Neural network modelling of Baltic zooplankton abundances

This data product is a series of gridded abundance maps for 40 zooplankton species from 2007 to 2013 in the Baltic Sea, based on a neural network analysis. As input data a combination of EMODnet Biology datasets were used, together with the environmental variables dissolved oxygen, salinity, temperature, chlorophyll concentration bathymetry and the distance from coast. Additionally the position (latitude and longitude) and the year are provided to the neural network. DIVAnd (n-dimensional Data-Interpolating Variational Analysis) and the neural network library Knet were used in this analysis.
 
Citation proposal
. Neural network modelling of Baltic zooplankton abundances. https://services.mspdata.eu:/geonetwork/srv/api/records/6d617269-6e65-696e-666f-000000006286

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GEMET - INSPIRE themes, version 1.0
  • Coordinate reference systems
Spatial scope
  • Regional
Use constraints
Other restrictions
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Attribution (CC BY)
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Barth, A.; Herman, P.M.J.; (2018): Neural network modelling of Baltic zooplankton abundances. Marine Data Archive. <a href="https://doi.org/10.14284/381" target="_blank">https://doi.org/10.14284/381</a>
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Other restrictions
Metadata language
no linguistic content; not applicable No linguistic content
Topic category
  • Biota
  • Geoscientific information
  • Oceans
Distribution format
  • NetCDF (Network Common Data Form) ()

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online information about the resource  
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online information about the resource  
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online instructions for transferring data from one storage device or system to another  
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Dataset

Domain consistency

Conformance result

Date ( Publication )
2017-03-02
Explanation
Conformance of this metadata set with the Technical Guidance for the implementation of INSPIRE dataset and service metadata based on ISO/TS 19139:2007 was not evaluated

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

Metadata

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6d617269-6e65-696e-666f-000000006286   XML
Metadata language
English
Character set
UTF-8 UTF8
Hierarchy level
Dataset
Date stamp
2024-12-04T00:00:00+01:00

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