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Morphological map of the Irish continental shelf created using Deep Learning
Citation
Arosio, R.; Hobley, B.; Wheeler, A.; Sacchetti, F.; Conti, L.; Furey, T.; Lim, A.; University College Cork (UCC), Ireland; (2024): Morphological map of the Irish continental shelf created using Deep Learning. https://marineinfo.org/id/dataset/8521
Contact: Arosio, Riccardo
Access data
Archived data
Availability: Creative Commons License This dataset is licensed under a Creative Commons Attribution 4.0 International License.
Description

Morphological map (10 classes) of the Irish shelf resulting from the modal aggregation (Cell statistics “MAJORITY” in ArcGIS Pro 3.1) of the qualitatively and quantitatively best Fully Convolutional Neural Networks models obtained in the study: Arosio, R., Hobley, B., Wheeler, A. J., Sacchetti, F., Conti, L. A., Furey, T. and A. Lim, 2023. Fully convolutional neural networks applied to large-scale marine morphology mapping. Frontiers in Marine Science, Sec. Ocean Observation, 10, https://doi.org/10.3389/fmars.2023.1228867.

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 862428 (MISSION ATLANTIC).

Scope
Keywords:
Marine/Coastal, Data not evaluated, Elevation, Esri Shapefile, Geology, Marine regions and units (Marine Strategy Framework Directive), Metadata conformant, National, No limitations to public access, WGS84/UTM zone 29N (EPSG:32629), ANE, Celtic Sea, Celtic Shelf, Irish Exclusive economic Zone, Irish part of the North Atlantic Ocean
Geographical coverage
ANE, Celtic Sea [Marine Regions]
Celtic Shelf [Marine Regions]
Irish Exclusive economic Zone [Marine Regions]
Irish part of the North Atlantic Ocean [Marine Regions]
Contributors
University College Cork (UCC), more, data creator
Arosio, Riccardo
Wheeler, Andrew
Lim, Aaron
University of East Anglia (HQ), more, data creator
Hobley, Brandon
Marine Institute Ireland (MI), more, data creator
Sacchetti, Fabio
Furey, Thomas
University of São Paulo (USP), more, data creator
Conti, Luis
Project
MISSION ATLANTIC: Towards the Sustainable Development of the Atlantic Ocean: Mapping and Assessing the present and future status of Atlantic marine ecosystems under the influence of climate change and exploitation, more
Funding H2020
Grant agreement ID 862428
Publication
Based on this dataset
Arosio, R. et al. (2023). Fully convolutional neural networks applied to large-scale marine morphology mapping. Front. Mar. Sci. 10: 1228867. https://dx.doi.org/10.3389/fmars.2023.1228867, more
URLs
Other:
Data type: GIS maps
Release date: 2024-03-15
Metadatarecord created: 2024-03-14
Information last updated: 2024-06-05
All data in the Integrated Marine Information System (IMIS) is subject to the VLIZ privacy policy