IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i11p1202-d673693.html
   My bibliography  Save this article

Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient

Author

Listed:
  • Shrobona Karkun Sen

    (Geography and Urban Studies Department and Center for Sustainable Communities, Temple University, Philadelphia, PA 19122, USA)

  • Hamil Pearsall

    (Geography and Urban Studies Department and Center for Sustainable Communities, Temple University, Philadelphia, PA 19122, USA)

  • Victor Hugo Gutierrez-Velez

    (Geography and Urban Studies Department and Center for Sustainable Communities, Temple University, Philadelphia, PA 19122, USA)

  • Melissa R. Gilbert

    (Geography and Urban Studies Department and Center for Sustainable Communities, Temple University, Philadelphia, PA 19122, USA)

Abstract

Recent regional research has taken an ‘infrastructure turn’ where scholars have called for examining the transformative ability of different infrastructures in causing systemic inequities beyond the spatial conception of ‘urban and the other’. This research examines the interconnected impact of infrastructure systems on existing spatial inequities through a study in metropolitan Philadelphia, Pennsylvania. This study investigates whether the urban-rural (U-R) gradient concept can enhance understanding of the spatial relationship between socioeconomic indicators and infrastructure systems. Indicators of spatial inequalities were regressed against infrastructure variables and imperviousness, as a proxy for the U-R gradient, using multivariate and spatial regression methods. The models show that imperviousness has a positive correlation with the concentration of racialized minorities and a negative correlation with access to health insurance. The study also shows that the predictive power of multiple infrastructures varies across space and does not adhere to urban boundaries or the U-R gradient. The complex interactions among different infrastructures shape inequities and require further inquiry in urban regions around the world.

Suggested Citation

  • Shrobona Karkun Sen & Hamil Pearsall & Victor Hugo Gutierrez-Velez & Melissa R. Gilbert, 2021. "Measuring Equity through Spatial Variability of Infrastructure Systems across the Urban-Rural Gradient," Land, MDPI, vol. 10(11), pages 1-15, November.
  • Handle: RePEc:gam:jlands:v:10:y:2021:i:11:p:1202-:d:673693
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/11/1202/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/10/11/1202/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Siciliano, Giuseppina & Urban, Frauke & Kim, Sour & Dara Lonn, Pich, 2015. "Hydropower, social priorities and the rural–urban development divide: The case of large dams in Cambodia," Energy Policy, Elsevier, vol. 86(C), pages 273-285.
    2. Michael R. Glass & Jean-Paul D. Addie & Jen Nelles, 2019. "Regional infrastructures, infrastructural regionalism," Regional Studies, Taylor & Francis Journals, vol. 53(12), pages 1651-1656, December.
    3. Morag Torrance, 2009. "Reconceptualizing urban governance through a new paradigm for urban infrastructure networks," Journal of Economic Geography, Oxford University Press, vol. 9(6), pages 805-822, November.
    4. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    Full references (including those not matched with items on IDEAS)

