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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

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Front. Earth Sci.    2020, Vol. 14 Issue (2) : 384-400    https://doi.org/10.1007/s11707-019-0777-5
RESEARCH ARTICLE
An ultraviolet to visible scheme to estimate chromophoric dissolved organic matter absorption in a Case-2 water from remote sensing reflectance
Xia LEI1, Jiayi PAN2(), Adam DEVLIN2
1. Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
2. School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China
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Abstract

In a typical Case-2 coastal water environment (here, the Pearl River Estuary (PRE), China), chromophoric dissolved organic matter (CDOM) and suspended particulates dominate the water optical properties, and CDOM fluorescence contributes considerably to surface water reflectance. In this paper, an ultraviolet (UV) to visible scheme to retrieve CDOM absorption (ag) is developed based on a set of in situ observations. First, the CDOM UV absorption and spectral slope (Sg) are derived directly from the visible remote sensing reflectance; then the Sg is extrapolated to obtain the spectrum from UV to visible spectral range. This algorithm performs well, with an overall mean absolute percent difference (MAPD) of ~30%, ~5% and ~6% for the estimation of ag in 250–450 nm, Sg over 250–400 nm, and 250–700 nm, respectively. The effectiveness and stability of the algorithm is further demonstrated in capturing the distribution pattern of CDOM absorption in the PRE from satellite ocean color imagery with multiple spatial and spectral resolution, namely: the Visible Infrared Imaging Radiometer Suite (VIIRS) (750 m/Multispectral), the Ocean and Land Color Instrument (OLCI) (300 m/Multispectral), the Hyperspectral Imager for the Coastal Ocean (HICO) (100 m/Hyperspectral), and the Landsat 8 Operational Land Imager (OLI) (30 m/Multispectral). The UV to visible scheme can benefit the CDOM absorption estimation in two aspects: 1) it is free from the disturbance of suspended matter; 2) it avoids uncertainties caused by the low signal-to-noise ratio (SNR) of ag measurements in the visible range. The algorithm is effective in revealing multiple scales of variation of CDOM absorption from ocean color observations.
Keywords Chromophoric dissolved organic matter      ocean color remote sensing      Pearl River Estuary      ultraviolet     
Corresponding Author(s): Jiayi PAN   
Online First Date: 15 January 2020    Issue Date: 21 July 2020
 Cite this article:   
Xia LEI,Jiayi PAN,Adam DEVLIN. An ultraviolet to visible scheme to estimate chromophoric dissolved organic matter absorption in a Case-2 water from remote sensing reflectance[J]. Front. Earth Sci., 2020, 14(2): 384-400.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-019-0777-5
https://academic.hep.com.cn/fesci/EN/Y2020/V14/I2/384
1 Administration of Ocean and Fisheries of Guangdong Province (2013–2016). Report on the Marine Environmental Quality in Guangdong. Available at Guangdong Government website
2 N V Blough, R Del Vecchio (2002). Chromophoric dissolved organic matter (CDOM) in the coastal environment. In: Hansell D, Carlson C, eds. Biogeochemistry of Marine Dissolved Organic Matter. San Diego, CA: Academic Press, 509–546
3 A Bricaud, A Morel, L Prieur (1981). Absorption by dissolved organic matter of the sea (yellow substance) in the UV and visible domains. Limnol Oceanogr, 26(1): 43–53
