Application of satellite imagery and Artificial Intelligence (AI) for PFAS Contamination Mapping in African Aquatic Systems: Advancing Data-Driven Environmental and Public Health Risk Assessment
Domain:
environment and energygeospatialRecord type:
This Zenodo record provides an archived version of the article:
“Application of Satellite Imagery and Artificial Intelligence (AI) for PFAS Contamination Mapping in African Aquatic Systems: Advancing Data-Driven Environmental and Public Health Risk Assessment.”
This study reviews the integration of satellite remote sensing and artificial intelligence techniques for environmental monitoring and public health risk assessment in data-limited regions, with a focus on African aquatic systems. The paper synthesizes current approaches, evaluates machine learning methods, and highlights key challenges in PFAS contamination detection using indirect proxy indicators.
The study also outlines a conceptual framework combining satellite data, geospatial analysis, and AI-based modeling to support scalable and cost-effective environmental monitoring and decision-making.
Original publication: https://doi.org/10.30574/wj…