Integration of remote sensing techniques and connectionist models for decision support in fishing catches

Authors:
Alfonso Iglesias;Carlos Dafonte;Bernardino Arcay;J. Manuel Cotos
Affiliations:
Department of Information and Communications Technologies, Faculty of Computer Science, University of A Coruña, S/N 15071 A Coruña, Spain;Department of Information and Communications Technologies, Faculty of Computer Science, University of A Coruña, S/N 15071 A Coruña, Spain;Department of Information and Communications Technologies, Faculty of Computer Science, University of A Coruña, S/N 15071 A Coruña, Spain;Remote Sensing Laboratory (TELSIG), Department of Electronics and Computing, Faculty of Physics, University of Santiago, 15782 Santiago de Compostela, Spain
Venue:
Environmental Modelling & Software
Year:
2007

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Abstract

Estimating the presence and size of fishing banks has significant ecological and economic advantages: it contributes to a rational exploitation of the available marine resources, to the reduction of fuel costs, and to a general decrease in required fishing time. This work presents the integration of remote sensing techniques and connectionist models for the prediction of fishing banks. We have developed and implemented an information system that stores and processes the data from various satellites and visualizes them by generating a geographic forecasting map.