    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. Yanzhao Wang & Jianfei Cao, 2023. "Examining the Effects of Socioeconomic Development on Fine Particulate Matter (PM2.5) in China’s Cities Based on Spatial Autocorrelation Analysis and MGWR Model," IJERPH, MDPI, vol. 20(4), pages 1-23, February.
    2. Wang, Xiaoxi & Zhang, Yaojun & Yu, Danlin & Qi, Jinghan & Li, Shujing, 2022. "Investigating the spatiotemporal pattern of urban vibrancy and its determinants: Spatial big data analyses in Beijing, China," Land Use Policy, Elsevier, vol. 119(C).
    3. Hengyu Gu & Hanchen Yu & Mehak Sachdeva & Ye Liu, 2021. "Analyzing the distribution of researchers in China: An approach using multiscale geographically weighted regression," Growth and Change, Wiley Blackwell, vol. 52(1), pages 443-459, March.
    4. Jin, Peizhen & Mangla, Sachin Kumar & Song, Malin, 2021. "Moving towards a sustainable and innovative city: Internal urban traffic accessibility and high-level innovation based on platform monitoring data," International Journal of Production Economics, Elsevier, vol. 235(C).
    5. Chunfang Zhao & Yingliang Wu & Yunfeng Chen & Guohua Chen, 2023. "Multiscale Effects of Hedonic Attributes on Airbnb Listing Prices Based on MGWR: A Case Study of Beijing, China," Sustainability, MDPI, vol. 15(2), pages 1-21, January.
    6. Li Gao & Mingjing Huang & Wuping Zhang & Lei Qiao & Guofang Wang & Xumeng Zhang, 2021. "Comparative Study on Spatial Digital Mapping Methods of Soil Nutrients Based on Different Geospatial Technologies," Sustainability, MDPI, vol. 13(6), pages 1-19, March.
    7. Kate Gasparro & Ashby Monk, 2020. "Demystifying “localness†of infrastructure assets: Crowdfunders as local intermediaries for global investors," Environment and Planning A, , vol. 52(5), pages 878-897, August.
    8. Moore, David & Webb, Amanda L., 2022. "Evaluating energy burden at the urban scale: A spatial regression approach in Cincinnati, Ohio," Energy Policy, Elsevier, vol. 160(C).
    9. Hosseinzadeh, Aryan & Algomaiah, Majeed & Kluger, Robert & Li, Zhixia, 2021. "Spatial analysis of shared e-scooter trips," Journal of Transport Geography, Elsevier, vol. 92(C).
    10. Yigong Hu & Binbin Lu & Yong Ge & Guanpeng Dong, 2022. "Uncovering spatial heterogeneity in real estate prices via combined hierarchical linear model and geographically weighted regression," Environment and Planning B, , vol. 49(6), pages 1715-1740, July.
    11. Yongxin Liu & Yiting Wang & Yiwen Lin & Xiaoqing Ma & Shifa Guo & Qianru Ouyang & Caige Sun, 2023. "Habitat Quality Assessment and Driving Factors Analysis of Guangdong Province, China," Sustainability, MDPI, vol. 15(15), pages 1-23, July.
    12. Tao Wang & Kai Zhang & Keliang Liu & Keke Ding & Wenwen Qin, 2023. "Spatial Heterogeneity and Scale Effects of Transportation Carbon Emission-Influencing Factors—An Empirical Analysis Based on 286 Cities in China," IJERPH, MDPI, vol. 20(3), pages 1-17, January.
    13. Lu, Haiyan & Zhao, Pengjun & Hu, Haoyu & Zeng, Liangen & Wu, Kai Sheng & Lv, Di, 2022. "Transport infrastructure and urban-rural income disparity: A municipal-level analysis in China," Journal of Transport Geography, Elsevier, vol. 99(C).
    14. Junfeng Wang & Shaoyao Zhang & Wei Deng & Qianli Zhou, 2024. "Metropolitan Expansion and Migrant Population: Correlation Patterns and Influencing Factors in Chengdu, China," Land, MDPI, vol. 13(1), pages 1-20, January.
    15. Wang, Jiaoe & Xiao, Fan & Dobruszkes, Frédéric & Wang, Wei, 2023. "Seasonality of flights in China: Spatial heterogeneity and its determinants," Journal of Air Transport Management, Elsevier, vol. 108(C).
    16. Xin Lao & Hengyu Gu, 2020. "Unveiling various spatial patterns of determinants of hukou transfer intentions in China: A multi‐scale geographically weighted regression approach," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1860-1876, December.
    17. Huxiao Zhu & Xiangjun Ou & Zhen Yang & Yiwen Yang & Hongxin Ren & Le Tang, 2022. "Spatiotemporal Dynamics and Driving Forces of Land Urbanization in the Yangtze River Delta Urban Agglomeration," Land, MDPI, vol. 11(8), pages 1-21, August.
    18. Zhenbao Wang & Jiarui Song & Yuchen Zhang & Shihao Li & Jianlin Jia & Chengcheng Song, 2022. "Spatial Heterogeneity Analysis for Influencing Factors of Outbound Ridership of Subway Stations Considering the Optimal Scale Range of “7D” Built Environments," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    19. Qinglin Jia & Tao Zhang & Long Cheng & Gang Cheng & Minjie Jin, 2022. "The Impact of the Neighborhood Built Environment on the Walking Activity of Older Adults: A Multi-Scale Spatial Heterogeneity Analysis," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    20. Jiansheng Qu & Lina Liu & Jingjing Zeng & Tek Narayan Maraseni & Zhiqiang Zhang, 2022. "City-Level Determinants of Household CO 2 Emissions per Person: An Empirical Study Based on a Large Survey in China," Land, MDPI, vol. 11(6), pages 1-14, June.

    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:gam:jlands:v:10:y:2021:i:11:p:1202-:d:673693. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.