IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v51y2024i1p39-56.html
   My bibliography  Save this article

Spatial model for predictive recovery monitoring based on hazard, built environment, and population features and their spillover effects

Author

Listed:
  • Flavia Ioana Patrascu
  • Ali Mostafavi

Abstract

The ability to proactively monitor the trajectory of post-disaster recovery is valuable for resource allocation prioritization. Existing knowledge, however, lacks models and insights for quantifying and proactively monitoring post-disaster community recovery. This study examines models that could predict population activity recovery at the scale of the census block group (CBG). Population activity recovery is measured by using location-based human mobility visitation patterns to essential points-of-interest (POIs) in the context of the 2017 Hurricane Harvey in Harris County, Texas. The study examined the association between the population activity recovery duration and 32 features split into four categories: (1) physical vulnerability and access, (2) hazard exposure and impact, (3) proactive actions and (4) population features. Several types of spatial regression models were evaluated to determine their ability to capture this relationship. The Spatial Durbin Model was identified as the best fit for assessing direct, spillover, and total effects of features on population activity recovery at the CBG level. The results show the extent of physical vulnerability, measured by road network density, prolongs the duration of population activity recovery by a combination of direct and spillover effects. Also, the extent of access to essential facilities, measured based on the number of POIs, shortens the duration of population activity recovery. Correspondingly, the extent of flooding is not a significant feature in explaining the population recovery duration in CBGs. The results show that better preparedness, measured by extent of POIs visitations prior to hurricane landing, is associated with faster population activity recovery. In terms of population attributes, the total number of people, the percentage of minorities, and the percentage of Black and Asian subpopulations are significant features in the model for predicting the duration of population activity recovery. The study outcome offers data-driven insights for understanding the determinants of population activity recovery and provides a new model tool for predictive recovery monitoring based on evaluating the direct, spillover, and total effects of features. These findings can identify areas with slower or more rapid recovery to inform emergency managers and public officials in ensuring equitable resource allocation prioritization.

