Spatiotemporal Analysis of Light Purse Seine Fishing Vessel Operations in the Arabian High Seas Based on Automatic Identification System Data
文献类型： 外文期刊
作者： Yang, Shenglong 1 ; Yu, Linlin 1 ; Jiang, Keji 1 ; Fan, Xiumei 4 ; Wan, Lijun 5 ; Fan, Wei 1 ; Zhang, Heng 1 ;
作者机构： 1.Chinese Acad Fishery Sci, East China Sea Fisheries Res Inst, Key Lab Fisheries Remote Sensing, Minist Agr & Rural Affairs, Shanghai 200090, Peoples R China
2.Laoshan Lab, Qingdao 266237, Peoples R China
3.Shanghai Ocean Univ, Coll Informat, Shanghai 201306, Peoples R China
4.Chinese Acad Fishery Sci, Key & Open Lab Remote Sensing Informat Technol Fis, Shanghai 200090, Peoples R China
5.Dalian Ocean Univ, Sch Nav & Naval Architecture, Dalian 116023, Peoples R China
关键词： AIS data; light purse seining; fishing effort; spatiotemporal distribution characteristics; Arabian High Seas
期刊名称：APPLIED SCIENCES-BASEL （ 影响因子：2.5； 五年影响因子：2.7 ）
ISSN：
年卷期： 2024 年 14 卷 22 期
页码：
收录情况： SCI
摘要： Understanding the dynamic spatial distribution and characteristics of fishing activities is crucial for fisheries management and sustainable development. In recent years, small pelagic fish and cephalopods in the Arabian Sea have become new targets for light purse seine fishing; however, there is a lack of publicly available reports. This study uses automatic identification system (AIS) data from January to May and October to December of 2021 to 2022 in the region between 58 degrees-70 degrees E and 10 degrees-22 degrees N to extract spatial distribution information through three methods. The results show that with a spatial resolution of 0.25 degrees x 0.25 degrees, the spatial similarity index between the fishing ground information extracted in 2022 and catch data was consistently above 0.60, reaching 0.76 in March 2021 and 0.79 in November 2022, while the spatial similarity index in March 2022 exceeded 0.71. The spatial distribution of fishing effort and kernel density was similar to that of the fishing grounds, and the fishing intensity information exhibited the highest spatiotemporal similarity with commercial catch data, making it more suitable as a substitute for fishery data. Therefore, effective international cooperation and efficient joint management mechanisms for fishing vessels are needed to enhance the regulatory oversight of fishing vessels in this region. Integrating AIS data with other technological methods is crucial for more effective monitoring and management of fishing vessels. The findings presented in this paper provide both quantitative and qualitative scientific support for resource conservation and sustainable development in the region.
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