TY - GEN
T1 - Artificial neural networks for discovering characteristics of fishing surveillance areas
AU - Correia, Anacleto
AU - Moura, Ricardo
AU - Água, Pedro
AU - Lobo, Victor
N1 - This work was funded by the Portuguese Navy.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Artificial neural networks
KW - Fishing surveillance
KW - Geo-spatial information
UR - http://www.scopus.com/inward/record.url?scp=85080864454&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-40690-5_8
DO - 10.1007/978-3-030-40690-5_8
M3 - Conference contribution
AN - SCOPUS:85080864454
SN - 978-3-030-40689-9
T3 - Advances in Intelligent Systems and Computing
SP - 75
EP - 83
BT - Information Technology and Systems - Proceedings of ICITS 2020
A2 - Rocha, Álvaro
A2 - Ferrás, Carlos
A2 - Montenegro Marin, Carlos Enrique
A2 - Medina García, Víctor Hugo
PB - Springer
CY - Cham
T2 - International Conference on Information Technology and Systems, ICITS 2020
Y2 - 5 February 2020 through 7 February 2020
ER -