Suggested Citation

  • Flavia Ioana Patrascu & Ali Mostafavi, 2024. "Spatial model for predictive recovery monitoring based on hazard, built environment, and population features and their spillover effects," Environment and Planning B, , vol. 51(1), pages 39-56, January.
    • Handle: RePEc:sae:envirb:v:51:y:2024:i:1:p:39-56
    DOI: 10.1177/23998083231167433
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/23998083231167433
    Download Restriction: no
    File URL: https://libkey.io/10.1177/23998083231167433?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Walter Gillis Peacock & Shannon Van Zandt & Yang Zhang & Wesley E. Highfield, 2014. "Inequities in Long-Term Housing Recovery After Disasters," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(4), pages 356-371, October.
    2. Benjamin-Chung, Jade & Abedin, Jaynal & Berger, David & Clark, Ashley & Jimenez, Veronica & Konagaya, Eugene & Tran, Diana & Arnold, Benjamin F & Hubbard, Alan E & Luby, Stephen P & Miguel, Edward & C, 2017. "Spillover effects on health outcomes in low- and middle-income countries: a systematic review," Department of Economics, Working Paper Series qt15f554dd, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    3. Michael Bailey & Rachel Cao & Theresa Kuchler & Johannes Stroebel & Arlene Wong, 2018. "Social Connectedness: Measurement, Determinants, and Effects," Journal of Economic Perspectives, American Economic Association, vol. 32(3), pages 259-280, Summer.
    4. Sven Fischer, 2021. "Post-Disaster Spillovers: Evidence from Iranian Provinces," JRFM, MDPI, vol. 14(5), pages 1-26, April.
    5. Anselin, Luc & Bera, Anil K. & Florax, Raymond & Yoon, Mann J., 1996. "Simple diagnostic tests for spatial dependence," Regional Science and Urban Economics, Elsevier, vol. 26(1), pages 77-104, February.
    6. Steven J. Dundas & David J. Lewis, 2020. "Estimating Option Values and Spillover Damages for Coastal Protection: Evidence from Oregon’s Planning Goal 18," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(3), pages 519-554.
    7. Matthias Ruth & Dana Coelho, 2007. "Understanding and managing the complexity of urban systems under climate change," Climate Policy, Taylor & Francis Journals, vol. 7(4), pages 317-336, July.
    8. Robert B. Olshansky & Laurie A. Johnson, 2014. "The Evolution of the Federal Role in Supporting Community Recovery After U.S. Disasters," Journal of the American Planning Association, Taylor & Francis Journals, vol. 80(4), pages 293-304, October.
    9. Si, Deng-Kui & Li, Xiao-Lin & Xu, XuChuan & Fang, Yi, 2021. "The risk spillover effect of the COVID-19 pandemic on energy sector: Evidence from China," Energy Economics, Elsevier, vol. 102(C).
    10. Benjamin-Chung, Jade & Arnold, Benjamin F & Berger, David & Luby, Stephen P & Miguel, Edward & Colford, John M & Hubbard, Alan E, 2018. "Spillover effects in epidemiology: parameters, study designs and methodological considerations," Department of Economics, Working Paper Series qt1547q2zg, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
    11. Domenica Panzera & Paolo Postiglione, 2022. "The impact of regional inequality on economic growth: a spatial econometric approach," Regional Studies, Taylor & Francis Journals, vol. 56(5), pages 687-702, May.
    12. J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
    13. De la Roca, Jorge & Ellen, Ingrid Gould & O'Regan, Katherine M., 2014. "Race and neighborhoods in the 21st century: What does segregation mean today?," Regional Science and Urban Economics, Elsevier, vol. 47(C), pages 138-151.
    14. Shraddha Praharaj & T. Donna Chen & Faria T. Zahura & Madhur Behl & Jonathan L. Goodall, 2021. "Estimating impacts of recurring flooding on roadway networks: a Norfolk, Virginia case study," 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. 107(3), pages 2363-2387, July.
    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. Xu, Feng & Chi, Guangqing & Zhang, Zhexi & Yang, Jianxin, 2023. "How does quality regional growth affect land resources dependence in China? Evidence based on spatial Durbin panel models," Resources Policy, Elsevier, vol. 81(C).
    2. Chakir, Raja & Lungarska, Anna, 2015. "Agricultural land rents in land use models: a spatial econometric analysis," 150th Seminar, October 22-23, 2015, Edinburgh, Scotland 212641, European Association of Agricultural Economists.
    3. Fuess, Roland & Lerbs, Oliver, 2017. "Do Local Governments Tax Homeowner Communities Differently?," Working Papers on Finance 1714, University of St. Gallen, School of Finance.
    4. James P. LESAGE, 2014. "Software For Bayesian Spatial Model Comparison," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 40, pages 11-24.
    5. Modranka Emilia & Suchecka Jadwiga, 2014. "The Determinants Of Population Health Spatial Disparities," Comparative Economic Research, Sciendo, vol. 17(4), pages 173-185, December.
    6. J. Paul Elhorst & Katarina Zigova, 2011. "Evidence of Competition in Research Activity among Economic Department using Spatial Econometric Techniques," Working Paper Series of the Department of Economics, University of Konstanz 2011-04, Department of Economics, University of Konstanz.
    7. Todd Landman & T. Huw Edwards & Tulio Antonio-Cravo & David Kernohan, 2011. "Human Rights: The Effect of Neighbouring Countries," Discussion Paper Series 2011_01, Department of Economics, Loughborough University, revised Sep 2011.
    8. Syarifuddin, Ferry, 2020. "The Dynamics of Foreign Direct Investment and Exchange Rates: An Interconnection Approach in ASEAN," MPRA Paper 104596, University Library of Munich, Germany.
    9. GLUMAC Brano & HERRERA-GOMEZ Marcos & LICHERON Julien, 2018. "A residential land price index for Luxembourg: Dealing with the spatial dimension," LISER Working Paper Series 2018-07, Luxembourg Institute of Socio-Economic Research (LISER).
    10. Mahyudin Ahmad & Siong Hook Law, 2024. "Financial development, institutions, and economic growth nexus: A spatial econometrics analysis using geographical and institutional proximities," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 2699-2721, July.
    11. Ahmad, Mahyudin & Hall, Stephen G. & Law, Siong Hook & Nayan, Sabri, 2023. "The spillover effects of financial development and institutions on economic growth in emerging economies: new insights from spatial Durbin approach," MPRA Paper 118966, University Library of Munich, Germany.
    12. Nichols, Mark W. & Tosun, Mehmet Serkan, 2017. "The impact of legalized casino gambling on crime," Regional Science and Urban Economics, Elsevier, vol. 66(C), pages 1-15.
    13. Tsusaka, Takuji W. & Kajisa, Kei & Pede, Valerien O. & Aoyagi, Keitaro, 2015. "Neighborhood effects and social behavior: The case of irrigated and rainfed farmers in Bohol, the Philippines," Journal of Economic Behavior & Organization, Elsevier, vol. 118(C), pages 227-246.
    14. Chamberlin, Jordan, 2013. "Infrastructure, services, and smallholder income growth: evidence from Kenyan panel data," 2013 Fourth International Conference, September 22-25, 2013, Hammamet, Tunisia 161269, African Association of Agricultural Economists (AAAE).
    15. Coro Chasco & Maricruz Lacalle-Calderon & Javier Alfonso-Gil, 2021. "Spatial Diffusion of Civil Liberty," Revista Economía, Fondo Editorial - Pontificia Universidad Católica del Perú, vol. 44(87), pages 146-169.
    16. Kai Li & Zhili Ma & Jinjin Liu, 2019. "A New Trend in the Space–Time Distribution of Cultivated Land Occupation for Construction in China and the Impact of Population Urbanization," Sustainability, MDPI, vol. 11(18), pages 1-23, September.
    17. Qi, Guanqiu & Shi, Wenming & Lin, Kun-Chin & Yuen, Kum Fai & Xiao, Yi, 2020. "Spatial spillover effects of logistics infrastructure on regional development: Evidence from China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 96-114.
    18. Ethan Grumstrup & Mark W. Nichols, 2021. "Is video gambling terminal placement and spending in Illinois correlated with neighborhood characteristics?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 67(2), pages 273-298, October.
    19. Gonzalez, Juan Nicolas & Gomez, Juan & Vassallo, Jose Manuel, 2023. "Are low emission zones and on-street parking management effective in reducing parking demand for most polluting vehicles and promoting greener ones?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    20. Eleonora Dávalos & Leonardo Fabio Morales, 2023. "Diffusion of crime control benefits: forced eradication and coca crops in Colombia," Spatial Economic Analysis, Taylor & Francis Journals, vol. 18(3), pages 292-317, July.

    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:sae:envirb:v:51:y:2024:i:1:p:39-56. 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: SAGE Publications (email available below). General contact details of provider: .

    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.