IDEAS home Printed from https://ideas.repec.org/a/eee/jcjust/v46y2016icp52-63.html
   My bibliography  Save this article

Exploring the impact of ambient population measures on London crime hotspots

Author

Listed:
  • Malleson, Nick
  • Andresen, Martin A.

Abstract

Crime analysts need accurate population-at-risk measures to quantify crime rates. This research evaluates five measures to find the most suitable ambient population-at-risk estimate for ‘theft from the person’ crimes.

Suggested Citation

  • Malleson, Nick & Andresen, Martin A., 2016. "Exploring the impact of ambient population measures on London crime hotspots," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 52-63.
  • Handle: RePEc:eee:jcjust:v:46:y:2016:i:c:p:52-63
    DOI: 10.1016/j.jcrimjus.2016.03.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047235216300198
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jcrimjus.2016.03.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David Martin & Samantha Cockings & Samuel Leung, 2015. "Developing a Flexible Framework for Spatiotemporal Population Modeling," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(4), pages 754-772, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hipp, John R. & Kim, Young-An, 2019. "Explaining the temporal and spatial dimensions of robbery: Differences across measures of the physical and social environment," Journal of Criminal Justice, Elsevier, vol. 60(C), pages 1-12.
    2. Zhang, Yanji & Wang, Jiejing & Kan, Changcheng, 2022. "Temporal variation in activity-space-based segregation: A case study of Beijing using location-based service data," Journal of Transport Geography, Elsevier, vol. 98(C).
    3. Quick, Matthew & Li, Guangquan & Brunton-Smith, Ian, 2018. "Crime-general and crime-specific spatial patterns: A multivariate spatial analysis of four crime types at the small-area scale," Journal of Criminal Justice, Elsevier, vol. 58(C), pages 22-32.
    4. Chong Xu & Zhenhao He & Guangwen Song & Debao Chen, 2024. "Unraveling the influence of income-based ambient population heterogeneity on theft spatial patterns: insights from mobile phone big data analysis," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    5. Minxuan Lan & Lin Liu & Andres Hernandez & Weiyi Liu & Hanlin Zhou & Zengli Wang, 2019. "The Spillover Effect of Geotagged Tweets as a Measure of Ambient Population for Theft Crime," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    6. Álvaro Briz‐Redón & Jorge Mateu & Francisco Montes, 2022. "Identifying crime generators and spatially overlapping high‐risk areas through a nonlinear model: A comparison between three cities of the Valencian region (Spain)," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(1), pages 97-120, February.
    7. Guangwen Song & Jiaqi Li & Chunxia Zhang & Jie Gu, 2022. "Residents’ Location-Based Fear of Theft and Their Impact Factors in Guangzhou, China," IJERPH, MDPI, vol. 20(1), pages 1-13, December.
    8. Zhanjun He & Rongqi Lai & Zhipeng Wang & Huimin Liu & Min Deng, 2022. "Comparative Study of Approaches for Detecting Crime Hotspots with Considering Concentration and Shape Characteristics," IJERPH, MDPI, vol. 19(21), pages 1-16, November.
    9. Felson, Marcus & Xu, Yanqing & Jiang, Shanhe, 2022. "Property crime specialization in Detroit, Michigan," Journal of Criminal Justice, Elsevier, vol. 82(C).
    10. Daqian Liu & Wei Song & Chunliang Xiu & Jun Xu, 2021. "Understanding the Spatiotemporal Pattern of Crimes in Changchun, China: A Bayesian Modeling Approach," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    11. Chris Brunsdon & Jonathan Corcoran, 2022. "Unveiling the relationship between land use types and the temporal signals of crime: An empirical decomposition approach," Environment and Planning B, , vol. 49(3), pages 847-865, March.
    12. Paul Emile Tchinda & Seung-Nam Kim, 2020. "The Paradox of “Eyes on the Street”: Pedestrian Density and Fear of Crime in Yaoundé, Cameroon," Sustainability, MDPI, vol. 12(13), pages 1-16, June.
    13. Langton, Samuel & Dixon, Anthony & Farrell, Graham, 2021. "Small area variation in crime effects of COVID-19 policies in England and Wales," Journal of Criminal Justice, Elsevier, vol. 75(C).
    14. Langton, Samuel & Dixon, Anthony & Farrell, Graham, 2021. "Small area variation in crime effects of COVID-19 policies in England and Wales," SocArXiv cw6a4, Center for Open Science.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rains, Tim & Longley, Paul, 2021. "The provenance of loyalty card data for urban and retail analytics," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jcjust:v:46:y:2016:i:c:p:52-63. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jcrimjus .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.