Morphological map of the Irish continental shelf created using Deep Learning

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.
 
Citation proposal
Riccardo Arosio (University College Cork) - Brandon Hobley (University of East Anglia) - Andrew Wheeler (University College Cork) - Fabio Sacchetti (Marine Institute Ireland) - Luis Conti (Federal Institute of Education, Science and Technology of Rio Grande do Sul) - Thomas Furey (Marine Institute Ireland) - Aaron Lim (University College Cork) (2024) . Morphological map of the Irish continental shelf created using Deep Learning. https://services.mspdata.eu:/geonetwork/srv/api/records/f043785c-23d1-4845-b9c8-23d1703ef2c2

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Date ( Publication )
2024-03-15
Credit
University College Cork (Ireland)
Credit
University of East Anglia (England)
Credit
Marine Institute (Ireland)
Credit
Federal Institute of Education, Science and Technology of Rio Grande do Sul (Brazil)

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GEMET - INSPIRE themes, version 1.0 ( Theme )
  • Geology
Spatial scope
  • National
INSPIRE priority dataset
  • Marine regions and units (Marine Strategy Framework Directive)
Mission Atlantic - BODC Parameters ( Theme )
  • /Marine geology
Mission Atlantic - Data type (DMP) ( Theme )
  • Modelling data , Spatial data products
Mission Atlantic - Case Studies ( Theme )
  • Celtic Seas
Mission Atlantic - Resources ( Theme )
  • Data , Article , MISSION ATLANTIC Results
Mission Atlantic - Work Package ( Theme )
  • WP4 Benthic Mapping
Use constraints
Other restrictions
Other constraints
Attribution (CC BY)
Access constraints
Other restrictions
Spatial representation type
Vector
Denominator
1000
Metadata language
No linguistic content No linguistic content
Topic category
  • Elevation
N
S
E
W


Distribution format
  • Esri Shapefile ()

OnLine resource
INSPIRE Download Service (WFS)  
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INSPIRE WMS  
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Download original data  
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IMIS catalogue  
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GeoNode  
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Scientific publication  
Hierarchy level
Dataset

Domain consistency

Conformance result

Date ( Publication )
2017-03-02
Explanation
This metadata set is conformant with the Technical Guidance for the implementation of INSPIRE dataset and service metadata based on ISO/TS 19139:2007
Pass
true

Conformance result

Date ( Publication )
2010-12-08
Explanation
Conformance of this data set with the INSPIRE Implementing Rules for the interoperability of spatial data sets and services was not evaluated
Statement
The input bathymetry layers for this work were obtained from the multibeam echosounder (MBES) bathymetry (accessible on INFOMAR hydrographic dataset - https://www.infomar.ie ). More details on https://doi.org/10.3389/fmars.2023.1228867.

Metadata

File identifier
f043785c-23d1-4845-b9c8-23d1703ef2c2   XML
Metadata language
English
Character set
UTF8
Hierarchy level
Dataset
Date stamp
2024-07-31T08:52:35.229Z

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