IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i15p11639-d1204528.html
   My bibliography  Save this article

Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm

Author

Listed:
  • Zhixia Wu

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China
    College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Xiazhong Zheng

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

  • Yijun Chen

    (College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Shan Huang

    (Municipal Construction Engineering Center of Cuiping District, Yibin 644000, China)

  • Wenli Hu

    (College of Management, Sichuan University of Science & Engineering, Zigong 643000, China)

  • Chenfei Duan

    (College of Hydraulic & Environmental Engineering, China Three Gorges University, Yichang 443002, China)

Abstract

To address the problems of traditional insurance compensation methods for flood losses, such as difficulty in determining losses, poor timeliness, a complicated compensation process and moral hazard, an urban flood index insurance tiered compensation model integrating remote sensing and rainfall multi-source data was proposed. This paper first extracted the area of water bodies using the Normalized Difference Water Index and estimates the urban flood area loss based on the flood loss model of remote sensing pixels. Second, the tiered compensation mechanism triggered by rainfall was determined, and the urban flood index insurance tiered compensation model was constructed using remote sensing and rainfall multi-source data. Finally, the economic losses and flood insurance compensation in urban flood were estimated. The results show that: (1) the geo-spatial distribution of flood-affected areas by remote sensing inversion is consistent with the actual rainfall characteristics of Henan Province, China; (2) based on the flood losses model of remote sensing pixels, the estimated flood losses for Henan Province are CNY 110.20 billion, which is consistent with the official data (accuracy ≥ 90%); and (3) the proposed model has good accuracy (R 2 = 0.98, F = 1379.42, p < 0.05). The flood index insurance compensation in Henan Province is classified as a three-tier payout, with a total compensation of CNY 24,137 million. This paper can provide a new approach to estimate large-scale urban flood losses and the scientific design of flood index insurance products. It can also provide theoretical and technical support to many countries around the world, particularly those with underdeveloped flood insurance systems.

