From Autonomous Observations, to Digital Twins (Patrizio Mariani, DTU Aqua) скачать в хорошем качестве

From Autonomous Observations, to Digital Twins (Patrizio Mariani, DTU Aqua)

Integrated Ecosystem Assessments (IEAs) support ecosystem-based management, but require sustained, high-quality observations across scales. Traditionally, many indicators under the Marine Strategy Framework Directive (MSFD) depended on costly, labor-intensive surveys. Advances in marine automation, robotics, and modeling now enable partially automated monitoring with unprecedented temporal resolution and spatial coverage. In the EU-funded project MISSION ATLANTIC and BRIDGE-BS, autonomous platforms like mooring stations, ARGO profilers, unmanned surface vehicles, and gliders have been demonstrated and combined with remote sensing to delivered high quality data across multiple ocean regions. These heterogeneous datasets can be integrated using hybrid modelling that merge process-based simulations with machine learning, improving predictive capacity and detection of key ecosystem indicators and drivers. Project results contribute to advance the operationalisation of the Digital Twins of the Ocean (DTOs) framework, effectively linking advanced observations, AI, and ecosystem modeling. This integration strengthens IEA approaches providing decision-makers with actionable, science-based tools for sustainable marine resource management.