Artificial Intelligence and Remote Sensing for Desertification in Iraq: Overcoming Traditional Monitoring Constraints

Desertification is one of the most pressing environmental threats and socioeconomic issues facing Iraq, both as a result of aggravated weather and climatic conditions due to climate change and urban sprawl and as a consequence of unsustainable land use. Conventional methods of monitoring – like ground surveys and visual interpretation of satellite images – are costly and time-consuming and may not be able to monitor large-scale changes on a real-time basis. To overcome these limitations, this article 1 investigates the potential of artificial intelligence (AI), including its integration with remote sensing, in improving the detection, assessment, and prediction of land degradation. Exploiting data-driven models, AI enables rapid and reliable diagnoses toward better land management, in line with essential Sustainable Development Goals, such as food security, climate action, and biodiversity conservation. Major challenges hindering the application process in Iraq were also reported in this paper, including poor data infrastructure, lack of policy integration, and institution capacity. Finally, it suggests research directions to reinforce the AI monitoring system, to provide support for a more efficient response to desertification and sustainable development.