https://doi.org/10.4319/lo.1981.26.1.0043
4 J Callahan, M H Dai, R F Chen, X L Li, Z M Lu, W Huang (2004). Dissolved organic matter in the Pearl River Estuary, China. Mar Chem, 89(1-4): 211–224
https://doi.org/10.1016/j.marchem.2004.02.013
5 F Cao, W L Miller (2015). A new algorithm to retrieve chromophoric dissolved organic matter (CDOM) absorption spectra in the UV from ocean color. J Geophys Res Oceans, 120(1): 496–516
https://doi.org/10.1002/2014JC010241
6 K L Carder, R G Steward (1985). A remote-sensing reflectance model for a red tide dinoflagellate off West Florida. Limnol Oceanogr, 30(2): 286–298
https://doi.org/10.4319/lo.1985.30.2.0286
7 C Q Chen, P Shi, K D Yin, Z L Pan, H G Zhan, C M Hu (2003). Absorption coefficient of yellow substance in the Pearl River Estuary. In: Proceedings of Ocean Remote Sensing and Applications. Bellingham WA: SPIE, 4892: 215–221
8 Z Chen, Y Li, J Pan (2004). The distributions of the optical properties of colored dissolved organic matter and dissolved organic carbon in the Pearl River Estuary. Cont Shelf Res, 24: 1845–1856
https://doi.org/10.1016/j.csr.2004.06.011
9 M J Church, H W Ducklow, D M Karl (2002). Multi-year increases in dissolved organic matter inventories at Station ALOHA in the North Pacific Subtropical Gyre. Limnol Oceanogr, 47(1): 1–10
https://doi.org/10.4319/lo.2002.47.1.0001
10 Z Deng, Q He, Q Yang, J Lin (2015). Observations of in situ flocs characteristics in the Modaomen Estuary of the Pearl River. Haiyang Xuebao, 37(9): 152–161 (in Chinese)
11 H W Ducklow (2002). Forword. In: Hansell D, Carlson C, eds. Biogeochemistry of Marine Dissolved Organic Matter. San Diego, CA: Academic Press
12 C G Fichot, R Benner (2012). The spectral slope coefficient of chromophoric dissolved organic matter (S275–295) as a tracer of terrigenous dissolved organic carbon in river-influenced ocean margins. Limnol Oceanogr, 57(5): 1453–1466
https://doi.org/10.4319/lo.2012.57.5.1453
13 C G Fichot, R Benner, K Kaiser, Y Shen, R M W Amon, H Ogawa, C J Lu (2016). Predicting dissolved lignin phenol concentrations in the coastal ocean from chromophoric dissolved organic matter (CDOM) absorption coefficients. Front Mar Sci, 3(7): 1–15
https://doi.org/10.3389/fmars.2016.00007
14 D Fu, H Luan, D Liu, Y Zhang, Y Ding, W Wang, X Li, C Jiang (2016). Analysis of suspended sediment concentration remote sensing models in winter and spring in the Pearl River estuary. Haiyang Huanjiang Kexue, 35(4): 600–604 (in Chinese)
15 S Geisser (1993). Predictive Inference. New York, NY: Chapman and Hall
16 H R Gordon, M Wang (1994). Retrieval of water-leaving radiance and aerosol optical thickness over the oceans with SeaWiFS: a preliminary algorithm. Appl Opt, 33(3): 443–452
https://doi.org/10.1364/AO.33.000443 pmid: 20862036
17 J R Helms, A Stubbins, E M Perdue, N W Green, H Chen, K Mopper (2013). Photochemical bleaching of oceanic dissolved organic matter and its effect on absorption spectral slope and fluorescence. Mar Chem, 155: 81–91
https://doi.org/10.1016/j.marchem.2013.05.015
18 J R Helms, A Stubbins, J D Ritchie, E C Minor, D J Kieber, K Mopper (2008). Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter. Limnol Oceanogr, 53(3): 955–969
https://doi.org/10.4319/lo.2008.53.3.0955
19 H S Hong, J Y Wu, S L Shang, C M Hu (2005). Absorption and fluorescence of chromophoric dissolved organic matter in the Pearl River Estuary, South China. Marine. Chemistry, 97: 78–89
