A review of remote sensing and artificial intelligence applications in global fisheries monitoring and management

Abstract

The sustainable management of fisheries faces growing challenges due to the vast expanse of the oceans, overfishing, Illegal, Unreported and Unregulated (IUU) fishing, and climate change impacts. Traditional methods of monitoring are often insufficient to manage the complexity of these issues. The integration of Artificial Intelligence (AI) and Remote Sensing (RS) provides transformative, large-scale, real-time and cost-effective solutions for marine environment monitoring. RS tools like satellites and drones collect continuous data on oceanographic parameters such as Sea Surface Temperature (SST), chlorophyll-a and vessel activity. AI techniques including Machine Learning (ML), deep learning and computer vision process these complex data-sets to automate stock assessments, predict fish abundance, identify species and detect IUU fishing. Practical applications such as Global Fishing Watch and AI-powered fish counting highlight these benefits. Despite progress challenges remain in data quality, model transparency and capacity building. Future innovations such as eDNA monitoring and blockchain are expected to play a vital role in advancing sustainable fisheries management by supporting adaptive, data-driven strategies.