According to the EU Habitat directive and the Marine Strategy Framework Directive, member states are required to map, monitor and evaluate changes in the quality and areal distribution of different marine habitats and biotopes. Submerged aquatic vegetation (SAV), in particular eelgrass, is one of the key indicators of ecological status and environmental state of water bodies, and therefore widely used in reporting related to these directives.
Copernicus Sentinel-2 imagery, novel machine learning techniques and advanced data processing to create the first spatial overview of the distribution of SAV at national scale in Sweden.
A cloud-based web-application for Sentinel-2 based SAV mapping without prior specialist knowledge Input.
A training dataset constructed with more than 30 000 manually drawn polygons to build a robust machine learning model and predict nationwide SAV.
Huber, Silvia. et al. (2021), Novel approach to large-scale monitoring of submerged aquatic vegetation: A nationwide example from Sweden. Integrated Environmental Assessment and Management.
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