IDEAS home Printed from https://ideas.repec.org/a/fgv/epgrbe/v77y2023i1a84823.html
   My bibliography  Save this article

Combining Artificial Intelligence and Satellite Images to Forecast Agricultural Losses: Evidence for Brazil

Author

Listed:
  • Batista de Barros, Pedro Henrique
  • Freitas Junior, Adirson Maciel de

Abstract

The agricultural sector is subject to adversities arising from weather events, incidence of pests, fires and market variations, therefore, it is extremely important to adopt rural insurance for an adequate management of agricultural activities. However, the existence of market failures inhibits the development and expansion of this market, especially in Brazil. In this context, the main goal of this article is to propose an innovative methodology that combines machine learning algorithms with optical and radar satellite images for forecasting agricultural losses, thus allowing for the reduction of informational asymmetries in the Brazilian market.

Suggested Citation

  • Batista de Barros, Pedro Henrique & Freitas Junior, Adirson Maciel de, 2023. "Combining Artificial Intelligence and Satellite Images to Forecast Agricultural Losses: Evidence for Brazil," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 77(1), April.
  • Handle: RePEc:fgv:epgrbe:v:77:y:2023:i:1:a:84823
    as

    Download full text from publisher

    File URL: https://periodicos.fgv.br/rbe/article/view/84823
    Download Restriction: no
    ---><---

    More about this item

    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:fgv:epgrbe:v:77:y:2023:i:1:a:84823. 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: Núcleo de Computação da FGV EPGE (email available below). General contact details of provider: https://edirc.repec.org/data/epgvfbr.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.