20 IOCCG (2016). Remote sensing of inherent optical properties: Fundamentals, tests of algorithms, and applications. In: Lee Z P, ed. Reports of the International Ocean-Colour Coordinating Group (No. 5). Dartmouth, Canada: IOCCG
21 R W P M Laane, K J M Kramer (1990). Natural fluorescence in the North Sea and its major estuaries. Neth J Sea Res, 26(1): 1–9
https://doi.org/10.1016/0077-7579(90)90052-I
22 Z Lee, K L Carder, S K Hawes, R G Steward, T G Peacock, C O Davis (1994). Model for the interpretation of hyperspectral remote-sensing reflectance. Appl Opt, 33(24): 5721–5732
https://doi.org/10.1364/AO.33.005721 pmid: 20935974
23 X Lei, J Y Pan, A T Devlin (2018). Mixing behavior of chromophoric dissolved organic matter in the Pearl River Estuary in spring. Cont Shelf Res, 154: 46–54
https://doi.org/10.1016/j.csr.2018.01.004
24 D Liu, C Zhang, D Fu, C Shen (2010). Hyperspectral data-based remote-sensing inversion model for suspended sediment in surface waters at the Pearl River Estuary. Mark Sci, 34(7): 77–80 (in Chinese)
25 F Liu, C Chen, S Tang, D Liu (2009). A piecewise algorithm for retrieval of suspended sediment concentration based on in situ spectral data by MERIS in Zhujiang River Estuary. Journal of Tropical Oceanography, 28(1): 9–14 (in Chinese)
26 H Loisel, A Morel (2001). Non-isotropy of the upward radiance field in typical coastal (Case 2) waters. Int J Remote Sens, 22(2–3): 275–295
https://doi.org/10.1080/014311601449934
27 S A Loiselle, L A Bracchini, M Dattilo, M Ricci, A Tognazzi, A Cózar, C Rossi (2009). Optical characterization of chromophoric dissolved organic matter using wavelength distribution of absorption spectral slopes. Limnol Oceanogr, 54(2): 590–597
https://doi.org/10.4319/lo.2009.54.2.0590
28 S Loiselle, D Vione, C Minero, V Maurino, A Tognazzi, A M Dattilo, C Rossi, L Bracchini (2012). Chemical and optical phototransformation of dissolved organic matter. Water Res, 46(10): 3197–3207
https://doi.org/10.1016/j.watres.2012.02.047 pmid: 22503589
29 C Mobley (1994). Light and water: radiative transfer in natural waters. New York: Academic Press
30 C D Mobley (1999). Estimation of the remote-sensing reflectance from above-surface measurements. Appl Opt, 38(36): 7442–7455
https://doi.org/10.1364/AO.38.007442 pmid: 18324298
31 A Morel, B Gentili (1993). Diffuse reflectance of oceanic waters. II Bidirectional aspects. Appl Opt, 32(33): 6864–6879
https://doi.org/10.1364/AO.32.006864 pmid: 20856540
32 A Morel, J L Mueller (2002). Normalized water-leaving radiance and remote sensing reflectance. Bidirectional reflectance and other factors. In: Ocean Optics Protocols for Satellite Ocean Color Sensor Validation (Revision. 4). NASA: 3: 32–59
33 A Morel, L Prieur (1977). Analysis of variations in ocean color. Limnol Oceanogr, 22(4): 709–722
https://doi.org/10.4319/lo.1977.22.4.0709
34 J L Mueller, C Davis, R Arnone, R Frouin, K Carder, Z P Lee, R G Steward, S Hooker, C D Mobley, S Mclean (2002). Above-water radiance and remote sensing reflectance measurement and analysis protocols. In: Ocean Optics Protocols for Satellite Ocean Color Sensor Validation (Revesion 4). NASA: 3: 21–31
35 NASA Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group (2018). Ocean and Land Colour Imager (OLCI) L1 Data; NASA OB.DAAC, Greenbelt, MD, USA
36 N B Nelson, D A Siegel (2002). Chromophoric dissolved organic matter (CDOM) in the open ocean. In Hansell D, Carlson C, eds. Biogeochemistry of Marine Dissolved Organic Matter. San Diego, CA: Academic Press, 547–578.
