Abstract
Secchi depth (SD, m) is a direct and intuitive measure of water’s transparency, which is also an indicator of water quality. In 2015, a semi-analytical model was developed to derive SD from remote sensing reflectance, thus able to provide maps of water’s transparency in satellite images. Here an in-situ dataset (338 stations) is used to evaluate its potential ability to monitor water quality in the coastal and estuarine waters, with measurements covering the Zhujiang (Pearl) River Estuary, the Yellow Sea and the East China Sea where measured SD values span a range of 0.2–21.0 m. As a preliminary validation result, according to the whole dataset, the unbiased percent difference (UPD) between estimated and measured SD is 23.3% (N=338, R2=0.89), with about 60% of stations in the dataset having relative difference (RD) ⩽ 20%, over 80% of stations having RD ⩽ 40%. Furthermore, by excluding the field data which with relatively larger uncertainties, the semi-analytical model yielded the UPD of 17.7% (N=132, R2=0.92) with SD range of 0.2–11.0 m. In addition, the semi-analytical model was applied to Landsat-8 images in the Zhujiang River Estuary, and retrieved high-quality mapping and reliable spatial-temporal patterns of water clarity. Taking into account the uncertainties associated with both field measurements and satellite data processing, and that there were no tuning of the semi-analytical model for these regions, these findings indicate highly robust retrieval of SD from spectral techniques for such turbid coastal and estuarine waters. The results suggest it is now possible to routinely monitor coastal water transparency or visibility at high-spatial resolutions from measurements, like Landsat-8 and Sentinel-2 and newly launched Gaofen-5.
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References
Aas E, Høkedal J, Sørensen K. 2014. Secchi depth in the Oslofjord-Skagerrak area: theory, experiments and relationships to other quantities. Ocean Science, 10(2): 177–199, doi: https://doi.org/10.5194/os-10-177-2014
Al Kaabi M R, Zhao Jun, Ghedira H. 2016. MODIS-based mapping of Secchi disk depth using a qualitative algorithm in the shallow arabian gulf. Remote Sensing, 8(5): 423, doi: https://doi.org/10.3390/rs8050423
Arnone R A, Tucker S P, Hilder F A. 1984. Secchi depth atlas of the world coastlines. In: Proceedings of SPIE 0489, Ocean Optics VII. Monterey, USA: SPIE, 195–202, doi: https://doi.org/10.1117/12.943305
Binding C E, Jerome J H, Bukata R P, et al. 2007. Trends in water clarity of the lower Great Lakes from remotely sensed aquatic color. Journal of Great Lakes Research, 33(4): 828–841, doi: https://doi.org/10.3394/0380-1330(2007)33[828:TIWCOT]2.0.CO;2
Boyce D G, Lewis M R, Worm B. 2010. Global phytoplankton decline over the past century. Nature, 466(7306): 591–596, doi: https://doi.org/10.1038/nature09268
Brown D, Warwick R, Skaggs R. 1977. Reconnaissance analysis of lake condition in east-central Minnesota. Minneapolis, MN: Minnesota Land Management Information System, Center for Urban and Regional Affairs, University of Minnesota, 19
Bukata R P, Jerome J H, Bruton J E. 1988. Relationships among Secchi disk depth, beam attenuation coefficient, and irradiance attenuation coefficient for Great Lakes waters. Journal of Great Lakes Research, 14(3): 347–355, doi: https://doi.org/10.1016/S0380-1330(88)71564-6
Carlson R E. 1977. A trophic state index for lakes. Limnology and Oceanography, 22(2): 361–369, doi: https://doi.org/10.4319/lo.1977.22.2.0361
Chen Lei, Xie Jian, Peng Xiaojuan, et al. 2011. The relationship between seawater clarity and water-leaving reflectance spectra of seawater in the Pearl River Estuary. Remote Sensing for Land & Resources (in Chinese), (3): 151–155, doi: https://doi.org/10.6046/gtzyyg.2011.03.27
Cui Tingwei, Song Qingjun, Tang Junwu, et al. 2013. Spectral variability of sea surface skylight reflectance and its effect on ocean color. Optics Express, 21(21): 24929–24941, doi: https://doi.org/10.1364/OE.21.024929
