SCSIO OpenIR  > 热带海洋环境国家重点实验室(LTO)
Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea
Hu, SB; Zhou, W; Wang, GF; Cao, WX; Xu, ZT; Liu, HZ; Wu, GF; Zhao, WJ; hsb514@163.com; wenzhou@scsio.ac.cn; guifenwang@scsio.ac.cn; wxcao@scsio.ac.cn; xuzhantang@scsio.ac.cn; HuizengLiu@life.hkbu.edu.hk; guofeng.wu@szu.edu.cn; wenjing-jingjing@163.com
2018
Source PublicationREMOTE SENSING
Volume10Issue:4Pages:-526
AbstractOcean colour remote sensing is used as a tool to detect phytoplankton size classes (PSCs). In this study, the Medium Resolution Imaging Spectrometer (MERIS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Sea-viewing Wide Field-of-view Sensor (SeaWiFS) phytoplankton size classes (PSCs) products were compared with in-situ High Performance Liquid Chromatography (HPLC) data for the South China Sea (SCS), collected from August 2006 to September 2011. Four algorithms were evaluated to determine their ability to detect three phytoplankton size classes. Chlorophyll-a (Chl-a) and absorption spectra of phytoplankton (aph(A)) were also measured to help understand PSC's algorithm performance. Results show that the three abundance-based approaches performed better than the inherent optical property (IOP)-based approach in the SCS. The size detection of microplankton and picoplankton was generally better than that of nanoplankton. A three-component model was recommended to produce maps of surface PSCs in the SCS. For the IOP-based approach, satellite retrievals of inherent optical properties and the PSCs algorithm both have impacts on inversion accuracy. However, for abundance-based approaches, the selection of the PSCs algorithm seems to be more critical, owing to low uncertainty in satellite Chl-a input data
Department[Hu, Shuibo; Liu, Huizeng; Wu, Guofeng] Shenzhen Univ, Key Lab Geoenvironm Monitoring Coastal Zone, Natl Adm Surveying Mapping & GeoInformat, Shenzhen 518060, Peoples R China; [Hu, Shuibo; Liu, Huizeng; Wu, Guofeng] Shenzhen Univ, Shenzhen Key Lab Spatial Smart Sensing & Serv, Shenzhen 518060, Peoples R China; [Hu, Shuibo; Wu, Guofeng] Shenzhen Univ, Coll Life Sci & Oceanog, Shenzhen 518060, Peoples R China; [Zhou, Wen; Cao, Wenxi; Xu, Zhantang] Chinese Acad Sci, State Key Lab Trop Oceanog, South China Sea Inst Oceanol, Guangzhou 510301, Guangdong, Peoples R China; [Wang, Guifen] Hohai Univ, Coll Oceanog, Nanjing 210098, Jiangsu, Peoples R China; [Liu, Huizeng] Hong Kong Baptist Univ, Dept Geog, Kowloon, Hong Kong, Peoples R China; [Zhao, Wenjing] Minist Environm Protect RPC, South China Inst Environm Sci, Guangzhou 510535, Peoples R China
KeywordPhytoplankton Size Classes (Pscs) Comparison South China Sea Ocean Colour Remote Sensing
Subject AreaRemote Sensing
Funding ProjectLTO
Document Type期刊论文
Identifierhttp://ir.scsio.ac.cn/handle/344004/17078
Collection热带海洋环境国家重点实验室(LTO)
Corresponding Authorhsb514@163.com; wenzhou@scsio.ac.cn; guifenwang@scsio.ac.cn; wxcao@scsio.ac.cn; xuzhantang@scsio.ac.cn; HuizengLiu@life.hkbu.edu.hk; guofeng.wu@szu.edu.cn; wenjing-jingjing@163.com
Recommended Citation
GB/T 7714
Hu, SB,Zhou, W,Wang, GF,et al. Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea[J]. REMOTE SENSING,2018,10(4):-526.
APA Hu, SB.,Zhou, W.,Wang, GF.,Cao, WX.,Xu, ZT.,...&wenjing-jingjing@163.com.(2018).Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea.REMOTE SENSING,10(4),-526.
MLA Hu, SB,et al."Comparison of Satellite-Derived Phytoplankton Size Classes Using In-Situ Measurements in the South China Sea".REMOTE SENSING 10.4(2018):-526.
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