Center for Marine Biodiversity and Conservation

Oil spill risk is increasing in Alaska, due to retreating Arctic sea ice and increased maritime activity. This paper examines how Automated Identification Systems (AIS) and satellite imagery are used for spill detection and vessel tracking, detailing both their evolution and the technical limitations that arise when applying them in Arctic conditions. By analyzing remote sensing technologies and their integration with AIS, the paper identifies critical gaps in data accessibility and oil spill validation, especially in remote regions. It presents a dataset that allows remote sensing engineers to further adapt detection models to Arctic environments. It also highlights the role of community-based monitoring in bridging the gap between technology and spill detection. Finally, it proposes that community-led validation networks, improved tool access, and consistent QA feedback loops are essential for building a more responsive and equitable oil spill monitoring system.