Prospective Hot-Spotting
The Future of Crime Mapping
Datos Bibliográficos
| ID | 8401226 |
|---|---|
| Autores | K J Bowers, Kate Bowers (0000-0002-0965-492X, autor de correspondencia) |
| Año | 2004 |
| Volumen | 44 |
| Número | 5 |
| Páginas | 641-658 |
| Fecha de publicación | 2004-05-07 |
| Peer Reviewed | Sí |
| Open Access | No |
| Tipo | ARTICLE |
| Revista | The British Journal of Criminology (JOURNAL) |
| Identificadores de la revista | ISSN: 0007-0955 • E-ISSN: 1464-3529 |
| Editorial | Oxford University Press (PUBLISHER • GB) |
| DOI | 10.1093/bjc/azh036 |
| OpenAlex | W1987685062 |
| Idioma | EN |
| Citas recibidas | 60 |
| Referencias 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
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| Obras citantes distintas | 60 |
|---|---|
| Citas por año | 3,16 |
| Intervalo de citas | 2007 - 2026 (20) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 56 |