Davies-Colley R J, Vant W N. 1988. Estimation of optical properties of water from Secchi disk depths. Journal of the American Water Resources Association, 24(6): 1329–1335, doi: https://doi.org/10.1111/j.1752-1688.1988.tb03054.x
Dekker A G, Peters S W M. 1993. The use of the thematic mapper for the analysis of eutrophic lakes: a case study in the Netherlands. International Journal of Remote Sensing, 14(5): 799–821, doi: https://doi.org/10.1080/01431169308904379
Dev P J, Shanmugam P. 2014. A new theory and its application to remove the effect of surface-reflected light in above-surface radiance data from clear and turbid waters. Journal of Quantitative Spectroscopy and Radiative Transfer, 142: 75–92, doi: https://doi.org/10.1016/j.jqsrt.2014.03.021
Doron M, Babin M, Hembise O, et al. 2011. Ocean transparency from space: validation of algorithms estimating Secchi depth using MERIS, MODIS and SeaWiFS data. Remote Sensing of Environment, 115(12): 2986–3001, doi: https://doi.org/10.1016/j.rse.2011.05.019
Doron M, Babin M, Mangin A, et al. 2007. Estimation of light penetration, and horizontal and vertical visibility in oceanic and coastal waters from surface reflectance. Journal of Geophysical Research, 112(C6): C06003, doi: https://doi.org/10.1029/2006JC004007
Duntley S Q, Preisendorfer R W. 1952. The visibility of submerged objects. In: Final Report N5ori-07864. Cambridge, MA: Visibility Laboratory, Massachusetts Institute of Technology, 74
Franz B A, Bailey S W, Kuring N, et al. 2015. Ocean color measurements with the operational land imager on Landsat-8: implementation and evaluation in SeaDAS. Journal of Applied Remote Sensing, 9(1): 096070, doi: https://doi.org/10.1117/1.JRS.9.096070
Garaba S P, Schulz J, Wernand M R, et al. 2012. Sunglint detection for unmanned and automated platforms. Sensors, 12(9): 12545–12561, doi: https://doi.org/10.3390/s120912545
Han Liusheng, Chen Shuisen, Chen Xiuzhi, et al. 2014. Estimation of water clarity in offshore marine areas based on modified semi-analysis spectra model. Spectroscopy and Spectral Analysis (in Chinese), 34(2): 477–482, doi: https://doi.org/10.3964/j.issn.1000-0593(2014)02-0477-06
He Xianqiang, Pan Delu, Mao Zhihua. 2004. Water-transparency (Secchi Depth) monitoring in the China Sea with the SeaWiFS satellite sensor. In: Proceedings of SPIE 5568, Remote Sensing for Agriculture, Ecosystems, and Hydrology VI. Canary Islands, Spain: SPIE, 112–122, doi: https://doi.org/10.1117/12.564605
Holmes R W. 1970. The Secchi disk in turbid coastal waters. Limnology and Oceanography, 15(5): 688–694, doi: https://doi.org/10.4319/lo.1970.15.5.0688
Kirk J T O. 2011. Light and Photosynthesis in Aquatic Ecosystems. Cambridge: Cambridge University Press, 649
Kratzer S, Håkansson B, Sahlin C. 2003. Assessing Secchi and photic zone depth in the Baltic Sea from satellite data. AMBIO: A Journal of the Human Environment, 32(8): 577–585, doi: https://doi.org/10.1579/0044-7447-32.8.577
Lathrop R G. 1992. Landsat Thematic Mapper monitoring of turbid inland water quality. Photogrammetric Engineering & Remote Sensing, 58(4): 465–470
Lathrop R G, Lillesand T M, Yandell B S. 1991. Testing the utility of simple multi-date Thematic Mapper calibration algorithms for monitoring turbid inland waters. International Journal of Remote Sensing, 12(10): 2045–2063, doi: https://doi.org/10.1080/01431169108955235
Lee Z, Ahn Y H, Mobley C, et al. 2010. Removal of surface-reflected light for the measurement of remote-sensing reflectance from an above-surface platform. Optics Express, 18(25): 26313–26324, doi: https://doi.org/10.1364/OE.18.026313
Lee Z, Carder K L, Arnone R A. 2002. Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters. Applied Optics, 41(27): 5755–5772, doi: https://doi.org/10.1364/ao.41.005755
Lee Z, Carder K L, Mobley C D, et al. 1999. Hyperspectral remote sensing for shallow waters: 2. Deriving bottom depths and water properties by optimization. Applied Optics, 38(18): 3831–3843, doi: https://doi.org/10.1364/AO.38.003831
