Skip to main content
SpringerLink
Log in

Validation of MODIS ocean-colour products in the coastal waters of the Yellow Sea and East China Sea

  • Published:
Acta Oceanologica Sinica Aims and scope Submit manuscript

Abstract

An extensive study collected in situ data along the Yellow Sea (YS) and East China Sea (ECS) to assess the radiometric properties and the concentration of the water constituents derived from Moderate Resolution Imaging Spectroradiometer (MODIS). Thirteen high quality match-ups were obtained for evaluating the MODIS estimates of Rrs(λ), chlorophyll a (Chi a) and concentrations of suspended particulate sediment matter (SPM). For MODIS Rrs(λ), the mean absolute percentage difference (APD) was in the range of 20%-36%, and the highest uncertainty appeared at 412 nm, whereas the band ratio of Rrs(λ) at 488 nm compared with that at 547 nm was highly consistent, with an APD of 7%. A combination of near-infrared bands and shortwave infrared wavelengths atmosphere correction algorithm (NIR-SWIR algorithm) was applied to the MODIS data, and the estimation accuracy of RIS were improved at most of the visible spectral bands except 645 nm, 667 nm and 678 nm. Two ocean-colour empirical algorithms for Chi a estimation were applied to the processed data, the results indicated that the accuracy of the derived Chi a values was obviously improved, the four-band algorithms outperformed the other algorithm for measured and simulated datasets, and the minimum APD was 35%. The SPM was also quantified. Two regional and two coastal SPM algorithms were modified according to the in situ data. By comparison, the modified Tassan model had a higher accuracy for the application along the YS and ECS with an APD of 21%. However, given the limited match-up dataset and the potential influence of the aerosol properties on atmosphere correction, further research is required to develop additional algorithms especially for the low Chi a coastal water.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Bailey W S, Werdell J P. 2006. A multi-sensor approach for the on-or-bit validation of ocean color satellite data products. Remote Sensing of Environment, 102: 12–23, doi: https://doi.org/10.1016/j.rse.2006.01.015

    Google Scholar 

  • Bailey S W, Franz B A, Werdell P J. 2010. Estimation of near-infrared water-leaving reflectance for satellite ocean color data processing. Optics Express, 18(7): 7521–7527, doi: https://doi.org/10.1364/OE.18.007521

    Google Scholar 

  • Bian Changwei, Jiang Wensheng, Quan Qi, et al. 2013. Distributions of suspended sediment concentration in the Yellow Sea and the East China Sea based on field surveys during the four seasons of 2011. Journal of Marine Systems, 121-122(5): 24–35

    Google Scholar 

  • Carder K L, Chen F R, Cannizzaro J P, et al. 2004. Performance of the MODIS semi-analytical ocean color algorithm for chlorophyll-a. Advances in Space Research, 33(7): 1152–1159, doi: https://doi.org/10.1016/S0273-1177(03)00365-X

    Google Scholar 

  • Carswell T, Costa M, Young E, et al. 2017. Evaluation of MODIS-aqua atmospheric correction and chlorophyll products of western North American coastal waters based on 13 years of data. Remote Sensing, 9(10): 63–88

    Google Scholar 

  • Chen Shuguo, Zhang Tinglu, Hu Lianbo. 2015. Evaluation of the NIR-SWIR atmospheric correction algorithm for MODIS-Aqua over the Eastern China Seas. International Journal of Remote Sensing, 35(11-12): 4239–4251

    Google Scholar 

  • Cheng Chunmei, Wei Yuchun, Xu Jianjun, et al. 2013. Remote sensing estimation of Chlorophyll a and suspended sediment concentration in turbid water based on spectral separation. Optik, 124(24): 6815–6819, doi: https://doi.org/10.1016/j.ijleo.2013.05.078

    Google Scholar 

  • Cui Tingwei, Zhang Jie, Groom S, et al. 2010. Validation of MERIS ocean-color products in the Bohai Sea: A case study for turbid coastal waters. Remote Sensing of Environment, 114(10): 2326–2336, doi: https://doi.org/10.1016/j.rse.2010.05.009

    Google Scholar 

  • Cui Tingwei, Zhang Jie, Tang Junwu, et al. 2014. Assessment of satellite ocean color products of MERIS, MODIS and SeaWiFS along the East China Coast (in the Yellow Sea and East China Sea). IS-PRS Journal of Photogrammetry and Remote Sensing, 87: 137–151, doi: https://doi.org/10.1016/j.isprsjprs.2013.10.013

    Google Scholar 

  • Dall’Olmo G, Gitelson A, Rundquist D C, et al. 2005. Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands. Remote Sensing of Environment, 96(2): 176–187, doi: https://doi.org/10.1016/j.rse.2005.02.007

