Improved Accuracy of Chlorophyll-a Concentration Estimates from MODIS Imagery Using a Two-Band Ratio Algorithm and Geostatistics: As Applied to the Monitoring of Eutrophication Processes over Tien Yen Bay (Northern Vietnam)
Sea eutrophication is a natural process of water enrichment caused by increased nutrient loading that severely affects coastal ecosystems by decreasing water quality. The degree of eutrophication can be assessed by chlorophyll-a concentration. This study aims to develop a remote sensing method suitable for estimating chlorophyll-a concentrations in tropical coastal waters with abundant phytoplankton using Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra imagery and to improve the spatial resolution of MODIS/Terra-based estimation from 1 km to 100 m by geostatistics. A model based on the ratio of green and blue band reflectance (rGBr) is proposed considering the bio-optical property of chlorophyll-a. Tien Yen Bay in northern Vietnam, a typical phytoplankton-rich coastal area, was selected as a case study site. The superiority of rGBr over two existing representative models, based on the blue-green band ratio and the red-near infrared band ratio, was demonstrated by a high correlation of the estimated chlorophyll-a concentrations at 40 sites with values measured in situ. Ordinary kriging was then shown to be highly capable of predicting the concentration for regions of the image covered by clouds and, thus, without sea surface data. Resultant space-time maps of concentrations over a year clarified that Tien Yen Bay is characterized by natural eutrophic waters, because the average of chlorophyll-a concentrations exceeded 10 mg/m 3 in the summer. The temporal changes of chlorophyll-a concentrations were consistent with average monthly air temperatures and precipitation. Consequently, a combination of rGBr and ordinary kriging can effectively monitor water quality in tropical shallow waters.
References
[1]
Matthews, A.M.; Duncan, A.G.; Davison, R.G. An assessment of validation techniques for estimating chlorophyll-a concentration from airborne multispectral imagery. Int. J. Remote Sens 2001, 22, 429–447.
[2]
Cauwer, V.D.; Ruddick, K.; Park, Y.J.; Nechad, B.; Kyramarios, M. Optical remote sensing in support of eutrophication monitoring in the southern North Sea. EARSeL eProc 2004, 3, 208–221.
[3]
Zimba, P.V.; Gitelson, A. Remote estimation of chlorophyll concentration in hyper-eutrophic aquatic systems: Model tuning and accuracy optimization. Aquaculture 2006, 256, 272–286.
[4]
Schalles, J.F. Optical Remote Sensing Techniques to Estimate Phytoplankton Chlorophyll-a Concentrations in Coastal Waters with Varying Suspended Matter and CDOM Concentrations. In Remote Sensing of Aquatic Coastal Ecosystem Processes: Science and Management Application; Richardson, L.L., LeDew, E.F., Eds.; Springer: Dordrecht, The Netherlands, 2006; pp. 27–78.
[5]
Ibrahim, A.N; Mabuchi, Y.; Murakami, M. Remote sensing algorithms for monitoring eutrophication in Ishizuchi storm water reservoir in Kochi Prefecture, Japan. Hydrol. Sci. J 2009, 50, 525–542.
[6]
Gordon, H.R; Morel, A.Y. Remote Assessment of Ocean Color for Interpretation of Satellite Visible Imagery: A Review; Springer-Verlag: New York, NY, USA, 1983; pp. 1–114.
[7]
Aiken, J.; Moore, G.F.; Trees, C.C.; Hooker, S.B.; Clark, D.K. The SeaWiFS CZCS-Type Pigment Algorithm. In SeaWiFS Technical Report Series; Hooker, S.B., Firestone, E.R., Eds.; NASA Goddard Space Flight Center: Greenbelt, MD, USA, 1995; Volume 29, pp. 1–34.
[8]
O’Reilly, J.E.; Maritorena, S.; Mitchell, B.G.; Siegel, D.A.; Carder, K.L.; Garver, S.A.; Kahru, M.; McClain, C. Ocean color chlorophyll algorithms for SeaWiFS. J. Geophys. Res 1998, 103, 24937–24953.