Lee Z, Hu Chuanmin, Shang Shaoling, et al. 2013. Penetration of UV-visible solar radiation in the global oceans: insights from ocean color remote sensing. Journal of Geophysical Research, 118(9): 4241–4255, doi: https://doi.org/10.1002/jgrc.20308
Lee Z, Shang Shaoling, Hu Chuanmin, et al. 2015. Secchi disk depth: a new theory and mechanistic model for underwater visibility. Remote Sensing of Environment, 169: 139–149, doi: https://doi.org/10.1016/j.rse.2015.08.002
Lee Z, Shang Shaoling, Qi Lin, et al. 2016. A semi-analytical scheme to estimate Secchi-disk depth from Landsat-8 measurements. Remote Sensing of Environment, 177: 101–106, doi: https://doi.org/10.1016/j.rse.2016.02.033
Lee Z, Weidemann A, Kindle J, et al. 2007. Euphotic zone depth: its derivation and implication to ocean-color remote sensing. Journal of Geophysical Research, 112(C3): C03009, doi: https://doi.org/10.1029/2006JC003802
Lewis M R, Kuring N, Yentsch C. 1988. Global patterns of ocean transparency: implications for the new production of the open ocean. Journal of Geophysical Research, 93(C6): 6847–6856, doi: https://doi.org/10.1029/JC093iC06p06847
Lillesand T M, Johnson W L, Deuell R L, et al. 1983. Use of Landsat data to predict the trophic state of Minnesota lakes. Photogrammetric Engineering and Remote Sensing, 49(2): 219–229
Liu Xianfu, Li Tongji, Chen Qinglian. 2004. Impact of dominant components to Apparent Optical Properties in the ocean. Ocean Technology (in Chinese), 123(11): 86–90, doi: https://doi.org/10.3969/j.issn.1003-2029.2004.01.020
Luhtala H, Tolvanen H. 2013. Optimizing the use of secchi depth as a proxy for euphotic depth in coastal waters: an empirical study from the Baltic sea. International Journal of Environmental Research and Public Health (IJERPH), 2(4): 1153–1168, doi: https://doi.org/10.3390/ijgi2041153
Luis K M A, Rheuban J E, Kavanaugh M T, et al. 2019. Capturing coastal water clarity variability with Landsat 8. Marine Pollution Bulletin, 145: 96–104, doi: https://doi.org/10.1016/j.marpolbul.2019.04.078
Megard R O, Berman T. 1989. Effects of algae on the Secchi transparency of the southeastern Mediterranean Sea. Limnology and Oceanography, 34(8): 1640–1655, doi: https://doi.org/10.4319/lo.1989.34.8.1640
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
Mueller J L. 2000. SeaWiFS algorithm for the diffuse attenuation coefficient, K(490), using water-leaving radiances at 490 and 555 nm. In: O’Reilly J E, ed. SeaWiFS Postlaunch Calibration and Validation Analyses. California: NASA Goddard Space Flight Center, 24–27
Mueller J L, Davis C, Arnone R, et al. 2003. Above-water radiance and remote sensing reflectance measurement and analysis protocols. In: Ocean Optics Protocols for Satellite Ocean-Colour Sensor Validation. Greenbelt, Maryland: NASA Goddard Space Flight Center, 21–31
Prasad K S, Bernstein R L, Kahru M, et al. 1998. Ocean color algorithms for estimating water clarity (Secchi depth) from Sea-WiFS. Journal of Advanced Marine Science and Technology Society, 4(2): 301, doi: https://doi.org/10.14928/amstec.4.2_301
Preisendorfer R W. 1986. Secchi disk science: visual optics of natural waters. Limnology and Oceanography, 31(5): 909–926, doi: https://doi.org/10.4319/lo.1986.31.5.0909
Ritchie J C, Cooper C M, Schiebe F R. 1990. The relationship of MSS and TM digital data with suspended sediments, chlorophyll, and temperature in Moon Lake, Mississippi. Remote Sensing of Environment, 33(2): 137–148, doi: https://doi.org/10.1016/0034-4257(90)90039-O
Shang Shaoling, Lee Z, Shi Lianghai, et al. 2016. Changes in water clarity of the Bohai Sea: observations from MODIS. Remote Sensing of Environment, 186: 22–31, doi: https://doi.org/10.1016/j.rse.2016.08.020
Singh N K, Bajwa S G, Chaubey I. 2008. Removal of surface reflection from above-water visible-near infrared spectroscopic measurements. Applied Spectroscopy, 62(9): 1013–1021, doi: https://doi.org/10.1366/000370208785793191
