Biodiversity loss remains one of the most urgent global challenges, threatening ecosystem resilience, human well-being, and the achievement of the European Green Deal objectives. Despite ambitious aims to improve the monitoring of ecosystem condition and biodiversity in Europe, significant challenges persist – including gaps in harmonized data, limited integration of multi-source observations (particularly remote sensing and in situ data) and insufficient capacity to deliver timely, policy-relevant evidence on the state of biodiversity and ecosystem services. More robust, scalable observation systems and harmonized biodiversity monitoring measures, such as Essential Biodiversity Variables (EBVs), are essential to meeting EU and international biodiversity commitments, including the EU Biodiversity Strategy for 2030, the Nature Restoration Law, and the Kunming-Montreal Global Biodiversity Framework.
OBSGESSION (Observation of Ecosystem Changes for Action) addresses these challenges by creating innovative workflows that integrate in-situ monitoring, remote sensing, citizen science, and modelling. The project brings together remote sensing and biodiversity experts, various data infrastructures, and policy stakeholders to co-design approaches that can strengthen biodiversity monitoring and assessment across multiple scales.
The overall objective and key ambition of OBSGESSION is to monitor and predict biodiversity change and its direct and indirect drivers in terrestrial and freshwater ecosystems through the integration of state-of-the-art multi-sensor Earth Observation (EO) data, innovative in-situ (including citizen science) data, and products, together with next-generation ecological models that account for uncertainty. To achieve this, the project is structured around five interlinked specific objectives that together form the foundation for delivering measurable impacts:
1) Identify policy needs and scientific gaps;
2) Develop and integrate EBV-enabling EO and in-situ data streams;
3) Build frameworks for detection, attribution and modelling of biodiversity change;
4) Assess and propagate uncertainty to decision-support systems; and
5) Validate approaches in pilot areas and foster science–policy integration