Green Intelligence: Transforming Environmental Science through Artificial Intelligence
Abstract
Artificial Intelligence (AI) has emerged as a transformative force across scientific disciplines, with profound implications for environmental science. In this paper, let us explore the multifaceted impact of AI technologies including machine learning, deep learning, computer vision and natural language processing on environmental monitoring, modelling, prediction and policy formulation. AI enhances data processing from satellites, sensors and citizen science platforms, improves the accuracy of climate and ecological forecasts and enables real-time decision-making for conservation and sustainability. Case studies in wildfire prediction, deforestation tracking, and species identification illustrate the practical utility of AI. Integration of AI into environmental science promises more responsive, scalable and equitable environmental governance. This editorial underscores the necessity of interdisciplinary collaboration to maximize the potential of AI while mitigating its ecological and ethical risks.
Fields of Study & Subjects
Air Quality Monitoring and Forecasting
Fire effects on ecosystems
Knowledge Management and Technology
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 1 January 2026