Journal of Geo-information Science >
Mapping Method of Fishing Grounds based on Marine AIS Data
Received date: 2021-03-04
Request revised date: 2021-04-09
Online published: 2022-02-25
Supported by
TheNational Key R&D Program of China(2019YFD0900705)
Shandong Provincial Natural Science Foundation(ZR2020MD014)
Copyright
Automatic Identification System (AIS) is a ship-to-ship and ship-to-shore system used for ship monitoring. It can automatically and continuously broadcast static and dynamic information about the vessel's position and movement, as well as voyage-related information. More and more research suggests that AIS is not only an effective tool for maritime traffic supervision, but also a good data source for the study of maritime traffic and its related industrial activities. In China, the application of AIS equipment is relatively late. The research based on AIS data mainly focuses on the maritime traffic safety management, such as vessel collision avoidance and traffic flow statistics, while there are few reports in the fishery field. In order to provide technical support for the protection and recovery of inshore fishery resources in China, it is urgent to excavate the information value of AIS data and carry out the research on the spatiotemporal pattern of inshore fishing activities based on AIS data. Therefore, based on AIS data of fishing vessels at sea, this study used the Gaussian Mixed Model (GMM) to identify fishing behavior of fishing vessels and determine the speed threshold of fishing vessels in fishing activities. This study proposed a method combining Kernel Density Estimation (KDE) and Hot Spot Analysis (HSA) to map fishing grounds. The results show that, firstly, compared with single KDE or HSA method, the combination method combined the distance attenuation effect of KDE with quantitative statistical index of HSA, which can not only avoid the problem of range definition of fishing grounds in the KDE process, but also improve the efficiency of data analysis in the HSA process and the scattered distribution effect of fishing grounds in the extraction results of the HSA. The combination method had better application effects and higher efficiency in the mapping of fishing grounds. It provided a quick and simple evaluation method for the rapid acquisition of marine fishing information and the effectiveness evaluation of fishery resources protection and management measures. Secondly, based on the AIS data from September to December 2018, the combination method was used to map the spatiotemporal distribution of fishing grounds around the Bohai Strait. The study found that the fishing grounds around the Bohai Strait were mainly distributed in the inshore areas of Yanwei and the Bohai Strait. The distribution range of concentrated fishing activities in traditional fishing grounds of the Bohai Sea is relatively small, and the distribution range and spatial morphological characteristics of fishing grounds had some variabilities in different months. The results can provide technical methods and decision support for fishing management and marine ecological protection around the Bohai Strait.
CHEN Renli , WU Xiaoqing , LIU Baijing , WANG Yueqi , GAO Meng . Mapping Method of Fishing Grounds based on Marine AIS Data[J]. Journal of Geo-information Science, 2021 , 23(12) : 2163 -2173 . DOI: 10.12082/dqxxkx.2021.210106
表1 渔船捕捞活动聚集区不同方法提取结果统计Tab. 1 Statistics of fishing grounds by different methods |
提取方法 | 总区块数量/个 | 总区块面积/km2 | 大于10 km2区块数量/个 | 大于10 km2区块面积/km2 |
---|---|---|---|---|
KDE | 65 | 22 421.95 | 49 | 22 357.82 |
IHSA | 197 | 5048.25 | 37 | 4680.38 |
FHSA | 37 | 20 610.85 | 29 | 20 591.98 |
KDHSA | 33 | 15 771.57 | 27 | 15 749.61 |
图5 2018年9—12月渤海海峡周边海域渔船捕捞活动聚集区分布Fig. 5 Distribution of fishing grounds around the Bohai Strait from September to December 2018 |
图6 2018年9—12月渔船捕捞活动聚集区与海表Chl-a浓度分布叠加图Fig. 6 Distribution of fishing grounds and the concentration of Chl-a on the sea surface from September to December 2018 |
表2 2018年9—12月捕捞活动聚集区基本特征统计Tab. 2 Statistics of basic characteristics of fishing grounds from September to December 2018 |
9月 | 10月 | 11月 | 12月 | |
---|---|---|---|---|
区块面积/km2 | 15 749.61 | 13 856.57 | 13 610.92 | 8686 |
区块数量/个 | 27 | 26 | 22 | 29 |
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