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Estimating local daytime population density from census and payroll data

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  • Geoff Boeing

Abstract

Daytime population density reflects where people commute and spend their waking hours. It carries significant weight as urban planners and engineers site transportation infrastructure and utilities, plan for disaster recovery, and assess urban vitality. Various methods with various drawbacks exist to estimate daytime population density across a metropolitan area, such as using census data, travel diaries, GPS traces, or publicly available payroll data. This study estimates the San Francisco Bay Area's tract-level daytime population density from US Census and LEHD LODES data. Estimated daytime densities are substantially more concentrated than corresponding night-time population densities, reflecting regional land use patterns. We conclude with a discussion of biases, limitations, and implications of this methodology.

Suggested Citation

  • Geoff Boeing, 2018. "Estimating local daytime population density from census and payroll data," Regional Studies, Regional Science, Taylor & Francis Journals, vol. 5(1), pages 179-182, January.
    • Handle: RePEc:taf:rsrsxx:v:5:y:2018:i:1:p:179-182
    DOI: 10.1080/21681376.2018.1455535
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    Cited by:

    1. Geoff Boeing & Yougeng Lu & Clemens Pilgram, 2023. "Local inequities in the relative production of and exposure to vehicular air pollution in Los Angeles," Urban Studies, Urban Studies Journal Limited, vol. 60(12), pages 2351-2368, September.
    2. repec:osf:socarx:qfvry_v1 is not listed on IDEAS
    3. Areum Jo & Sang-Kyeong Lee & Jaecheol Kim, 2020. "Gender Gaps in the Use of Urban Space in Seoul: Analyzing Spatial Patterns of Temporary Populations Using Mobile Phone Data," Sustainability, MDPI, vol. 12(16), pages 1-22, August.
    4. Matthew Hall & John Iceland & Youngmin Yi, 2019. "Racial Separation at Home and Work: Segregation in Residential and Workplace Settings," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 38(5), pages 671-694, October.
    5. Fox, Sean & Wolf, Levi John, 2022. "What makes a place urban?," SocArXiv qfvry, Center for Open Science.
    6. Jack Liddle & Wenhua Jiang & Nick Malleson, 2025. "Leveraging principal component analysis to uncover urban pedestrian dynamics," Journal of Geographical Systems, Springer, vol. 27(3), pages 425-453, July.
    7. repec:osf:socarx:wd92j_v1 is not listed on IDEAS
    8. Radoslaw Panczak & Elin Charles-Edwards & Jonathan Corcoran, 2020. "Estimating temporary populations: a systematic review of the empirical literature," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 6(1), pages 1-10, June.

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