Agentic AI for Earth-Observation-Driven Maritime Monitoring - the SeaScope Project

We present SeaScope, an explainable AI agent that accelerates interaction with complex Earth Observation (EO) workflows. Users express analytical questions in natural language, which are transformed into transparent, executable EO analyses. By combining generative AI, vision–language models, and Retrieval-Augmented Generation (RAG), SeaScope links scientific literature, satellite data descriptions, and validated analysis methods to automatically generate, execute, and explain EO workflows. For example, a query such as “Detect vessel activity and possible oil spills in May 2025” triggers dataset selection, code generation, cloud execution, and map outputs with traceable reasoning.

 

SeaScope is designed as a geoscience-specific AI agent that supports both rapid decision-making and accelerated research. Non-technical users can obtain EO-based insights in time-critical situations without continuous involvement of expert programmers, while researchers benefit from faster hypothesis testing, automated pipeline generation, and reproducible workflows. Human expertise remains central: users inspect retrieved sources, review generated code, and validate analytical steps, ensuring scientific control and accountability. This setup combines domain knowledge with AI-driven scalability, addressing challenges such as sensor-specific scripts and fragmented tools.

 

As a pilot use case, SeaScope is applied to maritime EO in the Mediterranean region, supporting environmental monitoring and marine activity analysis using satellite data. Beyond the application, the project delivers research insights on generative and vision-based AI for EO, including lessons learned from benchmarking LLMs for code generation, evaluating vision-language models for image understanding, and comparing different RAG and knowledge ingestion strategies. The findings highlight practical trade-offs in accuracy, robustness, explainability, and user validation in real-world workflows.