IDEAS home Printed from https://ideas.repec.org/p/oec/devaaa/355-en.html
   My bibliography  Save this paper

Using AI to measure disaster damage costs: Methodology and the example of the 2018 Sulawesi earthquake

Author

Listed:
  • Kensuke Molnar-Tanaka
  • Kuo-Shih Shao

Abstract

As disasters grow in frequency and intensity, the opportunities to apply Artificial Intelligence (AI) to disaster risk reduction are becoming increasingly prominent. This paper discusses various AI-based approaches including crowdsourcing, Internet of Things, aerial imagery, videos from unmanned aerial vehicles (UAVs), as well as airborne and terrestrial Light Detection and Ranging (LiDAR). It focuses on the use of AI for disaster damage cost estimation and examines the methodological aspect of measuring disaster costs with AI- and satellite imagery-based analysis, using the specific example of the 2018 Sulawesi earthquake.

Suggested Citation

  • Kensuke Molnar-Tanaka & Kuo-Shih Shao, 2025. "Using AI to measure disaster damage costs: Methodology and the example of the 2018 Sulawesi earthquake," OECD Development Centre Working Papers 355, OECD Publishing.
    • Handle: RePEc:oec:devaaa:355-en
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    AI; Artificial intelligence; Big data; disaster cost assessment; disaster response; Indonesia; satellite imagery; Southeast Asia; Sulawesi earthquake;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • O53 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Asia including Middle East

    Statistics

    Access and download statistics

    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:oec:devaaa:355-en. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/dcoecfr.html .

    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.