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

Kensuke Molnar-Tanaka and Kuo-Shih Shao

No 355, OECD Development Centre Working Papers from OECD Publishing

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.

Keywords: AI; Artificial intelligence; Big data; disaster cost assessment; disaster response; Indonesia; satellite imagery; Southeast Asia; Sulawesi earthquake (search for similar items in EconPapers)
JEL-codes: O33 O53 Q54 (search for similar items in EconPapers)
Date: 2025-06-27
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Persistent link: https://EconPapers.repec.org/RePEc:oec:devaaa:355-en

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