We collected AIS information on fishing vessels operating near Jeju Island, and analyzed appearance density of the Chinese fishing vessels and inferred the movements of the fishing grounds. AIS information was received from October 16, 2016 to October 16, 2017 and stored on a hard disk through a program called AisDecoder. Unauthorized fishing vessels within the Exclusive Fisheries Agreement Zone (EFAZ) operated near the EFAZ boundary, and the frequency of appearance of fishing vessels were high in the middle waters of Korea and Japan, 252 and 250 fishing zones. Chinese fishing vessels authorized to enter appeared scattered outside the Prohibiting Fishing Zone of the Large Trawlers (PFZLT), and the closer they were to the PFZLT boundary, the higher the appearance density. And the appearance of Chinese fishing vessels with a speed from 0 to 3 knots was mostly outside the EFAZ, showing high density in the waters close to the boundary between Korea and Japan. On the other hand, within the EFAZ, the frequency of appearance of Chinese fishing vessels was also low and scattered. The appearance of Chinese fishing vessels with a speed from 3 to 5 knots mostly shows some variability within the EFAZ, but the frequency of appearance was high and the density was high. The seasonal appearance of Chinese fishing vessels in the waters south of Jeju Island appeared in the southwest in the autumn and then moved south and southeast of Jeju Island in the winter, and in the spring and summer. They were considered going to other fishing grounds without fishing in the waters south of Jeju Island.

The purpose of this paper is to explore the fishing grounds of trawl fishery, which are operating in the waters around Jeju Island, and to investigate the monthly shifting changes of the explored fishing grounds. Information on AIS of fishing vessels operating near Jeju Island was collected and analyzed from October 16, 2016 to October 16, 2017. Thus, the location of fishing vessels with the same operational characteristics as those in this industry was extracted and displayed on Google Maps' location drawings to analyze the dense distribution of fishing vessels according to the frequency of their appearance. In the distribution of fishing vessels that appeared in October, a wide range of fishing grounds connecting the upper and lower waters of the 221 and 222 sea of fishing area was found to have gradually expanded and increased density, showing the widest range and highest density in December, and then gradually decreasing from January 2017 to near extinction in May. The distribution of fishing vessels that appeared in the left and lower waters of the 243 sea estuary increased not only in November and December, but also in the appearing sea areas gradually moved to the 242 sea and the range of their appearance was extended to the 241 sea. In other words, the highly dense fishing area in December indirectly shows that it is winter fishing grounds for these industries. The distribution of these dense fishing vessels gradually moved north and west with each passing day, reducing their density and reaching a near extinction in August. However, in September, the density was gradually restored again. Fishing vessels that appeared in high density in the northern waters of the 224 sea east of the Yeoseo island in December were thought to be fishing vessels, whose density decreased over time, almost disappeared in May, and reappeared in July and August, showing a certain degree of density, and then decreased again.

In the area around Jeju Island, the squid jigging fishery and the hair-tail angling are popular. Therefore, the study on the characteristics of the formation and shift of fishing grounds is very important. We have received and analyzed AIS data of all vessels around Jeju Island from October 16, 2016 to October 16, 2017, and extracted the positions of the fishing vessels with the same operational characteristics as the fishing vessels of their fisheries. The distribution chart of the frequency of fishing vessels appearing in each predefined fishing grid (1 NM × 1 NM) was analyzed. So we took a analogy with the monthly shift of fishing grounds. Many fishing vessels appeared in the seas around Jeju Island from November 2016 to January 2017, and the frequency of their appearance was maintained. In November, however, fishing vessels were mostly concentrated in coastal waters. Yet, the density gradually weakened as they moved into January. From February, the frequency itself began to decline, making it the worst in April. The high concentration of fishing vessels in the waters leading from Jeju Island's northwest coast to south coast in November is believed to be related to the yellowtail fishery that are formed annually in the coastal waters off the island of Marado. In May 2017, the appearance frequency of fishing vessels increased and began to show a concentration in coastal waters around Jeju Island. Fishing vessels began to flock in waters northwest of Jeju Island beginning in July and peaked in August, and by September, fishing vessels were moving south along the coast of Jeju Island, weakening the density and spreading out. Between July and August, fishing vessels were concentrated in waters surrounding Jeju Island, which is believed to be related to the operations of fishing vessels for the squid jigging fishery and the hair-tail angling.

The constant increase in marine traffic and the simultaneous growth of the demand for exploiting marine areas (e.g., installing offshore wind power plants) require an adequate planning strategy for managing high traffic volumes. Maritime Spatial Planning (MSP) is the process of public development of an allocation plan for distributing, both spatially and temporally, human activities in marine areas. The adoption of e-Navigation is a possible solution for improving safety and security at sea by integrating maritime information on board and ashore. Automatic Identification System (AIS) data represents a fundamental source of information, since the analysis of AIS data can highlight the presence of congested areas as well as of illegal actions, such as smuggling, pollution, and unauthorized phishing in protected areas. Indeed, those activities are often characterized by abnormal manoeuvres that can be recognized by analyzing the routes of the vessels. However, the huge dimension of the AIS data to process requires the adoption of careful strategies for the data visualization. In this paper, we present a complete pipeline for visualizing ship routes from raw AIS data, which is a fundamental pre-requisite for carrying out a significant AIS-based route analysis, and describe a real case study, where 90 million AIS records, corresponding to one month of world-wide observations, are visualized using only open-source software.