Webinar: Exploring the Role of Artificial Intelligence in Landscape Restoration and Soil Health in Ethiopia

Artificial Intelligence (AI) refers to developing computer systems capable of performing tasks that typically require human intelligence. AI has applications in land restoration and soil health by providing data-driven insights and precision tools that improve decision-making. By helping to restore degraded lands and enhancing soil health, AI plays a crucial role in promoting integrated landscape management and combating the effects of climate change Through machine learning algorithms, AI can analyse complex data from satellite images, soil sensors, and climate patterns to monitor soil conditions, detect degradation, and predict ecological changes. This enables targeted restoration efforts, such as optimized erosion control, and nutrient management, which lead to healthier, more resilient ecosystems.

Capacity building at each stage including training researchers and lecturers on the role of AI in landscape restoration and soil health is crucial for advancing sustainable land management and ecological restoration practices. AI tools can analyze large complex data sets, identify patterns, and generate predictive models that help researchers make informed decisions.

By understanding how to leverage AI, researchers can enhance their ability to monitor soil conditions, track vegetation changes, and assess restoration efforts’ impact with greater accuracy and efficiency. Moreover, training in AI empowers researchers to create innovative solutions tailored to specific landscapes, improving the effectiveness of soil management techniques and promoting biodiversity. Equipping researchers with AI skills accelerates the development of data-driven strategies to address soil degradation, combat desertification, and restore ecosystems, contributing significantly to global environmental health and resilience efforts.

Recognizing the potential of AI, the Alliance and ELaRP organized the webinar on AI, soil health and landscape restoration, which attracted a multidisciplinary team (Fig 1).