Project

GeoAtlant-AI&BI is aligned with the regional priority area Space and Data Science, while also contributing to Territory, Resources and Circular Economy, Environment and Climate Action, Digital Transformation and Economy 4.0, Tourism, and Sea and Fisheries. The project promotes the integration of digital technologies, geospatial data, Artificial Intelligence and Bayesian inference to support smarter and more sustainable management of natural resources, land use, biodiversity and tourism.

UNESCO Chair framework

GeoAtlant-AI&BI was developed within the framework of the UNESCO Chair “Biodiversity and Sustainability in Atlantic Islands”, reinforcing the Chair’s mission to promote research, knowledge transfer, capacity building and cooperation on biodiversity and sustainability in island systems.

By combining geospatial data, Artificial Intelligence and Bayesian inference, the project contributes to the Chair’s broader objectives of supporting evidence-based knowledge, strengthening collaboration among academic, public and private entities, and promoting sustainable development in Atlantic islands, with the Azores as a pilot region.

General objective

To establish a robust geospatial data integration platform focused on Atlantic Islands, using the Azores as a pilot region, supporting the analysis and organization of data related to land management, biodiversity conservation, landscape interpretation and environmental decision-making.

Specific objectives

Integrate geospatial data

Compile and organize data from multiple sources, including land use/land cover, protected areas, habitats, forest inventories, geosites, digital elevation models and bioclimatic variables.

Apply AI and Bayesian tools

Develop models to support environmental research and decision-making, including land-use change, invasive species distribution, population dynamics and tourism potential.

Support biodiversity conservation

Produce maps, models and indicators that help guide conservation, habitat management, invasive species control and sustainable use of natural resources.

Promote capacity building

Support knowledge transfer through training, workshops, webinars, educational resources and a postgraduate course in AI and Bayesian data analysis.

Foster Atlantic cooperation

Contribute to the creation of a collaborative Atlantic cluster focused on geospatial data analysis, Artificial Intelligence and Bayesian inference.

Strategic relevance

The project addresses the underuse of existing Earth observation and geospatial data by making these resources more accessible and usable. It promotes innovation, open-source GIS, knowledge transfer and long-term capacity building in the Azores and other Atlantic Island contexts.