[9]
O’Reilly, J.E.; Maritorena, S.; Mitchell, B.G.; Siegel, D.A.; Carder, K.L.; Garver, S.A.; Kahru, M.; McClain, C. Ocean Color Chlorophyll a Algorithms for SeaWiFS, OC2, and OC4: Version 4. In SeaWiFS Postlaunch Technical Report Series, Volume 11, SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3; Hooker, S.B., Firestone, E.R., Eds.; NASA Goddard Space Flight Center: Greenbelt, MD, USA, 2000; pp. 9–23.
[10]
Carder, K.L.; Steward, R.G.; Harvey, G.R.; Ortner, P.B. Marine humic and fulvic acids: Their effects on remote sensing of ocean chlorophyll. Limnol. Oceanogr 1989, 34, 68–81.
[11]
Gallegos, C.L.; Correll, D.L.; Pierce, J.W. Modeling spectral diffuse attenuation, absorption, and scattering coefficients in a turbid estuary. Limnol. Oceanogr 1990, 35, 1486–1502.
[12]
Ritchie, J.C.; Schiebe, F.R.; Cooper, C.M.; Harrington, J.A., Jr. Chlorophyll measurements in the presence of suspended sediment using broad band spectral sensors aboard satellites. J. Freshwater Ecol 1994, 9, 197–206.
[13]
Schalles, J.F.; Sheil, A.T.; Tycast, J.F.; Alberts, J.J.; Yacobi, Y.Z. Detection of Chlorophyll, Seston, and Dissolved Organic Matter in the Estuarine Mixing Zone of Georgia Coastal Plain Rivers. Proceedings of the Fifth International Conference on Remote Sensing for Marine and Coastal Environments, San Diego, CA, USA, 5–7 October 1998; pp. 315–324.
[14]
Gons, H.J. Optical tele-detection of chlorophyll a in turbid inland waters. Environ. Sci. Technol 1999, 33, 1127–1132.
[15]
Hladik, C.M. Close Range, Hyperspectral Remote Sensing of Southeastern Estuaries and an Evaluation of Phytoplankton Chlorophyll-a Predictive AlgorithmsM.Sc. Thesis. Creighton University, Omaha, NE, USA, 2004.
[16]
Vertucci, F.A.; Likens, G.E. Spectral reflectance and water quality of Adirondack mountain region lakes. Limnol. Oceanogr 1989, 34, 1656–1672.
[17]
Schalles, J.F.; Gitelson, A.A.; Yacobi, Y.Z.; Kroenke, A.E. Estimation of chlorophyll a from time series measurements of high spectral resolution reflectance in an eutrophic lake. J. Phycol 1998, 34, 383–390.
[18]
Thiemann, S.; Kaufmann, H. Lake water quality monitoring using hyperspectral airborne data—A semiempirical multisensor and multitemporal approach for the Mecklenburg Lake District, Germany. Remote Sens. Environ 2002, 81, 228–237.
[19]
Kallio, K.; Koponen, S.; Pulliainen, J. Feasibility of airborne imaging spectrometry for lake monitoring—A case study of spatial chlorophyll-a distribution in two meso-eutrophic lakes. Int. J. Remote Sens 2003, 24, 3771–3790.
[20]
McGlathery, K.J.; Sundback, K.; Anderson, I.C. Eutrophication in shallow coastal bays and lagoons: the role of plants in coastal filter. Marine Ecol. Prog. Series 2007, 348, 1–18.
[21]
Morel, A.; Prieur, L. Analysis of variations in ocean color. Limnol. Oceanogr 1977, 22, 709–722.
[22]
Wu, M.; Zhang, W.; Wang, X.; Luo, D. Application of MODIS satellite data in monitoring water quality parameters of Chaohu Lake in China. Environ. Monit. Assess 2009, 148, 255–264.
[23]
Vietnam Environment Protection Agency (VEPA), World Conservation Union (IUCN), Mekong Wetlands Biodiversity Conservation and Sustainable Use Programme (MWBP). Overview of Wetland Status in Vietnam following 15 Years of Ramsar Convention Implementation; VEPA: Hanoi, Vietnam, 2005; pp. 1–80.
[24]
Hoang, V.T.; Pham, V.H. Biodiversity in Coastal Zones of Tien Yen—Dam Ha, Quang Ninh Province and Conservation. Proceeding of the 2nd Vietnam National Conference on Biodiversity (in Vietnamese), Hanoi, Vietnam, 17 October 2010; pp. 61–74.
