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<p>Agricultural drought is a recurring catastrophe with devastating impacts on public health, the economy, and ecosystems. Within this framework, this review highlights the current state of knowledge and scientific studies carried out on agricultural drought, applying a bibliometric analysis to assess the state of the art in drought studies and a systematic analysis to map scientific advances in the use of technologies (remote sensing, GIS, AI). Data on publications related to these topics were obtained from the Scopus and Web of Science databases, covering the period from 2000 to 2024, using the Bibliometrix R package. The results of the analysis showed a significant annual increase in publications, with 18.44%. This growth is mainly driven by the United States, China, and Australia, which are among the leading countries cited in the scientific literature. This work provides an exhaustive analysis, including a critical assessment of the most commonly used drought indices. It outlines their importance and limitations, a comparison of the performance of machine learning algorithms, with Random Forest systematically superior to other algorithms in its ability to handle non-linear remote sensing data and identify the most influential variables, and finally, an examination of the methods applied in GIS, including their integration with cloud platforms for more efficient, large-scale evaluation. However, this study examines major challenges, including the availability and interpretation of complex satellite data, the inadequacy of their spatial resolutions, and the complexity and adaptability of AI models to various agroclimatic contexts.</p>

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Bibliometric and systematic review of agricultural drought assessment and monitoring: trends and techniques

  • 期刊论文

  • 发表日期：

    2025年9月4日

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  • Fatima Ezzahra El Kamouni,
  • Mustapha Namous,
  • Samira Krimissa,
  • Hasna Eloudi,
  • Maryem Ismaili,
  • Abdenbi Elaloui,
  • Insaf Ouchkir,
  • Oussama Nait‐Taleb,
  • Mohamed Chikh Essbiti

摘要

Agricultural drought is a recurring catastrophe with devastating impacts on public health, the economy, and ecosystems. Within this framework, this review highlights the current state of knowledge and scientific studies carried out on agricultural drought, applying a bibliometric analysis to assess the state of the art in drought studies and a systematic analysis to map scientific advances in the use of technologies (remote sensing, GIS, AI). Data on publications related to these topics were obtained from the Scopus and Web of Science databases, covering the period from 2000 to 2024, using the Bibliometrix R package. The results of the analysis showed a significant annual increase in publications, with 18.44%. This growth is mainly driven by the United States, China, and Australia, which are among the leading countries cited in the scientific literature. This work provides an exhaustive analysis, including a critical assessment of the most commonly used drought indices. It outlines their importance and limitations, a comparison of the performance of machine learning algorithms, with Random Forest systematically superior to other algorithms in its ability to handle non-linear remote sensing data and identify the most influential variables, and finally, an examination of the methods applied in GIS, including their integration with cloud platforms for more efficient, large-scale evaluation. However, this study examines major challenges, including the availability and interpretation of complex satellite data, the inadequacy of their spatial resolutions, and the complexity and adaptability of AI models to various agroclimatic contexts.