The fishing grounds and frequency of appearance of Chinese fishing vessels obtained by analyzing AIS data in the south coast of Jeju Island

Kim, Kwang-Il; heon, lee chang; Young, Ahn Jang

doi:10.3796/ksfot.2019.55.4.356

Cited by 1 publication

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“…Although the spatial and temporal monitoring of vessel activity and the analyses of fishing effort intensities on marine ecosystems have been enhanced by VMS data globally [13], it is difficult to access the data due to confidentiality and concerns related to data protection [14]. The difficulties regarding VMS data in terms of identifying fishing activity and gear type are due to the long intervals of vessel trajectory data [15], leading to AIS data, which is characterized by high persistence, being a better choice [8]. The availability of satellite AIS (S-AIS) data from a growing number of satellite-based data providers [16] has made it readily available for fisheries resource assessments.…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Fish Catch Assessments Using Fishing Vessel Trajectories and Coastal Fish Landing Data from around Jeju Island

Owiredu

Kim

2021

Sustainability

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While pressure on marine ecosystems leading to declines in global fish catches have been attributed to excessive fishing and to unregulated and unreported fishing, existing management practices have yet to fully address these declines. Estimation of spatial and temporal distribution of fisheries resources and the extent of fishing impacts on marine ecosystems using vessel trajectories has become central in recent studies. This study proposed the use of trajectories of 771 Korean coastal and offshore fishing vessels and one-year fish landing data to estimate variations in commercial fish species, vessel, and fishing gear activity distributions in the waters around Jeju island. A set of standards were applied to identify individual fishing tracks of major gears and uniformly distributed catch to fishing segments of trajectories to produce spatio-temporal distributions of catch, fishing activities, and vessel reliance on fishing grounds at a fine spatial scale. The method identified reference points that can inform management at local and regional scales. We discuss the opportunities of combining larger datasets collected over a longer period and applying predictive modeling techniques in making extensive assessments, including climate change impacts on fishing activities that can inform resource management and marine spatial planning.

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