[25]
Thuoc, C.V. Phytoplankton in the Tien Yen, Bach Dang and Red River mouths. Marine Resour. Environ 1996, 3, 242–248.
[26]
American Public Health Association (APHA). Standard Methods for the Examination of Water and Wastewater, 20th ed. ed.; American Public Health Association: Washington, DC, USA, 1998; pp. E1–E15.
[27]
Department of Environment, Climate Change and Water NSW. Waterwatch Estuary Field Mannual: A Manual for On-Site Use in the Monitoring of Water Quality and Estuary Health; Department of Environment, Climate Change and Water NSW: Sydney, Australia, 2010; pp. 2_6–2_7.
[28]
Vietnam Ministry of Natural Resources and Environment. Vietnam Topographic Map. Scale 1/50,000;; Department of Survey Map Publishing House: Hanoi, Vietnam, 2004.
[29]
Chavez, J.P.S., Jr. An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sens. Environ 1988, 24, 459–479.
[30]
Bernstein, L.S.; Adler-Golden, S.M.; Sundberg, R.L.; Levine, R.Y.; Perkins, T.C.; Berk, A.; Ratkowski, A.J.; Felde, G.; Hoke, M.L. A New Method for Atmospheric Correction and Aerosol Optical Property Retrieval for VIS-SWIR Multi- and Hyperspectral Imaging Sensors: QUAC (QUick Atmospheric Correction). Proceedings of IEEE International Geosciences and Remote Sensing Symposium, Seoul, Korea, 25–27 July 2005; pp. 3549–3552.
[31]
Hadjimitsis, D.G.; Clayton, C.R.I.; Hope, V.S. An assessment of the effectiveness of atmospheric correction algorithms through the remote sensing of some reservoirs. Int. J. Remote Sens 2004, 25, 3651–3674.
[32]
Hadjimitsis, D.G.; Clayton, C.R.I. Field spectroscopy for assisting water quality monitoring and assessment in water treatment reservoirs using atmospheric corrected satellite remotely sensed imagery. Remote Sens 2011, 3, 362–377.
[33]
Ha, N.T.T.; Koike, K. Integrating satellite imagery and geostatistics of point samples for monitoring spatio-temporal changes of total suspended solids in bay waters: application to Tien Yen Bay (Northern Vietnam). Frontiers Earth Sci 2011, 5, 305–316.
[34]
Moses, W.J.; Gitelson, A.A.; Berdnikov, S.; Povazhnyy, V. Estimation of chlorophyll-a concentration in case II waters using MODIS and MERIS data-successes and challenges. Environ. Res. Lett 2009, 4, doi:10.1088/1748-9326/4/4/045005.
[35]
Carder, K.L.; Chen, F.R.; Cannizzaro, J.P.; Campbell, J.W.; Mitchell, B.G. Performance of the MODIS semi-analytical ocean color algorithm for chlorophyll-a. Adv. Space Res 2004, 33, 1152–1159.
[36]
Gitelson, A. The Peak near 700 nm on Radiance Spectra of algae and water - Relationships of its magnitude and position with chlorophyll concentration. Int. J. Remote Sens 1992, 13, 3367–3373.
[37]
Antoite, D.; Andre, J.M.; Morel, A. Oceanic primary production 2: Estimation of global scale from satellite (coastal zone color scanner) chlorophyll. Glob. Biogeochem. Cy 1996, 10, 57–69.
[38]
D’Sa, E.J.; Miller, R.L. Bio-optical properties in waters influenced by the Mississippi River during low flow conditions. Remote Sens. Environ 2002, 84, 538–549.
[39]
Dall’Olmo, G.; Gitelson, A.A.; Rundquist, D.C. Toward a unified approach for remote estimation of chlorophyll-a in both terrestrial vegetation and turbid productive waters. Geophys. Res. Lett 2003, 30, 1938–1941.
[40]
Gilerson, A.A; Gitelson, A.A.; Zhou, J.; Gurlin, D.; Moses, W.; Ioannou, I.; Ahmed, S. Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near infrared bands. Opt. Express 2010, 18, 24109–24125.
[41]
Lee, Z.P.; Carder, K.L.; Hawes, S.H.; Steward, R.G.; Peacock, T.G.; Davis, C.O. A model for interpretation of hyperspectral remote-sensing reflectance. Appl. Opt 1994, 33, 5721–5732.