Suggested Citation

  • Zhixia Wu & Xiazhong Zheng & Yijun Chen & Shan Huang & Wenli Hu & Chenfei Duan, 2023. "Urban Flood Loss Assessment and Index Insurance Compensation Estimation by Integrating Remote Sensing and Rainfall Multi-Source Data: A Case Study of the 2021 Henan Rainstorm," Sustainability, MDPI, vol. 15(15), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11639-:d:1204528
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/15/11639/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/15/11639/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kousky, Carolyn & Michel-Kerjan, Erwann O. & Raschky, Paul A., 2018. "Does federal disaster assistance crowd out flood insurance?," Journal of Environmental Economics and Management, Elsevier, vol. 87(C), pages 150-164.
    2. Breckner, Miriam & Englmaier, Florian & Stowasser, Till & Sunde, Uwe, 2016. "Resilience to natural disasters — Insurance penetration, institutions, and disaster types," Economics Letters, Elsevier, vol. 148(C), pages 106-110.
    3. Xue Jin & U. Rashid Sumaila & Kedong Yin, 2020. "Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models," Sustainability, MDPI, vol. 12(18), pages 1-25, September.
    4. Xavier Giné & Robert Townsend & James Vickery, 2008. "Patterns of Rainfall Insurance Participation in Rural India," The World Bank Economic Review, World Bank, vol. 22(3), pages 539-566, October.
    5. David Crichton, 2008. "Role of Insurance in Reducing Flood Risk," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 33(1), pages 117-132, January.
    6. Quirin Schiermeier, 2011. "Increased flood risk linked to global warming," Nature, Nature, vol. 470(7334), pages 316-316, February.
    7. Yasuhide Okuyama & Joost R. Santos, 2014. "Disaster Impact And Input--Output Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 1-12, March.
    8. Craig E. Landry & Mohammad R. Jahan‐Parvar, 2011. "Flood Insurance Coverage in the Coastal Zone," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 78(2), pages 361-388, June.
    9. Shawn Cole & Daniel Stein & Jeremy Tobacman, 2014. "Dynamics of Demand for Index Insurance: Evidence from a Long-Run Field Experiment," American Economic Review, American Economic Association, vol. 104(5), pages 284-290, May.
    10. Craig E. Landry & Dylan Turner & Daniel Petrolia, 2021. "Flood Insurance Market Penetration and Expectations of Disaster Assistance," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 79(2), pages 357-386, June.
    11. Boudreault, Mathieu & Ojeda, Angelica, 2022. "Ratemaking territories and adverse selection for flood insurance," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 349-360.
    12. Donatella Porrini & Reimund Schwarze, 2014. "Insurance models and European climate change policies: an assessment," European Journal of Law and Economics, Springer, vol. 38(1), pages 7-28, August.
    13. Carolyn Kousky & Erwann Michel-Kerjan, 2017. "Examining Flood Insurance Claims in the United States: Six Key Findings," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 84(3), pages 819-850, September.
    14. Barry J. Barnett & Olivier Mahul, 2007. "Weather Index Insurance for Agriculture and Rural Areas in Lower-Income Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(5), pages 1241-1247.
    15. Tse‐Ling Teh & Christopher Woolnough, 2019. "A Better Trigger: Indices for Insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 86(4), pages 861-885, December.
    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. Ayako Matsuda & Takashi Kurosaki, 2017. "Temperature and Rainfall Index Insurance in India," OSIPP Discussion Paper 17E002, Osaka School of International Public Policy, Osaka University.
    2. Michler, Jeffrey & Shively, Gerald, 2016. "Agricultural Production, Weather Variability, and Technical Change: 40 Years of Evidence from Indi," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236342, Agricultural and Applied Economics Association.
    3. Chloe H. Lucas & Kate I. Booth & Carolina Garcia, 2021. "Insuring homes against extreme weather events: a systematic review of the research," Climatic Change, Springer, vol. 165(3), pages 1-21, April.
    4. Veronika Bertram-Huemmer & Kati Kraehnert, 2018. "Does Index Insurance Help Households Recover from Disaster? Evidence from IBLI Mongolia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 145-171.
    5. Stoeffler, Quentin & Opuz, Gülce, 2022. "Price, information and product quality: Explaining index insurance demand in Burkina Faso," Food Policy, Elsevier, vol. 108(C).
    6. Martin Achtnicht & Daniel Osberghaus, 2019. "The Demand for Index‐Based Flood Insurance in a High‐Income Country," German Economic Review, Verein für Socialpolitik, vol. 20(2), pages 217-242, May.
    7. Hill, Ruth Vargas & Kumar, Neha & Magnan, Nicholas & Makhija, Simrin & de Nicola, Francesca & Spielman, David J. & Ward, Patrick S., 2019. "Ex ante and ex post effects of hybrid index insurance in Bangladesh," Journal of Development Economics, Elsevier, vol. 136(C), pages 1-17.
    8. Wong, Ho Lun & Wei, Xiangdong & Kahsay, Haftom Bayray & Gebreegziabher, Zenebe & Gardebroek, Cornelis & Osgood, Daniel E. & Diro, Rahel, 2020. "Effects of input vouchers and rainfall insurance on agricultural production and household welfare: Experimental evidence from northern Ethiopia," World Development, Elsevier, vol. 135(C).
    9. Michael King & Anuj Pratab Singh, 2018. "Understanding farmers' valuation of agricultural insurance: Evidence from Vietnam," WIDER Working Paper Series wp-2018-93, World Institute for Development Economic Research (UNU-WIDER).
    10. Jeffrey D. Michler & Frederi G. Viens & Gerald E. Shively, 2021. "Risk, Agricultural Production, and Weather Index Insurance in Village India," Papers 2103.11047, arXiv.org.
    11. Nathaniel Jensen & Christopher Barrett, 2017. "Agricultural Index Insurance for Development," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 39(2), pages 199-219.
    12. Mogge, Lukas, 2023. "A District-Level Analysis of the Effect of Risk Exposure on the Demand for Index Insurance in Mongolia," Ruhr Economic Papers 1018, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    13. Anuj Singh & Michael King, 2018. "Understanding farmers’ valuation of agricultural insurance: Evidence from Vietnam," WIDER Working Paper Series 93, World Institute for Development Economic Research (UNU-WIDER).
    14. Peter John Robinson & W.J.W. Botzen & F. Zhou, 2019. "An experimental study of charity hazard: The effect of risky and ambiguous government compensation on flood insurance demand," Working Papers 19-19, Utrecht School of Economics.
    15. Renuka Sane & Susan Thomas, 2020. "From Participation To Repurchase: Low Income Households And Micro‐insurance," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 87(3), pages 783-814, September.
    16. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 265675, Collaborative Masters Program in Agricultural and Applied Economics.
    17. Singh, Nirvikar, 2018. "Financial Inclusion: Concepts, Issues and Policies for India," MPRA Paper 91047, University Library of Munich, Germany.
    18. Fabio Gaetano Santeramo, 2018. "Imperfect information and participation in insurance markets: evidence from Italy," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 78(2), pages 183-194, February.
    19. Quentin Stoeffler & Michael Carter & Catherine Guirkinger & Wouter Gelade, 2022. "The Spillover Impact of Index Insurance on Agricultural Investment by Cotton Farmers in Burkina Faso," The World Bank Economic Review, World Bank, vol. 36(1), pages 114-140.
    20. Takahashi, Kazushi & Noritomo, Yuma & Ikegami, Munenobu & Jensen, Nathaniel D., 2020. "Understanding pastoralists’ dynamic insurance uptake decisions: Evidence from four-year panel data in Ethiopia," Food Policy, Elsevier, vol. 95(C).

    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:jsusta:v:15:y:2023:i:15:p:11639-:d:1204528. 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.