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Exploring the impact of ambient population measures on London crime hotspots

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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