Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data
Li, Jie1,2,3; Xing, Qianguo1,2,3; Li, Xuerong1; Arif, Maham1,2,3; Li, Jinghu1,2,3
发表期刊SENSORS
2024-02-01
卷号24期号:3页码:19
关键词automatic identification system (AIS) fishing vessels spatial-temporal distribution northern Indian Ocean sea surface temperature (SST) chlorophyll a concentration (Chl-a)
DOI10.3390/s24030781
通讯作者Xing, Qianguo([email protected])
英文摘要Satellite-derived Sea Surface Temperature (SST) and sea-surface Chlorophyll a concentration (Chl-a), along with Automatic Identification System (AIS) data of fishing vessels, were used in the examination of the correlation between fishing operations and oceanographic factors within the northern Indian Ocean from March 2020 to February 2023. Frequency analysis and the empirical cumulative distribution function (ECDF) were used to calculate the optimum ranges of two oceanographic factors for fishing operations. The results revealed a substantial influence of the northeast and southwest monsoons significantly impacting fishing operations in the northern Indian Ocean, with extensive and active operations during the period from October to March and a notable reduction from April to September. Spatially, fishing vessels were mainly concentrated between 20 degrees N and 6 degrees S, extending from west of 90 degrees E to the eastern coast of Africa. Observable seasonal variations in the distribution of fishing vessels were observed in the central and southeastern Arabian Sea, along with its adjacent high sea of the Indian Ocean. Concerning the marine environment, it was observed that during the northeast monsoon, the suitable SST contributed to high CPUEs in fishing operation areas. Fishing vessels were widely distributed in the areas with both mid-range and low-range Chl-a concentrations, with a small part distributed in high-concentration areas. Moreover, the monthly numbers of fishing vessels showed seasonal fluctuations between March 2020 and February 2023, displaying a periodic pattern with an overall increasing trend. The total number of fishing vessels decreased due to the impact of the COVID-19 pandemic in 2020, but this was followed by a gradual recovery in the subsequent two years. For fishing operations in the northern Indian Ocean, the optimum ranges for SST and Chl-a concentration were 27.96 to 29.47 degrees C and 0.03 to 1.81 mg/m3, respectively. The preliminary findings of this study revealed the spatial-temporal distribution characteristics of fishing vessels in the northern Indian Ocean and the suitable ranges of SST and Chl-a concentration for fishing operations. These results can serve as theoretical references for the production and resource management of off-shore fishing operations in the northern Indian Ocean.
资助机构Chinese Academy of Science
收录类别SCI
语种英语
关键词[WOS]SEA-SURFACE TEMPERATURE ; ARABIAN SEA ; WEST-COAST ; AIS DATA ; FISHERIES ; TRACKING ; VARIABILITY ; FOOTPRINT ; GROUNDS
研究领域[WOS]Chemistry ; Engineering ; Instruments & Instrumentation
WOS记录号WOS:001160361100001
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.yic.ac.cn/handle/133337/36333
专题中国科学院海岸带环境过程与生态修复重点实验室
中国科学院海岸带环境过程与生态修复重点实验室_海岸带信息集成与战略规划研究中心
通讯作者Xing, Qianguo
作者单位1.Chinese Acad Sci, Yantai Inst Coastal Zone Res, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Yantai 264003, Peoples R China
2.Shandong Key Lab Coastal Environm Proc, Yantai 264003, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Li, Jie,Xing, Qianguo,Li, Xuerong,et al. Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data[J]. SENSORS,2024,24(3):19.
APA Li, Jie,Xing, Qianguo,Li, Xuerong,Arif, Maham,&Li, Jinghu.(2024).Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data.SENSORS,24(3),19.
MLA Li, Jie,et al."Monitoring Off-Shore Fishing in the Northern Indian Ocean Based on Satellite Automatic Identification System and Remote Sensing Data".SENSORS 24.3(2024):19.
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