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, doi: https://doi.org/10.11834/jrs.20040106
Vanhellemont Q, Ruddick K. 2014. Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sensing of Environment, 145: 105–115, doi: https://doi.org/10.1016/j.rse.2014.01.009
Vanhellemont Q, Ruddick K. 2015. Advantages of high quality SWIR bands for ocean colour processing: examples from Landsat-8. Remote Sensing of Environment, 161: 89–106, doi: https://doi.org/10.1016/j.rse.2015.02.007
Wang Xiaomei, Tang Junwu, Ma Chaofei, et al. 2005. The retrieval algorithms of diffuse attenuation and transparency for the Case-II waters of the Huanghai Sea and the East China Sea. Haiyang Xuebao (in Chinese), 27(5): 38–45, doi: https://doi.org/10.3321/j.issn:0253-4193.2005.05.006
Wei Jianwei, Lee Z, Garcia R, et al. 2018. An assessment of Landsat-8 atmospheric correction schemes and remote sensing reflectance products in coral reefs and coastal turbid waters. Remote Sensing of Environment, 215: 18–32, doi: https://doi.org/10.1016/j.rse.2018.05.033
Wei Jianwei, Lee Z, Shang Shaoling. 2016. A system to measure the data quality of spectral remote-sensing reflectance of aquatic environments. Journal of Geophysical Research, 121(11): 8189–8207, doi: https://doi.org/10.1002/2016JC012126
Xu Jingping, Zhao Jianhua, Li Fang, et al. 2016. Object-based image analysis for mapping geomorphic zones of coral reefs in the Xisha Islands, China. Acta Oceanologica Sinica, 35(12): 19–27, doi: https://doi.org/10.1007/s13131-016-0921-y
Xue Kun, Zhang Yuchao, Duan Hongtao, et al. 2015. A remote sensing approach to estimate vertical profile classes of phytoplankton in a eutrophic lake. Remote Sensing, 7(11): 14403–14427, doi: https://doi.org/10.3390/rs71114403
Yentsch C S, Yentsch C M, Cullen J J, et al. 2002. Sunlight and water transparency: cornerstones in coral research. Journal of Experimental Marine Biology and Ecology, 268(2): 171–183, doi: https://doi.org/10.1016/S0022-0981(01)00379-3
Yu D F, Xing Q G, Lou M J, et al. 2014a. Retrieval of Secchi disk depth in the Yellow Sea and East China Sea using 8-day MODIS data. IOP Conference Series: Earth and Environmental Science, 17(1): 012112, doi: https://doi.org/10.1088/1755-1315/17/1/012112
Yu Dingfeng, Zhou Bin, Xing Qianguo, et al. 2014b. Monitoring Secchi depth of the Yellow Sea and the East China Sea using a semi-analytical algorithm. In: Proceedings of SPIE 9261, Ocean Remote Sensing and Monitoring from Space. Beijing: SPIE, 92611J, doi: https://doi.org/10.1117/12.2068166
Acknowledgements
We thank Junwu Tang, and other colleagues for their great efforts in field measurements. This research was carrying out under Zhongping Lee’s guidance, and got critical advices and helps from Ocean Optical Lab, when Xianfu Liu was a one-year visiting scholar in the University of Massachusetts Boston (UMB). We also thank Mingjie Li, Di Dong and Bing Li, Lumei Huang for their constructive comments and helpful discussions on the manuscript. Our special thanks go to Jianwei Wei for his efforts in revising the manuscript.
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Foundation item: The National Natural Science Foundation of China under contract No. 61527810; the Marine Science and Technology Fund from Director of South China Sea Branch, State Oceanic Administration of China under contract No. 180101; the Key Laboratory Open Project Fund of Technology and Application for Safeguarding of Marine Rights and Interests, State Oceanic Administration of China under contract No. 1720.
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Liu, X., Meng, X., Wang, X. et al. Using a semi-analytical model to retrieve Secchi depth in coastal and estuarine waters. Acta Oceanol. Sin. 39, 103–112 (2020). https://doi.org/10.1007/s13131-020-1620-2
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DOI: https://doi.org/10.1007/s13131-020-1620-2