Articles | Volume 20, issue 22
https://doi.org/10.5194/bg-20-4551-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-20-4551-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
20 Nov 2023
Research article |
| 20 Nov 2023
| 20 Nov 2023
Toward coherent space–time mapping of seagrass cover from satellite data: an example of a Mediterranean lagoon
Guillaume Goodwin
CORRESPONDING AUTHOR
Fish-Pass Environnement, 18, Rue de la Plaine, 35830 Laillé, France
Marco Marani
DICEA, Universita di Padova, via Marzolo, 9, Padova, Italy
Sonia Silvestri
Dipartimento di Scienze Biologiche, Geologiche e Ambientali, Alma Mater Studiorum Università di Bologna, Via S. Alberto 163, Ravenna, Italy
Luca Carniello
DICEA, Universita di Padova, via Marzolo, 9, Padova, Italy
Andrea D'Alpaos
Dipartimento di Geoscienze, Universita di Padova, via Gradenigo, 6, Padova, Italy
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Short summary
Seagrass meadows are an emblematic coastal habitat. Their sensitivity to environmental change means that it is essential to monitor their evolution closely. However, high costs make this endeavor a technical challenge. Here, we used machine learning to map seagrass meadows in 148 satellite images in the Venice Lagoon, Italy. We found that adding information such as depth of the seabed and known seagrass location improved our capacity to map temporal change in seagrass habitat.
Seagrass meadows are an emblematic coastal habitat. Their sensitivity to environmental change...
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