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The Relationship between Neighborhood Characteristics and Homicide in Karachi, Pakistan

Author

Listed:
  • Salma Hamza

    (Department of Earth and Environmental Sciences, Bahria University Karachi Campus, Karachi 75300, Pakistan)

  • Imran Khan

    (Department of Geography, University of Karachi, Karachi 75300, Pakistan)

  • Linlin Lu

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Hua Liu

    (Department of Political Science and Geography, Old Dominion University, Norfolk, VA 23529, USA)

  • Farkhunda Burke

    (Department of Geography, University of Karachi, Karachi 75300, Pakistan)

  • Syed Nawaz-ul-Huda

    (Dawn GIS, Geospatial Statistical Research & Analysis Division, Karachi 75300, Pakistan)

  • Muhammad Fahad Baqa

    (Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China)

  • Aqil Tariq

    (State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China)

Abstract

The geographical concentration of criminal violence is closely associated with the social, demographic, and economic structural characteristics of neighborhoods. However, few studies have investigated homicide patterns and their relationships with neighborhoods in South Asian cities. In this study, the spatial and temporal patterns of homicide incidences in Karachi from 2009 to 2018 were analyzed using the local indicators of spatial association (LISA) method. Generalized linear modeling (GLM) and geographically weighted Poisson regression (GWPR) methods were implemented to examine the relationship between influential factors and the number of homicides during the 2009–2018 period. The results demonstrate that the homicide hotspot or clustered areas with high homicide counts expanded from 2009 to 2013 and decreased from 2013 to 2018. The number of homicides in the 2017–2018 period had a positive relationship with the percentage of the population speaking Balochi. The unplanned areas with low-density residential land use were associated with low homicide counts, and the areas patrolled by police forces had a significant negative relationship with the occurrence of homicide. The GWPR models effectively characterized the varying relationships between homicide and explanatory variables across the study area. The spatio-temporal analysis methods can be adapted to explore violent crime in other cities with a similar social context.

Suggested Citation

  • Salma Hamza & Imran Khan & Linlin Lu & Hua Liu & Farkhunda Burke & Syed Nawaz-ul-Huda & Muhammad Fahad Baqa & Aqil Tariq, 2021. "The Relationship between Neighborhood Characteristics and Homicide in Karachi, Pakistan," Sustainability, MDPI, vol. 13(10), pages 1-14, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5520-:d:555106
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    References listed on IDEAS

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    Cited by:

    1. Muhammad Fahad Baqa & Fang Chen & Linlin Lu & Salman Qureshi & Aqil Tariq & Siyuan Wang & Linhai Jing & Salma Hamza & Qingting Li, 2021. "Monitoring and Modeling the Patterns and Trends of Urban Growth Using Urban Sprawl Matrix and CA-Markov Model: A Case Study of Karachi, Pakistan," Land, MDPI, vol. 10(7), pages 1-17, July.
    2. Muhammad Majeed & Aqil Tariq & Muhammad Mushahid Anwar & Arshad Mahmood Khan & Fahim Arshad & Faisal Mumtaz & Muhammad Farhan & Lili Zhang & Aroosa Zafar & Marjan Aziz & Sanaullah Abbasi & Ghani Rahma, 2021. "Monitoring of Land Use–Land Cover Change and Potential Causal Factors of Climate Change in Jhelum District, Punjab, Pakistan, through GIS and Multi-Temporal Satellite Data," Land, MDPI, vol. 10(10), pages 1-17, September.
    3. Umer Khalil & Umar Azam & Bilal Aslam & Israr Ullah & Aqil Tariq & Qingting Li & Linlin Lu, 2022. "Developing a Spatiotemporal Model to Forecast Land Surface Temperature: A Way Forward for Better Town Planning," Sustainability, MDPI, vol. 14(19), pages 1-21, September.

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