Prospective Hot-Spotting
The Future of Crime Mapping
Dados Bibliográficos
| ID | 8401226 |
|---|---|
| Autores | K J Bowers, Kate Bowers (0000-0002-0965-492X, autor correspondente) |
| Ano | 2004 |
| Volume | 44 |
| Fascículo | 5 |
| Páginas | 641-658 |
| Data de publicação | 2004-05-07 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | The British Journal of Criminology (JOURNAL) |
| Identificadores do periódico | ISSN: 0007-0955 • E-ISSN: 1464-3529 |
| Editora | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/bjc/azh036 |
| OpenAlex | W1987685062 |
| Idioma | EN |
| Citações recebidas | 60 |
| Referências citadas | 1 |
Existing methods of predicting and mapping the future locations of crime are intrinsically retrospective. This paper explores the development of a mapping procedure that seeks to produce Prospective' hot-spot maps. Recent research conducted by the authors demonstrates that the risk of burglary is communicable, with properties within 400 metres of a burgled household being at a significantly elevated risk of victimization for up to two months after an initial event. We discuss how, using this knowledge, recorded crime data can be analysed to generate an ever-changing prospective risk surface. One of the central elements of this paper examines the issue of how such a risk surface could be evaluated to determine its effectiveness and utility in comparison to existing methods. New methods of map evaluation are proposed, such as the production of search efficiency rates and area-to-perimeter ratios; standardized metrics that can be derived for maps produced using different techniques, thereby allowing meaningful comparisons to be made and techniques contrasted. The results suggest that the predictive mapping technique proposed here has considerable advantages over more traditional methods and might prove particularly useful in the shift-by-shift deployment of police personnel.
Business · Data science · Event (particle physics) · Risk analysis (engineering) · Software deployment · Spotting · Artificial Intelligence · Computer Science · Crime Patterns and Interventions · Data-Driven Disease Surveillance · Geographic Information Systems Studies
Deterrence or prevention? The challenges of algorithmic crime prediction in urban spaces
Trends in police research
Spatial and Temporal Analyses of Terrorist Incidents in Iraq, 2004–2006
A Geographic Information Systems (GIS) Analysis of Spatiotemporal Patterns of Terrorist Incidents in Iraq 2004–2009
Criminal Futures
Self-Exciting Point Process Modeling of Crime
Risk Terrain Modeling
Comparative Study of Approaches for Detecting Crime Hotspots with Considering Concentration and Shape Characteristics
Graph Representation Learning for Street-Level Crime Prediction
Considerations for Developing Predictive Spatial Models of Crime and New Methods for Measuring Their Accuracy
Construction, Detection, and Interpretation of Crime Patterns over Space and Time
Ambient Population and Larceny-Theft
An Adaptive Spatial Resolution Method Based on the ST-ResNet Model for Hourly Property Crime Prediction
All Burglaries Are Not the Same
Urban Crime Risk Prediction Using Point of Interest Data
When Do Offenders Commit Crime? An Analysis of Temporal Consistency in Individual Offending Patterns
An Offenders-Offenses Shared Component Spatial Model for Identifying Shared and Specific Hotspots of Offenders and Offenses
Mapping the Risk Terrain for Crime Using Machine Learning
A deep multi-scale neural networks for crime hotspot mapping prediction
A data-driven agent-based simulation to predict crime patterns in an urban environment
Graph deep learning model for network-based predictive hotspot mapping of sparse spatio-temporal events
Data in Policing
Filaments of crime
Homicide concentration and retaliatory homicide near repeats
Predictive policing
Understanding the Multi-level Interactions Between Physical Environment and Neighborhood Characteristics in Assessing Vulnerability to Crime in Micro-places
‘Top 10’ policing as an alternative place-based strategy
Trends in Police Research
The Contribution of Open Source Software in Identifying Environmental Crimes Caused by Illicit Waste Management in Urban Areas
UK open source crime data
Repeat and near-repeat burglaries and offender involvement in a large Chinese city
How Swiftly Does Re-Victimisation Occur? Evidence from Surveys of Victims
Machine learning for policing
Algorithmic prediction in policing
Patterns in the supply and demand of urban policing at the street segment level
Spatiotemporal crime analysis in U.S. law enforcement agencies
Understanding the spatial distribution of crime in hot crime areas
Exploring Violent and Property Crime Geographically
Keeping Score
Artificial Intelligence, Predictive Policing, and Risk Assessment for Law Enforcement
A multi-faceted approach to analyzing historical police logs
Police use of force data collection issues in Florida
Space–Time Patterns of Risk
The Utility of Hotspot Mapping for Predicting Spatial Patterns of Crime
Promises and Pitfalls of Algorithm Use by State Authorities
Natural outbreaks and bioterrorism
Environmental Criminology
Environmental Criminology
Environmental Criminology
Actionable predictions
Predicting cannabis cultivation on national forests using a rational choice framework
Crime in a planned city
The Rise of Evidence-Based Policing
Ripping up the Map
The exacerbating effect of police presence
Adopting the Position of Error
Epistemologies of predictive policing
Predictable Policing
COPtimization and the operational banality of policing's technocratic drive
Event-level prediction of urban crime reveals a signature of enforcement bias in US cities
| Obras citantes distintas | 60 |
|---|---|
| Citações por ano | 3,16 |
| Intervalo de citações | 2007 - 2026 (20) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 56 |