Artificial neural networks for discovering characteristics of fishing surveillance areas

Anacleto Correia, Ricardo Moura, Pedro Água, Victor Lobo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

The demographic pressure entails over-exploitation of the coastal regions and the consumption of marine resources in a non-sustainable manner, jeopardizing the species renewal. Several species are currently facing great threat of disappearing from Portuguese coastal waters, namely the Sardina pilchardus, due to illegal, unregulated or not reported fishing. The Portuguese Navy performs regular surveillance and monitoring of fishing activities for law enforcement. Those actions gather useful information about the fishing activity, specifically about the types of fishing gear used. Since the geo-spatial data on a regular map, by itself, was not enough to present a clear picture regarding the predominant type of fishing gears used for captured sardine in the Portuguese coastal areas, we applied an artificial neural network to georeferenced information in order to derive a new layer with the areas where the fishing gears used for Sardina pilchardus fishing are most likely to be found.

Original languageEnglish
Title of host publicationInformation Technology and Systems - Proceedings of ICITS 2020
EditorsÁlvaro Rocha, Carlos Ferrás, Carlos Enrique Montenegro Marin, Víctor Hugo Medina García
Place of PublicationCham
PublisherSpringer
Pages75-83
Number of pages9
ISBN (Electronic)978-3-030-40690-5
ISBN (Print)978-3-030-40689-9
DOIs
Publication statusPublished - 2020
EventInternational Conference on Information Technology and Systems, ICITS 2020 - Bogota, Colombia
Duration: 5 Feb 20207 Feb 2020

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
Volume1137 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

ConferenceInternational Conference on Information Technology and Systems, ICITS 2020
CountryColombia
CityBogota
Period5/02/207/02/20

Keywords

  • Artificial neural networks
  • Fishing surveillance
  • Geo-spatial information

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