Scholarlink

<p>The commune of El Oued, located in the Souf region of southeastern Algeria, is renowned for its unique hydro-agricultural system and its palm groves cultivated in depressions dug into the sandy soil to access the water table and enable date palm cultivation. In 2011, the Food and Agriculture Organization of the United Nations (FAO) classified the Ghout system as a Globally Important Agricultural Heritage System (GIAHS), due to its historical, socio-economic, and cultural significance worldwide. However, this vital agricultural system is threatened by various factors, including rising and falling water tables, extreme climatic conditions, rural exodus, groundwater pollution, and urban sprawl. In this study, we applied the YOLOv8 deep learning model to monitor the Ghouts’ degradation by analyzing over 1300 satellite and aerial images from 2007 to 2024. The model tracked the evolution of Ghout areas, identified and classified their condition, and assessed the rate of loss. Analyses reveal a significant reduction in Ghout areas, from 61.79 hectares in 2007 to 23.90 hectares in 2024, with a particularly alarming loss of 17.65 hectares between 2018 and 2019. This demonstrates the effectiveness of artificial intelligence in providing a rapid and accurate analysis for monitoring and predicting environmental changes, offering valuable insights for the conservation and sustainable management of this unique ecosystem.</p> Graphic abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

YOLOv8 model for monitoring ghout degradation in the El Oued region, southeastern Algeria

  • 期刊论文

  • 发表日期：

    2025年11月17日

查看全文
  • Faouzi Mohammed Lacheheb,
  • Nabil Mega,
  • Akram Mohamed Seddiki,
  • Abdelmonem Miloudi,
  • Mohamed Nadhir Abid,
  • Ishak Guemari,
  • Azzeddine Laouid,
  • Abderrahmane Khechekhouche

摘要

The commune of El Oued, located in the Souf region of southeastern Algeria, is renowned for its unique hydro-agricultural system and its palm groves cultivated in depressions dug into the sandy soil to access the water table and enable date palm cultivation. In 2011, the Food and Agriculture Organization of the United Nations (FAO) classified the Ghout system as a Globally Important Agricultural Heritage System (GIAHS), due to its historical, socio-economic, and cultural significance worldwide. However, this vital agricultural system is threatened by various factors, including rising and falling water tables, extreme climatic conditions, rural exodus, groundwater pollution, and urban sprawl. In this study, we applied the YOLOv8 deep learning model to monitor the Ghouts’ degradation by analyzing over 1300 satellite and aerial images from 2007 to 2024. The model tracked the evolution of Ghout areas, identified and classified their condition, and assessed the rate of loss. Analyses reveal a significant reduction in Ghout areas, from 61.79 hectares in 2007 to 23.90 hectares in 2024, with a particularly alarming loss of 17.65 hectares between 2018 and 2019. This demonstrates the effectiveness of artificial intelligence in providing a rapid and accurate analysis for monitoring and predicting environmental changes, offering valuable insights for the conservation and sustainable management of this unique ecosystem.

Graphic abstract