    Google Scholar 

  • Dall’Olmo G, Gitelson A. 2006. Effect of bio-optical parameter variability and uncertainties in reflectance measurements on the remote estimation of chlorophyll-a concentration in turbid productive waters: Modeling results. Applied Optics, 45(15): 3577–3592, doi: https://doi.org/10.1364/AO.45.003577

    Google Scholar 

  • Darecki M, Stramski D. 2004. An evaluation of MODIS and SeaWiFS bio-optical algorithms in the Baltic Sea. Remote Sensing of Environment, 89(3): 326–350, doi: https://doi.org/10.1016/j.rse.2003.10.012

    Google Scholar 

  • Doxaran D, Cherukuru N, Lavender S J. 2006. Apparent and inherent optical properties of turbid estuarine waters: measurements, empirical quantification relationships, and modeling. Applied Optics, 45(10): 2310–2324, doi: https://doi.org/10.1364/AO.45.002310

    Google Scholar 

  • D’Sa E J, Miller R L, McKee B A. 2007. Suspended particulate matter dynamics in coastal waters from ocean color: application to the northern Gulf of Mexico. Geophysical Research Letters, 34(23): L23611

    Google Scholar 

  • Gao Xuelu, Song Jinming. 2005. Phytoplankton distributions and their relationship with the environment in the Changjiang Estuary, China. Marine Pollution Bulletin, 50(3): 327–335, doi: https://doi.org/10.1016/j.marpolbul.2004.11.004

    Google Scholar 

  • Gilerson A A, Gitelson A A, Zhou Jing, et al. 2010. Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands. Optics Express, 18(23): 24109–24125, doi: https://doi.org/10.1364/OE.18.024109

    Google Scholar 

  • Gitelson A A, Dall’Olmo G, Moses W, et al. 2008. A simple semi-analytical model for remote estimation of chlorophyll-a in turbid waters: Validation. Remote Sensing of Environment, 112(9): 3582–3593, doi: https://doi.org/10.1016/j.rse.2008.04.015

    Google Scholar 

  • Gitelson A, Schalles J F, Hladik C M. 2007. Remote chlorophyll-a retrieval in turbid, productive estuaries: Chesapeake Bay case study. Remote Sensing of Environment, 109(4): 464–472, doi: https://doi.org/10.1016/j.rse.2007.01.016

    Google Scholar 

  • Gons H J, Rijkeboer M, Ruddick K G. 2002. A chlorophyll-retrieval algorithm for satellite imagery (medium resolution imaging spectrometer) of inland and coastal waters. Journal of Plankton Research, 24(9): 947–951, doi: https://doi.org/10.1093/plankt/24.9.947

    Google Scholar 

  • Gons H J, Rijkeboer M, Ruddick K G. 2005. Effect of a waveband shift on chlorophyll retrieval from MERIS imagery of inland and coastal waters. Journal of Plankton Research, 27(1): 125–127

    Google Scholar 

  • Han L, Rundquist D C, Liu L L, et al. 1994. The spectral responses of algal chlorophyll in water with varying levels of suspended sediment. International Journal of Remote Sensing, 15(18): 3707–3718, doi: https://doi.org/10.1080/01431169408954353

    Google Scholar 

  • He Qianshan, Li Chengcai, Tang Xu, et al. 2010. Validation of MODIS derived aerosol optical depth over the Yangtze River Delta in China. Remote Sensing of Environment, 114(8): 1649–1661, doi: https://doi.org/10.1016/j.rse.2010.02.015

    Google Scholar 

  • Kang Na, Kumar K R, Yu Xingna, et al. 2016. Column-integrated aerosol optical properties and direct radiative forcing over the urban-industrial megacity Nanjing in the Yangtze River Delta, China. Environmental Science and Pollution Research, 23(17): 17532–17552, doi: https://doi.org/10.1007/sll356-016-6953-1

    Google Scholar 

  • Knaeps E, Dogliotti A I, Raymaekers D, et al. 2012. In situ evidence of non-zero reflectance in the OLCI1020 nm band for a turbid estuary. Remote Sensing of Environment, 120: 133–144, doi: https://doi.org/10.1016/j.rse.2011.07.025

    Google Scholar 

  • Kuchinke C P, Gordon H R, Harding L W Jr, et al. 2009. Spectral optimization for constituent retrieval in Case 2 waters II: validation study in the Chesapeake Bay. Remote Sensing of Environment, 113(3): 610–621, doi: https://doi.org/10.1016/j.rse.2008.11.002

    Google Scholar 

  • Lee Z, Carder K L, Steward R G, et al. 1996. Protocols for measurement of remote sensing reflectance from clear to turbid waters. Presented at SeaWiFS Workshop. Halifax

