GOYAS: A FAIR-by-Design System for Innovative remote-sensing data products

The Geospatial Open Science Yielding Applications (GOYAS) project, under the umbrella of the Horizon Europe project “OSCARS”, proposes a new approach for open science and open data in remote-sensing, integrating FAIR principles (Findable, Accessible, Interoperable, and Reusable) from the initial design phase. GOYAS provides innovative and/or experimental Earth Observation (EO) data and open science practices to address diverse environmental challenges, delivering advanced geospatial products that are tailored to meet the needs of multiple stakeholders, including researchers, decision-makers, and environmental managers.

GOYAS focuses on generating innovative and accessible remote sensing products for a variety of applications: monitoring water quality parameters, such as turbidity or chlorophyll-a; deriving high-resolution bathymetric maps over coastal regions based on optical instruments; assessing oceanographic variables like sea surface temperature and salinity; improving ocean and atmosphere forecasting capabilities with enhanced sea-surface wind & stress products; and supporting ecosystem monitoring and management in protected areas such as Doñana National Park. These products are generated through the integration of multi-source EO data, including Copernicus Sentinel satellites and complementary datasets, with advanced processing pipelines built on machine learning algorithms and geospatial standards.

A core strength of the GOYAS project lies in its FAIR-by-design system architecture, which prioritizes:

• Findability: Metadata-rich datasets indexed through open repositories and geospatial catalogues to enhance discoverability.

• Accessibility: FAIR-compliant platforms with user-friendly interfaces that provide seamless access to data products, ensuring usability across diverse technical expertise levels. GOYAS aims at facilitating the access providing data in common formats and contextualizing them with proper metadata.

• Interoperability: Adoption of open geospatial standards (e.g., OGC, INSPIRE) to ensure compatibility with existing systems and facilitate data exchange, specially under the context of Research Infrastructure hubs like ENVRI.

• Reusability: Comprehensive documentation and adherence to open licenses that allow users to adapt and build upon project outputs.

Key innovations include the automated processing of remote-sensing data to extract actionable insights and the application of machine learning to improve the accuracy and reliability of derived parameters. For example, GOYAS employs advanced spectral analysis techniques to calculate shallow bathymetry with sub-meter precision in coastal environments, as well as algorithms for near-real-time detection of water quality anomalies in inland waters.

The system also provides support for the monitoring and management of sensitive ecosystems. In Doñana National Park, GOYAS enables the identification of changes in hydrological regimes or vegetation health through the integration of long-term EO datasets with local ecological studies. Similar applications extend to marine protected areas, where GOYAS aids in monitoring oceanographic dynamics and ecosystem responses to climate change.

This presentation will detail the design, architecture, implementation, and outcomes of the GOYAS project, emphasizing its alignment with FAIR principles and its transformative potential for environmental monitoring. By fostering interoperability and collaboration across disciplines, GOYAS serves as a model for how open science and advanced remote sensing can drive innovation, sustainability, and informed decision-making in geospatial research.