Inlier Modeling-Based Good Fishing Ground Detection for Efficient Bullet Tuna Trolling Using Meteorological and Oceanographic Information

An attempt has been made to construct a system for detecting good fishing grounds using meteorological and oceanographic information. Monitoring fishing ground conditions is helpful for fishermen’s decision-making for efficient operations and fishery resource management. Since it is not realistic to monitor the ocean condition of the entire target area, an inlier modeling-based (also referred to as unsupervised) detector is constructed using only the good fishing ground data observed during the operation, and useful features for monitoring fishing ground conditions are also investigated. Experimental comparisons using four years of operation data of bullet tuna trolling demonstrated that the developed system detected good fishing grounds with a recall of about 99%.