    Google Scholar 

  • Li Shuangzhao, Yuan Dekui, Wang Xue. 2017. Improvement of SWIR atmospheric correction algorithm for case II water. Acta Scien-tiae Circumstantiae (in Chinese), 37(1): 104–111

    Google Scholar 

  • Menon H B, Lotliker A A, Moorthy K K, et al. 2006. Variability of remote sensing reflectance and implications for optical remote sensing-a study along the eastern and northeastern waters of Arabian Sea. Geophysical Research Letters, 33(15): L15602, doi: https://doi.org/10.1029/2006GL026026

    Google Scholar 

  • Mobley C D. 1999. Estimation of the remote-sensing reflectance from above-surface measurements. Applied Optics, 38(36): 7442–7455, doi: https://doi.org/10.1364/AO.38.007442

    Google Scholar 

  • Moses W J, Gitelson A A, Berdnikov S, et al. 2009. Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data-successes and challenges. Environmental Research Letters, 4(4): 045005, doi: https://doi.org/10.1088/1748-9326/4/4/045005

    Google Scholar 

  • Mueller J L, Fargion G S, Mc Clain C R. 2003. Ocean optics protocols for Satellite Ocean color sensor validation, revision 4, volume VI: Special topics in ocean optics protocols and appendices. Greenbelt, Maryland: Aeronautics and Space Administration of USA

    Google Scholar 

  • Prasad A K, Singh R P. 2007. Comparison of MISR-MODIS aerosol optical depth over the Indo-Gangetic basin during the winter and summer seasons (2000-2005). Remote Sensing of Environment, 107(1-2): 109–119, doi: https://doi.org/10.1016/j.rse.2006.09.026

    Google Scholar 

  • Salem S I, Higa H, Kim H, et al. 2017. Assessment of Chlorophyll-a algorithms considering different trophic statuses and optimal bands. Sensors, 17(8): 1746, doi: https://doi.org/10.3390/sl7081746

    Google Scholar 

  • Shen Fang, Yunxuan, Li Daoji, et al. 2010. Medium resolution imaging spectrometer (MERIS) estimation of chlorophyll-a concentration in the turbid sediment-laden waters of the Changjiang (Yangtze) Estuary. International Journal of Remote Sensing, 31(17-18): 4635–4650, doi: https://doi.org/10.1080/01431161.2010.485216

    Google Scholar 

  • Shi Wei, Wang Menghua. 2014. Ocean reflectance spectra at the red, near-infrared, and shortwave infrared from highly turbid waters: A study in the Bohai Sea, Yellow Sea, and East China Sea. Limnology and Oceanography, 59(2): 427–444, doi: https://doi.org/10.4319/10.2014.59.2.0427

    Google Scholar 

  • Sun Ling, Guo Maohua, Wang Xiaomei. 2010. Ocean color products retrieval and validation around China coast with MODIS. Acta Oceanologica Sinica, 29(4): 21–27, doi: https://doi.org/10.1007/sl3131-010-0047-6

    Google Scholar 

  • Tang Junwu, Tian Guoliang, Wang Xiaoyong, et al. 2004. The methods of water spectra measurement and analysis I: Above-water method. Journal of Remote Sensing (in Chinese), 8(1): 37–44

    Google Scholar 

  • Tassan S. 1993. An improved in-water algorithm for the determination of chlorophyll and suspended sediment concentration from Thematic Mapper data in coastal waters. International Journal of Remote Sensing, 14(6): 1221–1229, doi: https://doi.org/10.1080/01431169308904406

    Google Scholar 

  • Tilstone G H, Lotliker A A, Miller P I, et al. 2013. Assessment of MOD-IS-Aqua chlorophyll-a algorithms in coastal and shelf waters of the eastern Arabian Sea. Continental Shelf Research, 65: 14–26, doi: https://doi.org/10.1016/j.csr.2013.06.003

    Google Scholar 

  • Vanhellemont Q, Ruddick K G. 2015. Advantages of high quality SWIR bands for ocean colour processing: Examples from Land-sat-8. Remote Sensing of Environment, 161: 89–106, doi: https://doi.org/10.1016/j.rse.2015.02.007

    Google Scholar 

  • Wang Menghua, Shi Wei. 2007. The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. Optics Express, 15(24): 15722–15733, doi: https://doi.org/10.1364/OE.15.015722

    Google Scholar 

  • Wang Menghua, Son S, Shi Wei. 2009. Evaluation of MODIS SWIR and NIR-SWIR atmospheric correction algorithms using SeaBASS data. Remote Sensing of Environment, 113(3): 635–644, doi: https://doi.org/10.1016/j.rse.2008.11.005

