Identification of Fishing State of Purse Seine Fishing Vessels Based on Multi-Indices.

With the popularization of vessel satellite AIS (automatic identification system) equipment and the continuous improvement of the AIS data's coverage, continuity and effectiveness, AIS has become an important data source to study the navigation characteristics of vessel groups. This study established an identification model to extract the fishing state and intensity information of fishing vessels, based on the AIS data of purse seine fishing vessels, combined with the variables of vessel position, speed and course. Expert experience, spatial statistics and data mining analysis methods were applied to establish the model, and the Western and Central Pacific Ocean areas were studied. The results showed that the overall accuracy of identification of the fishing state using Support Vector Machine method is higher, and the method has a good modeling effect. The spatial distribution characteristics of the vessels' fishing intensity based on AIS data showed a significant cluster distribution pattern. The obtained high-intensity fishing area can be used as a prediction of purse seine fishing grounds in the Western and Central Pacific areas. Through the processing and research of AIS data, this study provided important scientific support for the identification of fishing state of purse seine fishing vessels. The spatial fishing intensity of fishing vessels based on AIS data can also be used for the analysis of fishery resources and fishing grounds, and further serve the sustainable development of marine fisheries. [ABSTRACT FROM AUTHOR]