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Measuring inequality in community resilience to natural disasters using large-scale mobility data

Author

Listed:
  • Boyeong Hong

    (New York University)

  • Bartosz J. Bonczak

    (New York University)

  • Arpit Gupta

    (New York University)

  • Constantine E. Kontokosta

    (New York University
    New York University)

Abstract

While conceptual definitions provide a foundation for the study of disasters and their impacts, the challenge for researchers and practitioners alike has been to develop objective and rigorous measures of resilience that are generalizable and scalable, taking into account spatiotemporal dynamics in the response and recovery of localized communities. In this paper, we analyze mobility patterns of more than 800,000 anonymized mobile devices in Houston, Texas, representing approximately 35% of the local population, in response to Hurricane Harvey in 2017. Using changes in mobility behavior before, during, and after the disaster, we empirically define community resilience capacity as a function of the magnitude of impact and time-to-recovery. Overall, we find clear socioeconomic and racial disparities in resilience capacity and evacuation patterns. Our work provides new insight into the behavioral response to disasters and provides the basis for data-driven public sector decisions that prioritize the equitable allocation of resources to vulnerable neighborhoods.

Suggested Citation

  • Boyeong Hong & Bartosz J. Bonczak & Arpit Gupta & Constantine E. Kontokosta, 2021. "Measuring inequality in community resilience to natural disasters using large-scale mobility data," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-22160-w
    DOI: 10.1038/s41467-021-22160-w
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    Cited by:

    1. Dai, Peichao & Zhang, Shaoliang & Gong, Yunlong & Zhou, Yuan & Hou, Huping, 2022. "A crowd-sourced valuation of recreational ecosystem services using mobile signal data applied to a restored wetland in China," Ecological Economics, Elsevier, vol. 192(C).
    2. Jiaojiao Liu & Shuai Liu & Xiaolin Xu & Qi Zou, 2022. "Can Digital Transformation Promote the Rapid Recovery of Cities from the COVID-19 Epidemic? An Empirical Analysis from Chinese Cities," IJERPH, MDPI, vol. 19(6), pages 1-14, March.
    3. Peng Chen & Wei Zhai & Xiankui Yang, 2023. "Enhancing resilience and mobility services for vulnerable groups facing extreme weather: lessons learned from Snowstorm Uri in Harris County, Texas," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(2), pages 1573-1594, September.
    4. Anna Camille Svirsko & Tom Logan & Christina Domanowski & Daphne Skipper, 2022. "Developing Robust Facility Reopening Processes Following Natural Disasters," SN Operations Research Forum, Springer, vol. 3(3), pages 1-17, September.
    5. Sean Fox & Felix Agyemang & Laurence Hawker & Jeffrey Neal, 2024. "Integrating social vulnerability into high-resolution global flood risk mapping," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    6. Natalie Coleman & Chenyue Liu & Yiqing Zhao & Ali Mostafavi, 2023. "Lifestyle pattern analysis unveils recovery trajectories of communities impacted by disasters," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    7. Zizhen Xu & Shauhrat S. Chopra, 2023. "Interconnectedness enhances network resilience of multimodal public transportation systems for Safe-to-Fail urban mobility," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    8. Sahar Derakhshan & Leah Blackwood & Margot Habets & Julia F. Effgen & Susan L. Cutter, 2022. "Prisoners of Scale: Downscaling Community Resilience Measurements for Enhanced Use," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    9. Xinghua Feng & Chunliang Xiu & Jianxin Li & Yexi Zhong, 2021. "Measuring the Evolution of Urban Resilience Based on the Exposure–Connectedness–Potential (ECP) Approach: A Case Study of Shenyang City, China," Land, MDPI, vol. 10(12), pages 1-22, November.
    10. Dong, Shangjia & Gao, Xinyu & Mostafavi, Ali & Gao, Jianxi & Gangwal, Utkarsh, 2023. "Characterizing resilience of flood-disrupted dynamic transportation network through the lens of link reliability and stability," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    11. Cheng-Chun Lee & Mikel Maron & Ali Mostafavi, 2022. "Community-scale big data reveals disparate impacts of the Texas winter storm of 2021 and its managed power outage," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    12. Songhua Hu & Kailai Wang & Lingyao Li & Yingrui Zhao & Zhenbing He & Yunpeng & Zhang, 2023. "Modeling Link-level Road Traffic Resilience to Extreme Weather Events Using Crowdsourced Data," Papers 2310.14380, arXiv.org.

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