for police service that relate to mental health, using intimate partner/domestic related calls for police service for context. Design/methodology/approach Approximately 20,000 mental health related and 20,000 intimate partner/domestic related calls for police service are analyzed. Intra-week and intra-day temporal patterns are analyzed using circular statistics. Findings Mental-health-related calls for police service have a distinct temporal pattern for both days of the week and hours of the day. Specifically, these calls for police service peak during the middle of the week and in the mid-afternoon. Originality/value This is the first analysis regarding the temporal patterns of police calls for service for mental health-related calls. The results have implications for police resourcing and scheduling, especially in the context of special teams for addressing mental health-related calls for police service.

Suspect investigation as a critical function of policing determines the truth about how a crime occurred, as far as it can be found. Understanding of the environmental elements in the causes of a crime incidence inevitably improves the suspect investigation process. Crime pattern theory concludes that offenders, rather than venture into unknown territories, frequently commit opportunistic and serial violent crimes by taking advantage of opportunities they encounter in places they are most familiar with as part of their activity space. In this paper, we present a suspect investigation method, called SINAS, which learns the activity space of offenders using an extended version of the random walk method based on crime pattern theory, and then recommends the top-K potential suspects for a committed crime. Our experiments on a large real-world crime dataset show that SINAS outperforms the baseline suspect investigation methods we used for the experimental evaluation.

The Howard Journal of Criminal JusticeVolume 14, Issue 2 p. 11-23 THE SPATIAL PATTERNING OF BURGLARY Paul J. Brantingham, Paul J. BrantinghamSearch for more papers by this authorPatricia L. Brantingham, Patricia L. BrantinghamSearch for more papers by this author Paul J. Brantingham, Paul J. BrantinghamSearch for more papers by this authorPatricia L. Brantingham, Patricia L. BrantinghamSearch for more papers by this author First published: July 1975 https://doi.org/10.1111/j.1468-2311.1975.tb00297.xCitations: 52AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume14, Issue2July 1975Pages 11-23 RelatedInformation

A range of spatial analyses are used in the field of crime mapping, such as kernel density estimation, Ripley's K-function, and spatial autocorrelation, but there is limited use of Voronoi diagrams (VDs). The goal of this article is to contribute to the spatial analysis of crime through the use of VDs. We use four years of commercial robbery data from Campinas, Brazil, and employ several VD techniques: (1) We analyze crime concentrations through the properties of VDsarea and number of verticesand coverage curve; (2) we introduce a new crime geovisualization with VD in three dimensions; and (3) we apply a network VD technique to crime analysis. The results demonstrate associations between these VD techniques and the ability of the researcher to recognize crime patterns associated with crime concentration, crime along pathways, and the highly regularized distribution of crime in limited areas spatially.

From Brantingham, P.L., and Brantingham, P.J. (1993). Environment, routine and situation: Toward a pattern theory of crime. Advances in Criminological ἀ eory, 5, 259-294.As a discipline, criminology tries to understand and explain crime and criminal behavior. This poses fascinating and long-standing questions: Why do some people commit crimes while others do not? Why are some people frequently victimized while others suffer only rarely? Why do some places experience a lot of crime while other places experience almost none? The answers to these questions seem, to us, to reside in understanding the patterns formed by the rich complexities of criminal events. Each criminal event is an opportune cross-product of law, offender motivation, and target characteristic arrayed on an environmental backcloth at a particular point in space-time. Each element in the criminal event has some historical trajectory shaped by past experience and future intention, by the routine activities and16.1 Introduction 365 16.2 Pattern Theory 37116.2.1 Event Process 373 16.2.2 Template/Activity Backcloth 374 16.2.3 Readiness/Willingness 37916.3 Application of Pattern Theory 382 16.3.1 Pilfering of Office Supplies 383 16.3.2 Household Burglary 384 16.3.3 Serial Rape 38716.4 Conclusions 388rhythms of life, and by the constraints of the environment.* Patterns within these complexities, considered over many criminal events, should point us toward understandings of crime as a whole.