Research progress on application of AIS 

data in distant-water fishery

XU Zhenqi1, WANG Jintao1,2,3,4,5, LEI Lin1,2,3,4,5, WU Feng1,2,3,4,5, CHEN Xinjun1,2,3,4,5

（ 1. College of Marine Sciences，Shanghai Ocean University，Shanghai201306，China； 2. Key Laboratory of Oceanic 

Fisheries Exploration，Ministry of Agriculture and Rural Affairs，Shanghai201306，China；3. National Engineering Research 

Center for Oceanic Fisheries，Shanghai201306，China；4. Key Laboratory of Sustainable Exploitation of Oceanic Fisheries 

Resources，Ministry of Education，Shanghai201306，China；5. Scientific Observing and Experimental Station of 

Oceanic Fishery Resources，Ministry of Agriculture and Rural Affairs，Shanghai201306，China ）

Abstract: Pelagic fishery is an important industry of the national economy. Due to the distance from land and port, the lack of effective means of observation and regulation is not conducive to the sustainable development of this industry. Automatic identification system （AIS） is an open data transmission system applied between ship and shore, and between ship and ship. The signals are sent and received in very high frequency （VHF） through transponders, and detailed information such as ship’s movement position is recorded using global positioning system （GPS） receivers, and important information such as ship’s position, speed, heading, ship’s name and call sign can be exchanged automatically. The initial purpose of AIS is to ensure the safety of ship navigation, which is a necessary navigation equipment for modern ships. The data generated by AIS has become an important data source for the study of pelagic fisheries because of its characteristics of wide coverage and high accuracy. This paper clarified the important role of AIS in pelagic fisheries by analyzing the characteristics of AIS data and its processing methods and the development and application of AIS technology at home and abroad. It explains how to extract and process AIS data effectively, including how to handle missing values and filter outliers and store them in an appropriate format, and finally how to apply the processed information to the field of pelagic fisheries through different algorithms and visualization processes. This paper focuses on three main application directions of AIS data in pelagic fisheries and the corresponding research methods. The identification of fishing vessel operation status and central fishing ground forecast are the most applied aspects in the field of pelagic fisheries, including the identification of fishing vessel operation status, calculation of fishing operation intensity, perception of fishing ground exploitation situation and dynamic changes by using the attribute features such as speed and heading in AIS trajectory data, which play an important role in the assessment of fishery resources and marine ecological protection. The monitoring of offshore fishing vessels and illegal fishing behavior is one of the most direct directions of AIS data application. AIS has great potential in monitoring unregulated fishing activities, and the larger and more perfect the amount of AIS data, the more accurate the monitoring of such activities. More and more scholars are exploring the application of AIS data in marine environmental protection and marine habitat management, which provides more tools to utilize and protect marine biodiversity. The application of AIS data is beneficial to improving the efficiency of marine habitat management, and also plays a role in monitoring overfishing in the high seas of pelagic fisheries. Then, we discusses the advantages and disadvantages of each method and its development prospects by comparing the research methods in different application directions. With the continuous progress of marine fisheries disciplines, modern statistics, artificial intelligence, machine learning and data mining and other disciplines and methods, the application models and research methods of AIS in fisheries science are becoming more and more diversified, promoting the progress and development of fisheries science, especially in fishing forecast technology and fishing vessel monitoring. However, there are certain problems and limitations of many methods and models in practical fisheries production applications. Therefore, we conclude with a summary of the important roles played by AIS data in pelagic fisheries applications and make a discussion of the shortcomings and deficiencies of related research methods. And a proposal for the optimization of AIS data applications in pelagic fisheries is presented, which is expected to provide a scientific basis for the sustainable development of pelagic fisheries. In the future, AIS may also solve more challenges including IUU monitoring and marine environmental protection to better serve the global marine fisheries.

Keywords: AIS data; pelagic fishery; fishing state; fishery forecast; IUU; marine environment protection