[42]
Gordon, H.R.; Brown, O.B.; Jacobs, M.M. Computed relationships between the inherent and apparent optical properties of a flat homogeneous ocean. Appl. Opt 1975, 14, 417–427.
[43]
Jerome, J.H.; Bukata, R.P.; Burton, J.E. Utilizing the components of vector irradiance to estimate the scalar irradiance in natural waters. Appl. Opt 1988, 27, 4012–4018.
[44]
Kirk, J.T.O. Volume scattering function, average cosines, and the underwater light field. Limnol. Oceanogr 1991, 36, 455–467.
[45]
Barnard, A.H.; Ronald, J.; Zaneveld, V.; Pegau, S.W. In situ determination of the remotely sensed reflectance and the absorption coefficient: Closure and inversion. Appl. Opt 1999, 38, 5108–5117.
[46]
Carder, K.L.; Chen, F.R.; Lee, Z.; Hawes, S.K.; Cannizzaro, J.P. Case 2 Chlorophyll a. In MODIS Ocean Science Team Algorithm Theoretical Basis Document; Version 7; NASA Goddard Space Flight Center: Greenbelt, MD, USA, 2003; pp. 4–67.
[47]
Morel, A. Optical Properties of Pure Water and Pure Seawater. In Optical Aspects of Oceanography; Jerlov, N.G., Nielson, E.S., Eds.; Academic Press: London, UK, 1974; pp. 1–24.
[48]
Smith, R.C.; Baker, K.S. Optical properties of the clearest natural waters (200–800 nm). Appl. Opt 1981, 20, 177–184.
[49]
Twardowski, M.S.; Claustre, H.; Freeman, S.A.; Stramski, D.; Huot, Y. Optical backscattering properties of the “clearest” natural waters. Biogeosciences 2007, 4, 1041–1058.
[50]
McKee, D.; Cunningham, A.; Slater, J.; Jones, K.J.; Griffiths, C.R. Inherent and apparent optical properties in coastal waters: A study of the Clyde Sea in early summer. Estuar. Coast. Shelf Sci 2002, 56, 369–376.
[51]
McKee, D.; Cunningham, A. Identification and characterisation of two optical water types in the Irish Sea from in situ inherent optical properties and seawater constituents. Estuar. Coast. Shelf Sci 2006, 68, 305–316.
[52]
Whitmire, A.L.; Boss, E.; Cowles, T.J.; Pegau, W.S. Spectral variability of the particulate backscattering ratio. Opt. Expr 2007, 15, 7019–7031.
[53]
Park, Y.J; Ruddick, K. Model of remote-sensing reflectance including bidirectional effects for case 1 and case 2 waters. Appl. Opt 2005, 44, 1236–1249.
[54]
Babin, M.; Stramski, D.; Ferrari, G.M.; Claustre, H.; Bricaud, A.; Obolensky, G.; Hoepffner, N. Variations in the light absorption coefficients of phytoplankton, non-algal particles, and dissolved organic matter in coastal waters around Europe. J. Geophys. Res 2003, 108, 4_1–4_20.
[55]
Fishwick, J.R.; Aiken, J.; Barlow, R.G.; Sessions, H.; Bernard, S.; Ras, J. Functional relationships and bio-optical properties derived from phytoplankton pigments, optical and photosynthetic parameters; a case study of the Benguela ecosystem. J. Mar. Biol. Assoc. UK 2006, 86, 1267–1280.
[56]
Hirata, T.; Aiken, J.; Hardman-Mountford, N.; Smyth, T.J.; Barlow, R.G. An absorption model to determine phytoplankton size classes from satellite ocean colour. Remote Sens. Environ 2009, 112, 3153–3159.
[57]
Carder, K.L.; Cannizzaro, J.P.; Lee, Z. Ocean color algorithms in optically shallow waters: Limitation and improvements. Proc. SPIE 2005, 5885, doi:10.1117/12.615039.
[58]
Cannizzaro, J.P.; Carder, K.L. Estimating chlorophyll a concentration from remote-sensing reflectance in optically shallow waters. Remote Sens. Environ 2006, 101, 13–24.