    Google Scholar 

  • Wang Menghua, Shi Wei. 2012. Sensor noise effects of the SWIR bands on MODIS-derived ocean color products. IEEE Transactions on Geoscience and Remote Sensing, 50(9): 3280–3292, doi: https://doi.org/10.1109/TGRS.2012.2183376

    Google Scholar 

  • Wang Lin, Zhao Dongzhi, Yangjianhong, et al. 2012. Retrieval of total suspended matter from MODIS 250 m imagery in the Bohai Sea of China. Journal of Oceanography, 68(5): 719–725, doi: https://doi.org/10.1007/S10872-012-0129-5

    Google Scholar 

  • Wang Fujiang, Chen Ying, Meng Xi, et al. 2016. The contribution of anthropogenic sources to the aerosols over East China Sea. Atmospheric Environment, 127: 22–33, doi: https://doi.org/10.1016/j.atmosenv.2015.12.002

    Google Scholar 

  • Werdell P J, Franz B A, Bailey S W. 2010. Evaluation of shortwave infrared atmospheric correction for ocean color remote sensing of Chesapeake Bay. Remote Sensing of Environment, 114(10): 2238–2247, doi: https://doi.org/10.1016/j.rse.2010.04.027

    Google Scholar 

  • Xiao Yanfang, Zhang Jie, Cui Tingwei, et al. 2018. A new merged data-set of global ocean chlorophyll a concentration with higher spatial and temporal coverage. Acta Oceanologica Sinica, 37(7): 118–130, doi: https://doi.org/10.1007/sl3131-018-1249-6

    Google Scholar 

  • Xiong Xiaoxiong, Sun Junqiang, Barnes W, et al. 2007. Multiyear on-orbit calibration and performance of Terra MODIS reflective solar bands. IEEE Transactions on Geoscience and Remote Sensing, 45(4): 879–889, doi: https://doi.org/10.1109/TGRS.2006.890567

    Google Scholar 

  • Yacobi Y Z, Moses W J, Kaganovsky S, et al. 2011. NIR-red reflectance-based algorithms for chlorophyll-a estimation in mesotrophic inland and coastal waters: Lake Kinneret case study. Water Research, 45(7): 2428–2436, doi: https://doi.org/10.1016/j.watres.2011.02.002

    Google Scholar 

  • Zhang Minwei, Tang Junwu, Dong Qing, et al. 2010. Retrieval of total suspended matter concentration in the Yellow and East China Seas from MODIS imagery. Remote Sensing of Environment, 114(2): 392–403, doi: https://doi.org/10.1016/j.rse.2009.09.016

    Google Scholar 

  • Zibordi G, Berthon J F, Melin F, et al. 2009. Validation of satellite ocean color primary products at optically complex coastal sites: Northern Adriatic Sea, Northern Baltic Proper and Gulf of Finland. Remote Sensing of Environment, 113(12): 2574–2591, doi: https://doi.org/10.1016/j.rse.2009.07.013

    Google Scholar 

  • Zibordi G, Melin F, Berthon J F. 2006. Comparison of SeaWiFS, MOD-IS and MERIS radiometric products at a coastal site. Geophysical Research Letters, 33(6): L06617

    Google Scholar 

Download references

Acknowledgements

This work was initiated when Lingling Jiang visited Plymouth Marine Laboratory funded by Dalian Maritime University and got many help from team members there for data processing. We thank all crew members on the cruises for their hard work in collecting and analyzing the in situ data. We also thank the NASA for their help with providing MODIS data.

Author information

Authors and Affiliations

  1. College of Environmental Science and Engineering, Dalian Maritime University, Dalian, 116026, China

    Lingling Jiang & Xiangyu Guo

  2. Ministry of Ecology Environment, National Marine Environmental Monitoring Center, Dalian, 116023, China

    Lin Wang, Yanlong Chen & Bingnan Li

  3. Plymouth Marine Laboratory (PML), Plymouth, Devon, PL1 3DH, UK

    Shubha Sathyendranath & Hayley Evers-King

Authors
  1. Lingling Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiangyu Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Lin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shubha Sathyendranath
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hayley Evers-King
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yanlong Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Bingnan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lingling Jiang.

Additional information

Foundation item: The National Natural Science Foundation of China under contract Nos 41506197 and 41406199; the Doctoral Scientific Research Foundation of Liaoning Province under contract No. 201501190; the Fundamental Research Funds for the Central Universities under contract No. 3132017110.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jiang, L., Guo, X., Wang, L. et al. Validation of MODIS ocean-colour products in the coastal waters of the Yellow Sea and East China Sea. Acta Oceanol. Sin. 39, 91–101 (2020). https://doi.org/10.1007/s13131-019-1522-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13131-019-1522-3

Keywords

Search

Navigation