Fishing Activity Prediction from Satellite Boat Detection Data

Monitoring and predicting fishing activity is important for the fishery resource management and the maritime traffic safety. In this paper, we trained deep learning models by grid images from satellite observations to predict areas of fishing activity in next three-day period. The best model predicted the estimated size of fishing areas with more than 70% coverage for days 1 and 3 after prediction, and areas of congestion with more than 50% certainty for day 1. In particular, the model using time information performed with higher coverage and certainty. The models might be used not only to predict fishing activities for resource management and navigation safety but also to supplement data in cloudy weather for supporting optical satellite observations.