Marine environmental monitoring with unmanned vehicle platforms: Present applications and future prospects

被引:117
作者
Yuan, Shuyun [1 ,2 ]
Li, Ying [2 ,3 ,4 ]
Bao, Fangwen [2 ]
Xu, Haoxiang [3 ]
Yang, Yuping [3 ]
Yan, Qiushi [3 ]
Zhong, Shuqiao [3 ]
Yin, Haoyang [3 ]
Xu, Jiajun [3 ]
Huang, Ziwei [3 ]
Lin, Jian [3 ]
机构
[1] Harbin Inst Technol, Sch Environm, Harbin 150059, Peoples R China
[2] Southern Univ Sci & Technol, Ctr Ocean & Atmospher Sci SUSTech COAST, Shenzhen, Peoples R China
[3] Southern Univ Sci & Technol, Dept Ocean Sci & Engn, Shenzhen, Peoples R China
[4] Southern Marine Sci & Engn Guangdong Lab Guangzhou, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Unmanned aerial vehicle; Remote sensing; Glider; Unmanned surface vehicle; Unmanned ship; Marine environmental monitoring; Ocean observation system; OIL-SPILL DETECTION; AERIAL VEHICLES; COASTAL WATERS; ALGAL BLOOMS; OCEAN ACIDIFICATION; VERTICAL PROFILES; PLASTIC DEBRIS; INDIAN-OCEAN; UAV; SAR;
D O I
10.1016/j.scitotenv.2022.159741
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Basic monitoring of the marine environment is crucial for the early warning and assessment of marine hydrometeoro-logical conditions, climate change, and ecosystem disasters. In recent years, many marine environmental monitoring platforms have been established, such as offshore platforms, ships, or sensors placed on specially designed buoys or submerged marine structures. These platforms typically use a variety of sensors to provide high-quality observations, while they are limited by low spatial resolution and high cost during data acquisition. Satellite remote sensing allows monitoring over a larger ocean area; however, it is susceptible to cloud contamination and atmospheric effects that subject the results to large uncertainties. Unmanned vehicles have become more widely used as platforms in marine science and ocean engineering in recent years due to their ease of deployment, mobility, and the low cost involved in data acquisition. Researchers can acquire data according to their schedules and convenience, offering significant im-provements over those obtained by traditional platforms. This study presents the state-of-the-art research on available unmanned vehicle observation platforms, including unmanned aerial vehicles (UAVs), underwater gliders (UGs), un-manned surface vehicles (USVs), and unmanned ships (USs), for marine environmental monitoring, and compares them with satellite remote sensing. The recent applications in marine environments have focused on marine biochem-ical and ecosystem features, marine physical features, marine pollution, and marine aerosols monitoring, and their in-tegration with other products are also analysed. Additionally, the prospects of future ocean observation systems combining unmanned vehicle platforms (UVPs), global and regional autonomous platform networks, and remote sens-ing data are discussed.
引用
收藏
页数:15
相关论文
共 183 条
[1]   Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows [J].
Aasen, Helge ;
Honkavaara, Eija ;
Lucieer, Arko ;
Zarco-Tejada, Pablo J. .
REMOTE SENSING, 2018, 10 (07)
[2]   Mapping Invasive Phragmites australis in the Old Woman Creek Estuary Using UAV Remote Sensing and Machine Learning Classifiers [J].
Abeysinghe, Tharindu ;
Milas, Anita Simic ;
Arend, Kristin ;
Hohman, Breann ;
Reil, Patrick ;
Gregory, Andrew ;
Vazquez-Ortega, Angelica .
REMOTE SENSING, 2019, 11 (11)
[3]   The Potentiality of Operational Mapping of Oil Pollution in the Mediterranean Sea near the Entrance of the Suez Canal Using Sentinel-1 SAR Data [J].
Abou El-Magd, Islam ;
Zakzouk, Mohamed ;
Abdulaziz, Abdulaziz M. ;
Ali, Elham M. .
REMOTE SENSING, 2020, 12 (08)
[4]   Detecting the red tide algal blooms from satellite ocean color observations in optically complex Northeast-Asia Coastal waters [J].
Ahn, Yu-Hwan ;
Shanmugam, Palanisamy .
REMOTE SENSING OF ENVIRONMENT, 2006, 103 (04) :419-437
[5]   Determining Shoreline Response to Meteo-oceanographic Events Using Remote Sensing and Unmanned Aerial Vehicle (UAV): Case Study in Southern Brazil [J].
Albuquerque, Miguel da G. ;
Leal Alves, Deivid C. ;
de A. Espinoza, Jean M. ;
Oliveira, Ulisses R. ;
Simoes, Rodrigo S. .
JOURNAL OF COASTAL RESEARCH, 2018, :766-770
[6]   Equity of our future oceans: practices and outcomes in marine science research [J].
Alexander, K. A. ;
Fleming, A. ;
Bax, N. ;
Garcia, C. ;
Jansen, J. ;
Maxwell, K. H. ;
Melbourne-Thomas, J. ;
Mustonen, T. ;
Pecl, G. T. ;
Shaw, J. ;
Syme, G. ;
Ogier, E. .
REVIEWS IN FISH BIOLOGY AND FISHERIES, 2022, 32 (01) :297-311
[7]   Seasonal and interannual variability of particulate organic carbon within the Southern Ocean from satellite ocean color observations [J].
Allison, David B. ;
Stramski, Dariusz ;
Mitchell, B. Greg .
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS, 2010, 115
[8]   Oil spill detection by imaging radars: Challenges and pitfalls [J].
Alpers, Werner ;
Holt, Benjamin ;
Zeng, Kan .
REMOTE SENSING OF ENVIRONMENT, 2017, 201 :133-147
[9]   Hyperspectral and Radar Airborne Imagery over Controlled Release of Oil at Sea [J].
Angelliaume, Sebastien ;
Ceamanos, Xavier ;
Viallefont-Robinet, Francoise ;
Baque, Remi ;
Deliot, Philippe ;
Miegebielle, Veronique .
SENSORS, 2017, 17 (08)
[10]   Responses of marine ecosystems to climate change impacts and their treatment in biogeochemical ecosystem models [J].
Ani, Chinenye J. ;
Robson, Barbara .
MARINE POLLUTION BULLETIN, 2021, 166