Articles | Volume 17, issue 12
https://doi.org/10.5194/essd-17-6669-2025
https://doi.org/10.5194/essd-17-6669-2025
Data description paper
 | 
01 Dec 2025
Data description paper |  | 01 Dec 2025

Global spatially-distributed sectoral GDP map for disaster risk analysis

Takeshi Shoji, Kiyoharu Kajiyama, Dai Yamazaki, Yuki Kita, and Megumi Watanabe

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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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Cited articles

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Chen, J., Gao, M., Cheng, S., Hou, W., Song, M., Liu, X., and Liu, Y.: Global 1 km × 1 km gridded revised real gross domestic product and electricity consumption during 1992–2019 based on calibrated nighttime light data, Scientific Data, 9, https://doi.org/10.1038/s41597-022-01322-5, 2022. 
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De Moel, H., Van Vliet, M., and Aerts, J. C. J. H.: Evaluating the effect of flood damage-reducing measures: a case study of the unembanked area of Rotterdam, the Netherlands, Regional Environmental Change, 14, 895–908, 2014. 
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This study addressed the essential need for detailed spatial economic data to accurately assess global economic losses from natural disasters by developing high-resolution global maps of sector-specific (Service, Industry, and Agriculture) Gross Domestic Product (GDP) for 2010, 2015, and 2020. The new maps showed improved accuracy in reflecting local economies, revealing that sectoral GDP distribution differs by country and affects disaster impact estimates.
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