[59]
Aiken, J.; Pradhan, Y.; Barlow, R.G.; Lavender, S.; Poulton, A.; Holligan, P.M.; Hardman-Mountford, N. Phytoplankton pigments and functional types in the Atlantic Ocean: A decadal assessment, 1995–2005. Deep-Sea Res. Part II: Top. Stud. Oceanogr 2009, 56, 899–917.
[60]
Cressie, N.A.C. Statistics for Spatial Data; John Wiley & Sons, Inc: New York, NY, USA, 1993; pp. 1–900.
[61]
Kanaroglou, P.S.; Soulakellis, N.A.; Sifakis, N.I. Improvement of satellite derived pollution maps with the use of a geostatistical interpolation method. J. Geogr. Syst 2001, 4, 193–208.
[62]
Zhang, C.; Li, W.; Travis, D. Restoration of clouded pixels in multispectral remotely sensed imagery with co-kriging. Int. J. Remote Sens 2009, 30, 2173–2195.
[63]
Meng, Q.; Borders, B.; Madden, M. High-resolution satellite image fusion using regression kriging. Int. J. Remote Sens 2010, 31, 1857–1876.
[64]
Petrie, G.M.; Heasler, P.G.; Perry, E.M.; Thompson, S.E.; Daly, D.S. Inverse kriging to enhance spatial resolution of imagery. Proc. SPIE 2002, 4789, doi:10.1117/12.454822.
[65]
Wang, X.J.; Liu, R.M. Spatial analysis and eutrophication assessment for chlorophyll a in Taihu Lake. Environ. Monit. Assess 2005, 101, 167–74.
[66]
Müller, D. Estimation of Algae Concentration in Cloud Covered Scenes Using Geostatistical Methods. Proceeding of ENVISAT Symposium 2007, Montreux, Switzerland, 23–27 April 2007.
[67]
Georgakarakos, S.; Kitsiou, D. Mapping abundance distribution of small pelagic species applying hydroacoustics and Co-Kriging techniques. Hydrobiologia 2008, 612, 155–169.
[68]
Saulquin, B.; Gohin, F.; Garrello, R. Regional objective analysis for merging high-resolution MERIS, MODIS/Aqua, and SeaWiFS Chlorophyll-a data from 1998 to 2008 on the European Atlantic Shelf. IEEE Trans. Geosci. Remote Sens 2010, 49, 143–154.
[69]
Shehhi, M.R.A.; Gherboudj, I.; Estima, J.; Ghedira, H. Geospatial Analysis of the Red-Tide over the Arabian Gulf. Proceeding of the 1st Geospatial Scientific Summit, Dubai, United Arab Emirates, 12–13 November 2012.
[70]
Agrawal, G.; Sarup, J. Comparision of QUAC and FLAASH atmospheric correction modules on EO-1 Hyperion data of Sanchi. Int. J. Adv. Eng. Sci. Technol 2011, 4, 178–186.
[71]
Simboura, N.; Panayotidis, P.; Papathanassiou, E. A synthesis of the biological quality elements for the implementation of the European Water Framework Directive in the Mediterranean ecoregion: The case of Saronikos Gulf. Ecol. Indic 2005, 5, 253–266.
[72]
Morton, B.; Blackmore, G. South China Sea. Mar. Pollut. Bull 2001, 42, 1236–1263.
[73]
Quangninh Province Statistics Office. Quangninh. Statistical Yearbook 1955–2011; Statistical Publishing House: Hanoi, Vietnam, 2012; pp. 1–548.
[74]
Lihan, T.; Mustapha, M.A.; Rahim, S.A.; Saitoh, S.; Iida, K. Influence of river plume on variability of chlorophyll a concentration using satellite images. J. Appl. Sci 2011, 11, 484–493.
[75]
CSTT (Comprehensive Study Task Team of Group Coordinating Sea Disposal Monitoring). Comprehensive Studies for the Purposes of Article 6 & 8.5 of DIR 91/271 EEC, the Urban. Waste Water Treatment Directive, 2nd ed. ed.; The Scottish Environment Protection Agency and Water Service Association: Edinburgh, UK, 1997; pp. 8–11.
[76]
Cannizzaroa, J.P.; Cardera, K.L.; Chena, F.R.; Heilb, C.A.; Vargoa, G.A. A novel technique for detection of the toxic dinoflagellate, Kareniabrevis, in the Gulf of Mexico from remotely sensed ocean color data. Cont. Shelf Res 2008, 28, 137–158.
