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Do high-resolution satellite indices at field level reduce basis risk of satellite-based weather index insurance?

Author

Listed:
  • Wienand Kölle
  • Matthias Buchholz
  • Oliver Musshoff

Abstract

Purpose - Satellite-based weather index insurance has recently been considered in order to reduce the high basis risk of station-based weather index insurance. However, the use of satellite data with a relatively low spatial resolution has not yet made it possible to determine the satellite indices free of disturbing landscape elements such as mountains, forests and lakes. Design/methodology/approach - In this context, the Normalized Difference Vegetation Index (NDVI) was used based on both Moderate Resolution Imaging Spectroradiometer (MODIS) (250 × 250 m) and high-resolution Landsat 5/8 (30 × 30 m) images to investigate the effect of a higher spatial resolution of satellite-based weather index contracts for hedging winter wheat yields. For three farms in north-east Germany, insurance contracts both at field and farm level were designed. Findings - The results indicate that with an increasing spatial resolution of satellite data, the basis risk of satellite-based weather index insurance contracts can be reduced. However, the results also show that the design of NDVI-based insurance contracts at farm level also reduces the basis risk compared to field level. The study shows that higher-resolution satellite data are advantageous, whereas satellite indices at field level do not reduce the basis risk. Originality/value - To the best of the author’s knowledge, the effect of increasing spatial resolution of satellite images for satellite-based weather index insurance is investigated for the first time at the field level compared to the farm level.

Suggested Citation

  • Wienand Kölle & Matthias Buchholz & Oliver Musshoff, 2021. "Do high-resolution satellite indices at field level reduce basis risk of satellite-based weather index insurance?," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 82(4), pages 616-640, August.
  • Handle: RePEc:eme:afrpps:afr-12-2020-0177
    DOI: 10.1108/AFR-12-2020-0177
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    Cited by:

    1. Eltazarov, Sarvarbek, 2023. "The potential of satellite-based data to detect weather extremes and crop yield variation for hedging agricultural weather risks in Central Asia and Mongolia: Three essays," EconStor Theses, ZBW - Leibniz Information Centre for Economics, number 286134, March.

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