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Agricultural Big Data Architectures in the Context of Climate Change: A Systematic Literature Review

Author

Listed:
  • Ania Cravero

    (Department of Computer Science and Informatics, Centre of Excellence for Modelling and Scientific Computing, Universidad de La Frontera, Temuco 4811230, Chile)

  • Ana Bustamante

    (Department of Computer Science and Informatics, Centre of Excellence for Modelling and Scientific Computing, Universidad de La Frontera, Temuco 4811230, Chile)

  • Marlene Negrier

    (Department of Computer Science and Informatics, Centre of Excellence for Modelling and Scientific Computing, Universidad de La Frontera, Temuco 4811230, Chile)

  • Patricio Galeas

    (Department of Computer Science and Informatics, Centre of Excellence for Modelling and Scientific Computing, Universidad de La Frontera, Temuco 4811230, Chile)

Abstract

Climate change is currently one of agriculture’s main problems in achieving sustainability. It causes drought, increased rainfall, and increased diseases, causing a decrease in food production. In order to combat these problems, Agricultural Big Data contributes with tools that improve the understanding of complex, multivariate, and unpredictable agricultural ecosystems through the collection, storage, processing, and analysis of vast amounts of data from diverse heterogeneous sources. This research aims to discuss the advancement of technologies used in Agricultural Big Data architectures in the context of climate change. The study aims to highlight the tools used to process, analyze, and visualize the data, to discuss the use of the architectures in crop, water, climate, and soil management, and especially to analyze the context, whether it is in Resilience Mitigation or Adaptation. The PRISMA protocol guided the study, finding 33 relevant papers. However, despite advances in this line of research, few papers were found that mention architecture components, in addition to a lack of standards and the use of reference architectures that allow the proper development of Agricultural Big Data in the context of climate change.

Suggested Citation

  • Ania Cravero & Ana Bustamante & Marlene Negrier & Patricio Galeas, 2022. "Agricultural Big Data Architectures in the Context of Climate Change: A Systematic Literature Review," Sustainability, MDPI, vol. 14(13), pages 1-26, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:7855-:d:849448
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    References listed on IDEAS

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    1. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
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    1. Huaizhi Tang & Jiacheng Niu & Zibing Niu & Qi Liu & Yuanfang Huang & Wenju Yun & Chongyang Shen & Zejun Huo, 2023. "System Cognition and Analytic Technology of Cultivated Land Quality from a Data Perspective," Land, MDPI, vol. 12(1), pages 1-17, January.

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