37 J Y Pan, Y Z Gu (2016). Cruise observation and numerical modeling of turbulent mixing in the Pearl River estuary in summer. Cont Shelf Res, 120: 122–138
https://doi.org/10.1016/j.csr.2016.03.019
38 C M Sharpless, N V Blough (2014). The importance of charge-transfer interactions in determining chromophoric dissolved organic matter (CDOM) optical and photochemical properties. Environ Sci Process Impacts, 16(4): 654–671
https://doi.org/10.1039/C3EM00573A pmid: 24509887
39 D A Siegel, S Maritorena, N B Nelson, D A Hansell, M Lorenzi-Kayser (2002). Global distribution and dynamics of colored dissolved and detrital organic materials. J Geophys Res, 107(C12): 3228–3242
https://doi.org/10.1029/2001JC000965
40 D A Siegel, M Wang, S Maritorena, W Robinson (2000). Atmospheric correction of satellite ocean color imagery: the black pixel assumption. Appl Opt, 39(21): 3582–3591
https://doi.org/10.1364/AO.39.003582 pmid: 18349929
41 C A Stedmon, S Markager (2001). The optics of chromophoric dissolved organic matter (CDOM) in the Greenland Sea: an algorithm for differentiation between marine and terrestrially derived organic matter. Limnol Oceanogr, 46(8): 2087–2093
https://doi.org/10.4319/lo.2001.46.8.2087
42 C A Stedmon, N B Nelson (2015). The optical properties of DOM in the ocean. In: Hansell D, Carlson C, eds. Biogeochemistry of Marine Dissolved Organic Matter. 2nd ed. San Diego, CA: Academic Press, 481–508
43 M S Twardowski, E Boss, J M Sullivan, P L Donaghay (2004). Modeling the spectral shape of absorption by chromophoric dissolved organic matter. Mar Chem, 89(1–4): 69–88
https://doi.org/10.1016/j.marchem.2004.02.008
44 V Vantrepotte, F P Danhiez, H Loisel, S Ouillon, X Mériaux, A Cauvin, D Dessailly (2015). CDOM-DOC relationship in contrasted coastal waters: implication for DOC retrieval from ocean color remote sensing observation. Opt Express, 23(1): 33–54
https://doi.org/10.1364/OE.23.000033 pmid: 25835652
45 E Vermote (2016). VNP09-VIIRS/NPP Atmospherically Corrected Surface Reflectance 6-Min L2 Swath IP 375m, 750m, NASA Level-1 and Atmosphere Archive & Distribution System (LAADS) Distributed Active Archive Center (DAAC). Goddard Space Flight Center, Greenbelt, MD
46 G Wang, W Cao, D Xu, D Yang (2007). Variations in the light absorption coefficients of non-algal particels in the north of the South China Sea. HAIYANG JISHU, 26(1): 45–53 (in Chinese)
47 S S Wang, Y B Wang, Q H Fu, B Yin, Y M Li (2014). Spectral absorption properties of the water constituents in the estuary of Zhujiang River. Environm Sci, 35(12): 4511–4521 (in Chinese)
pmid: 25826920
48 J Wei, Z Lee, M Ondrusek, A Mannino, M Tzortziou, R Armstrong (2016). Spectral slopes of the absorption coefficient of colored dissolved and detrital material inverted from UV-visible remote sensing reflectance. J Geophys Res Oceans, 121(3): 1953–1969
https://doi.org/10.1002/2015JC011415 pmid: 29201583
49 X Xu, W Cao, Y Yang (2004). Relationships between spectral absorption coefficient of particulates and salinity and chlorophyll a concentration in Zhujiang River mouth. J Tropical Oceanogra, 23(5): 63–71 (in Chinese)
50 J Yang, C Chen (2007). An optimal algorithm for retrieval of chlorophyll, suspended sediments and gelbstoff of case II waters in Zhujiang River estuary. J Tropical Oceanogra, 26(5): 15–20 (in Chinese)
51 H Zhou, B Han, T Li, J Zhu, X Wang (2007). Variations in the light absorption coefficients of de-pigment par ticles in South Yellow Sea and Zhu Jiang Kou of China. Ocean Technology, 26(3): 114–117 (in Chinese)
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