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Frontiers of Earth Science

ISSN 2095-0195

ISSN 2095-0209(Online)

CN 11-5982/P

Postal Subscription Code 80-963

2018 Impact Factor: 1.205

Front. Earth Sci.    2015, Vol. 9 Issue (4) : 732-741    https://doi.org/10.1007/s11707-015-0526-3
RESEARCH ARTICLE
Modified optical remote sensing algorithms for the Pearl River Estuary
Man-Chung CHIM, Jiayi PAN(), Wenfeng LAI
Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong SAR, China
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Abstract

This study aims to develop new algorithms to retrieve sea surface parameters including concentrations of Chlorophyll a (Chl a) and Suspended Particulate Matter (SPM), and absorbance of Colored Dissolved Organic Matter (aCDOM) by incorporating the contribution of red bands to make them more adaptable to case 2 waters. Optical remote sensing algorithms have demonstrated efficient retrieval of Chl a, SPM, and aCDOM, yet they are not very accurate especially for coastal areas. It has also been found that the default algorithm has overestimated Chl a in the Pearl River Estuary, and shown poor correlation for CDOM absorbance. By incorporating the red band ratios into the algorithm, a correction effect has been shown, which improves the accuracy of quantifying the actual concentration. Modeling and data fitting of the algorithm have been done based on 61 data samples collected in the Pearl River estuary during a cruise from 3 to 11 May 2014. The study also attempts to modify the aerosol correction bands used in SeaDAS to prevent saturation of these bands. The modified algorithms showed an R-Square value of 0.7289 for Chl a fitting, and 0.7338 for CDOM fitting, and corrected overestimation of Chl a concentration in the Pearl River estuary.

Keywords optical remote sensing algorithm      Pearl River Estuary     
Corresponding Author(s): Jiayi PAN   
Just Accepted Date: 26 August 2015   Online First Date: 30 September 2015    Issue Date: 30 October 2015
 Cite this article:   
Man-Chung CHIM,Jiayi PAN,Wenfeng LAI. Modified optical remote sensing algorithms for the Pearl River Estuary[J]. Front. Earth Sci., 2015, 9(4): 732-741.
 URL:  
https://academic.hep.com.cn/fesci/EN/10.1007/s11707-015-0526-3
https://academic.hep.com.cn/fesci/EN/Y2015/V9/I4/732
1 A R Arellano (2013). Investigation of Colored Dissolved Organic Matter (CDOM) Optical Properties, Nutrients, and Salinity in Coastal Florida: Springshed to Estuaries. University of South Florida Scholar Commons, Graduate Theses and Dissertations
2 X Chen, L Chen, Z Yu, L Tian, W Zhang (2009). Chromophoric dissolved organic matter optical characteristics and spatial distribution in the lakes of the middle reaches of YangTze River. Journal of Lake Science, 21(2): 248–254
3 A A Gilerson, A A Gitelson, J Zhou, D Gurlin, W Moses, I Ioannou, S A Ahmed (2010). Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands. Opt Express, 18(23): 24109–24125
https://doi.org/10.1364/OE.18.024109
4 I Ioannou, A Gilerson, B Gross, F Moshary, S Ahmed (2013). Deriving ocean color products using neural networks. Remote Sens Environ, 134: 78–91
https://doi.org/10.1016/j.rse.2013.02.015
5 Z Lee, K L Carder (2000). Band-ratio or spectral-curvature algorithms for satellite remote sensing. Applied Optics, 39(24): 4377–4380
6 Z Lee, K L Carder, C D Mobley, R G Steward, and J S Patch (1998). Hyperspectral remote sensing for shallow waters. I. A semianalytical model. Applied Optics, 37(27): 6329–6338
7 A Matsuoka, A Bricaud, R Benner, J Para, R Sempéré, L Prieur, S Bélanger, M Babin (2012). Tracing the transport of colored dissolved organic matter in water masses of the Southern Beaufort Sea: relationship with hydrographic characteristics. Biogeosciences, 9(3): 925–940
https://doi.org/10.5194/bg-9-925-2012
8 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
9 B Nababan (2008). Comparison of chlorophyll concentration estimation using two different algorithms and the effect of coloured dissolved organic matter. International Journal of Remote Sensing and Earth Sciences, 5: 92–101
10 R A Neville, J F R Gower (1977). Passive remote sensing of phytoplankton via chlorophyll a fluorescence. Journal of Geophysical Research, 82(24): 3487–3493
11 J E O’Reilly, S Maritorena, B G Mitchell, D A Siegel, K L Carder, S A Garver, M Kahru, C McClain (1998). Ocean Color Chlorophyll algorithms for SeaWiFS. J Geophys Res, 103(C11): 24937–24953
https://doi.org/10.1029/98JC02160
12 K Ruddick, B Nechad, G Neukermans, Y Park, D Doxaran, D Sirjacobs, J M Beckers (2008). Remote Sensing of Suspended Particulate Matter in Turbid Waters: State of the Art and Future Perspectives. CDROM Proceedings of the Ocean Optics XIX conference held in Barga, 2008-October-6
13 J Tang (2004). The methods of water spectra measurement and analysis I: above-water method. Journal of Remote Sensing, 8(1): 37–44
14 M Wang, W Shi (2007). The NIR-SWIR combined atmospheric correction approach for MODIS ocean color data processing. Opt Express, 15(24): 15722–15733
https://doi.org/10.1364/OE.15.015722
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[2] Meilin WU, Youshao WANG, Junde DONG, Fulin SUN, Yutu WANG, Yiguo HONG. Spatial assessment of water quality using chemometrics in the Pearl River Estuary, China[J]. Front. Earth Sci., 2017, 11(1): 114-126.
[3] Xianbin LIU, Deliang LI, Guisheng SONG. Assessment of heavy metal levels in surface sediments of estuaries and adjacent coastal areas in China[J]. Front. Earth Sci., 2017, 11(1): 85-94.
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