Dictionary-Based Method for Fishing Gear Pattern Detection

Abstract

Fishing is an ancient practice that dates back to at least the beginning of the Upper Paleolithic period about 40,000 years ago. Nowadays, Fishing is one of the most important activities, as it provides a source of food and economic income worldwide. A key challenge in ecology and conservation is to decrease the Illegal, Unreported and Unregulated fishing (IUU). IUU fishing depletes fish stocks, destroys marine habitats, distorts competition, puts honest fishers at an unfair disadvantage, and weakens coastal communities, particularly in developing countries. One strategy to decrease the IUU fishing is monitoring and detecting the fishing vessel behaviors. Satellite–based Automatic Information Systems (S– AIS) are now commonly installed on most ocean–going vessels and have been proposed as a novel tool to explore the movements of fishing fleets in near real time. In this article, we present a dictionary–based method to classify, by using AIS data, between two fishing gear types: trawl and purse seine. The data was obtained from Global Fishing Watch. Our experiments show that our proposal has a good performance in classifying fishing behaviors, which could help to prevent overexploit and improve the strategies of the fisheries management.