Journal of Geo-information Science ›› 2021, Vol. 23 ›› Issue (5): 850-859.doi: 10.12082/dqxxkx.2021.200328

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Spatial Characteristics Mining of Fishing Intensity in the Northern South China Sea based on Fishing Vessels AIS Data

LI Xiaoen1,3,4(), ZHOU Liang1,3,5, XIAO Yang2,3,6, WU Wenzhou3, SU Fenzhen3,6,7,*(), SHI Wei3   

  1. 1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
    2. School of Geography and Ocean Science, Nanjing University, Nanjing 210023, China
    3. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    4. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
    5. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
    6. Collaborative Innovation Center of South China Sea Studies, Nanjing University, Nanjing 210093, China
    7. Innovation Academy of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences, Guangzhou 510301, China
  • Received:2020-06-24 Revised:2020-09-14 Online:2021-05-25 Published:2021-07-25
  • Contact: SU Fenzhen;
  • Supported by:
    Science and Technology Basic Resources Investigation Program of China(2017FY201401);National Natural Science Foundation of China(41890854);Innovation Academy of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences(ISEE2018YB06);National Natural Science Foundation of China(41961027);Lanzhou Jiaotong University Excellent Platform LZJTU EP(201806)


High-precision fishing intensity data in the fishery is the prerequisite and key to carrying out fishing quota management, as well as the significant guarantee for the sustainable development of marine fishery resources. Therefore, the paper selects 180 million records of high spatiotemporal multi-granularity data of 6364 fishing vessels with Chinese nationality in typical seasons including February, April, September, and November of 2018, aiming to mine the spatial characteristics of the fishing intensity in marine fishery. It leverages expert knowledge and experience and employs spatial statistics and data mining analysis methods to conduct a thorough mining and analysis of the spatial characteristics of the fishing intensity. We take Beibu Gulf fisheries on the coast of Guangxi, the coast of Guangdong, and the surrounding sea areas of the Hainan Island as the study areas. The results show that: (1) The high-intensity fishing in coastal waters of Guangdong and Guangxi (referred to as "Liang Guang") mainly presents the characteristics of "clumps" expanding outward and converging into "bands" or "larger clumps", while the surrounding area of Hainan island mainly presents the characteristics of "clumps"; (2) Influenced by fishery workers, the number of fishing vessels, marine fisheries, and marine environment, the fishing intensity in the coastal waters of "Liang Guang" is apparently higher than that of the surrounding waters of Hainan Island; (3) The high-intensity fishing area is mainly concentrated within 30~50 km near the shore, and the intensity of offshore fishing is higher than that of the far-sea area, which is attributed to the high proportion (up to 50.9%) of small and medium-sized fishing vessels in the study area; (4) Fishing activities are affected by the traditional Lunar New Year, the fishing moratorium, and other policy factors, thus the fishing intensity during the Spring Festival being the lowest in the selected data coverage time range. In addition, the fishing intensity after the fishing moratorium (September) is significantly higher than that before the fishing moratorium (April); (5) The large fishing ports near the coast of the study area have a certain radiation-driven effect on the high-intensity fishing in the coastal waters. This study can provide important data support for the analysis of the fishing intensity of offshore marine fisheries and contribute to the sustainable development of the marine fishery, by processing, analyzing, and deeply mining AIS data with high spatiotemporal multi-granularity.

Key words: fishing vessels AIS data, big data, Northern South China Sea fishery, data analysis and mining, Gaussian mixture model, fishing intensity, spatial characteristics analysis, sustainable marine fisheries