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Big Earth Data Volume 7, 2023 - Issue 4: Big Earth data for disaster risk reduction
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Original Research Article

Improving risk reduction potential of weather index insurance by spatially downscaling gridded climate data - a machine learning approach

Sarvarbek EltazarovDepartment of Agricultural Markets, Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, GermanyCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-5578-9772View further author information
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Ihtiyor BobojonovDepartment of Agricultural Markets, Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, GermanyORCID Iconhttps://orcid.org/0000-0003-2166-6234View further author information
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Lena KuhnDepartment of Agricultural Markets, Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, GermanyORCID Iconhttps://orcid.org/0000-0002-1453-0040View further author information
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Thomas GlaubenDepartment of Agricultural Markets, Marketing and World Agricultural Trade, Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, GermanyORCID Iconhttps://orcid.org/0000-0003-0640-9387View further author information
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Pages 937-960 | Received 29 Dec 2022, Accepted 24 Mar 2023, Published online: 04 Apr 2023

Citations (2)

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Read on this site (1)

Lei Zou, Fang Chen, Xiao Huang & Bandana Kar. (2023) Big Earth data for disaster risk reduction. Big Earth Data 7:4, pages 931-936.
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Articles from other publishers (1)

Gabriela C. Gesualdo, Marcos R. Benso, Karina S. Sass & Eduardo M. Mendiondo. (2024) Index-based insurance to mitigate current and future extreme events financial losses for water utilities. International Journal of Disaster Risk Reduction 100, pages 104218.
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