Rationalizing police patrol beats using Voronoi Tessellations (original) (raw)

Voronoi Diagrams and Spatial Analysis of Crime

The Professional Geographer, 2017

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 VDs-area and number of vertices-and 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.

Improving the Creation of Hot Spot Policing Patrol Routes: Comparing Cognitive Heuristic Performance to an Automated Spatial Computation Approach

2021

Hot spot policing involves the deployment of police patrols to places where high levels of crime have previously concentrated. The creation of patrol routes in these hot spots is mainly a manual process that involves using the results from an analysis of spatial patterns of crime to identify the areas and draw the routes that police officers are required to patrol. In this article we introduce a computational approach for automating the creation of hot spot policing patrol routes. The computational techniques we introduce created patrol routes that covered areas of higher levels of crime than an equivalent manual approach for creating hot spot policing patrol routes, and were more efficient in how they covered crime hot spots. Although the evidence on hot spot policing interventions shows they are effective in decreasing crime, the findings from the current research suggest that the impact of these interventions can potentially be greater when using the computational approaches that...

Developing Police Patrol Strategies Based on the Urban Street Network

2019

In urban areas, crime and disorder have been long-lasting problems that spoil the economic and emotional well-being of residents. A significant way to deter crime, and maintain public safety is through police patrolling. So far, the deployment of police forces in patrolling has relied mainly on expert knowledge, and is usually based on two-dimensional spatial units, giving insufficient consideration to the underlying urban structure and collaboration among patrol officers. This approach has led to impractical and inefficient police patrol strategies, as well as a workload imbalance among officers. Therefore, it is of essential importance to devise advanced police patrol strategies that incorporate urban structure, the collaboration of the patrol officers, and a workload balance. This study aims to develop police patrol strategies that would make intelligent use of the street network layout in urban areas. The street network is a key component in urban structure and is the domain in ...

Designing efficient and balanced police patrol districts on an urban street network

International Journal of Geographical Information Science, 2018

In police planning, a territory is often divided into several patrol districts with balanced workloads, in order to repress crime and provide better police service. Conventionally, in this districting problem, there is insufficient consideration of the impacts of street networks. In this study, we propose a street-network police districting problem (SNPDP) that explicitly uses streets as basic underlying units. This model defines the workload as a combination of different attributes and seeks an efficient and balanced design of districts. We also develop an efficient heuristic to generate high-quality districting plans in an acceptable time. The capability of the algorithm is demonstrated in comparison to an exact linear programming solver on simulated datasets. The SNPDP model is successfully implemented and tested in a case study in London, and the generated police districts have different characteristics that are consistent with the crime risk and land use distribution. Besides, we demonstrate that SNPDP is superior to an aggregation grid-based model regarding the solution quality. This model has the potential to generate streetbased districts with balanced workloads for other districting problems, such as school districting and health care districting.

A computational model for simulating spatial aspects of crime in urban environments

Systems, Man and …

In this paper, we present a novel approach to computational modeling of social systems. By combining the abstract state machine (ASM) formalism with the multi-agent modeling paradigm, we obtain a formal semantic framework for modeling and integration of established theories of crime analysis and prediction. We focus here on spatial and temporal aspects of crime in urban areas. Our work contributes to a new multidisciplinary research effort broadly classified as Computational Criminology.

Integrating GIS and Maximal Covering Models to Determine Optimal Police Patrol Areas

This chapter presents a new method for determining the most efficient spatial distribution of police patrols in a metropolitan region, termed the police patrol area covering (PPAC) model. This method employs inputs from geographic information systems (GIS) data layers, analyzes that data through an optimal covering model formulation, and provides alternative

Visualization and spatial analysis of police open data as a part of community policing in the ci

Different types of spatial analyses and visualizations can be used in the police practice for investigation, crime prediction, and planning of police forces. The public availability of crime data is one of the often discussed issues for the police, general public and academia. The efforts to open police data are rooted in the philosophy of the so-called 'community policing'. In this article, we demonstrate the possibilities of spatial analysis and cartographic visualization of open crime data. We provide two use cases based on the data gathered by the municipal police in Pardubice, Czech Republic. We investigate the impact of gambling sites on crime offence intensity and found that gambling sites considerably influence their surroundings within 100 m. The other use case is focused on traffic offences caused by cyclists. We extracted hot spots of these offences and tried to identify their causation, since the police should not only carry out repressive measures, but also strive to eliminate the causes (e.g. add cycle lanes, bike paths, underpasses or overpasses). Different types of cartographic visualization have been designed and discussed for both use cases. The advantages, limitations and future development of the described concepts are commented on in the conclusion.

Modeling Criminal Activity in Urban Landscapes

Mathematical Methods in Counterterrorism, 2009

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework also provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

The spatio-temporal modeling for criminal incidents

2012

Abstract Law enforcement agencies monitor criminal incidents. With additional geographic and demographic data, law enforcement analysts look for spatio-temporal patterns in these incidents in order to predict future criminal activity. When done correctly these predictions can inform actions that can improve security and reduce the impact of crime. Effective prediction requires the development of models that can find and incorporate the important associative and causative variables available in the data.

A Spatial Approach to Surveying Crime‐problematic Areas at the Street Level

Reaching far beyond the realm of geography and its related disciplines, spatial analysis and visualization tools now actively support the decision-making processes of law enforcement agencies. Interactive mapping of crime outperforms the previously manual and laborious querying of crime databases. Using burglary and robbery events reported in the urban city of Manchester, England, we illustrate the utility of graphical methods for interactive analysis and visualization of event data. These novel surveillance techniques provide insight into offending characteristics and changes in the offending process in ways that cannot be replicated by traditional crime investigative methods. We present a step-wise methodology for computing the intensity of aggregated crime events which can potentially accelerate law enforcers' decision making processes by mapping concentrations of crime in near real time.