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Trend in fishing activity in the open South China Sea estimated from remote sensing of the lights used at night by fishing vessels

文献类型: 外文期刊

作者: Li, Jiajun 1 ; Qiu, Yongsong 1 ; Cai, Yancong 1 ; Zhang, Kui 1 ; Zhang, Peng 1 ; Jing, Zhiyou 3 ; Wu, Qiaer 1 ; Ma, Shengwei 1 ; Liu, Huaxue 1 ; Chen, Zuozhi 1 ;

作者机构: 1.Chinese Acad Fishery Sci, South China Sea Fisheries Res Inst, Guangzhou 510300, Peoples R China

2.Minist Agr & Rural Affairs, Key Lab Open Sea Fishery Dev, Guangzhou 510300, Peoples R China

3.Chinese Acad Sci, South China Sea Inst Oceanol, State Key Lab Trop Oceanog, Guangzhou 510301, Peoples R China

4.Southern Marine Sci & Engn Guangdong Lab, Guangzhou 511458, Peoples R China

关键词: light fishing; nighttime light remote sensing; South China Sea; trend; VIIRS

期刊名称:ICES JOURNAL OF MARINE SCIENCE ( 影响因子:3.906; 五年影响因子:4.198 )

ISSN: 1054-3139

年卷期: 2022 年 79 卷 1 期

页码:

收录情况: SCI

摘要: With the progression of overfishing along the coast, oceanic fisheries in the South China Sea have attracted increasing attention from bordering countries. Fishing with lights has developed rapidly over the past decade. In this study, we analysed the trend in fishing over the spring fishing season (March-April) from 2012 to 2020 in the open-SCS fishing zone based on nightly satellite. The results indicated that the number of fishing boats detected by satellites were apparently influenced by the phases of the moon. Using data from moonless nights, we estimated that the number of fishing boats increased from similar to 400 to similar to 2000 over the past decade. These fishing craft in the open-SCS could be classified into large falling net vessels with bright lights and tuna fishing boats with dim lights. The nightly images of large falling net vessels were studied further using records from a typical commercial fishing vessel and, on this basis, we established an algorithm to extract data for this type of craft, whose numbers were estimated to have increased from similar to 20 to similar to 200 over the past decade. Using this algorithm, we were able to trace the development of these fleets and map out their distribution patterns in the open-SCS.

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