Spectral Geometric Triangle Properties of Chlorophyll-A Inversion in Taihu Lake Based on TM Data

Jun Chen, Zhenhe Wen, Zhengqing Xiao

.

DOI: 10.4236/jwarp.2011.31008                

Abstract

The main objective of this study was to develop and validate the applicability of the Area Chlorophyll-a Concentration Retrieved Model (ACCRM), Height Chlorophyll-a Concentration Retrieved Model (HCCRM), Angle Chlorophyll-a Concentration Retrieved Model (AgCCRM), and Ratio Model of TM2/TM3 (RM) in estimating the chlorophyll-a concentration in Case II water bodies, such as Taihu Lake in Jiangsu Province, China. Water samples were collected from 23 stations on the 27th and 28th of October, 2003. The four empirical models were calibrated against the calibration dataset (samples from 19 stations) and validated using the validation dataset (samples from 4 stations). The regression analysis showed higher correlation coefficients for the ACCRM and the HCCRM than for the AgCCRM and the Ratio Model; and the HCCRM was slightly superior to the ACCRM. The performance of the ACCRM and the HCCRM was validated, and the ACCRM underestimated concentration values more than the HCCRM. The distribution of chlorophyll-a concentrations in Taihu Lake on October 27, 2003 was estimated based on the Landsat/TM data using the ACCRM and the HCCRM. Both models indicated higher chlorophyll-a concentrations in the east, north and center of the lake, but lower concentrations in the south. The accuracy of results obtained from the HCCRM and the ACCRM were also supported by the validation dataset. The study revealed that the HCCRM and the ACCRM had the best potential for accurately assessing the chlorophyll-a concentration in the highly turbid water bodies.

Keywords

Water Quality, Remote Sensing, Invsersion Model, Chlorophyll-a Concentration, Taihu Lake

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	D. G. George, “The Airborne Remote Sensing of Phytoplankton Chlorophyll-A in the Lakes and Tarns of the English Lake District,” International Journal of Remote Sensing, Vol. 18, No. 9, 1997, pp. 1961-1975. doi:10.1080/014311697217972
[2]	P. A. Tester and R. P. Stumpf, “Phytoplankton Blooms and Remote Sensing: What is the Potential for Early Warning,” Journal of Shellfish Resources, Vol. 17, No. 5, 1998, pp. 1469-1471.
[3]	J. B. Michael and B. Emmanuel, “The Beam Attenuation to Chlorophyll-A Ratio: An Optical Index of Phytoplankton Physiology in the Surface Ocean,” Deep-Sea Research, Vol. 50, 2003, pp. 1537-1549.
[4]	L. H. Kantha, “A General Ecosystem Model of for Applications to Primary Productivity and Carbon Cycle Studies in the Global Oceans,” Ocean Modeling, Vol. 6, No. 3-4, 2004, pp. 285-334. doi:10.1016/S1463-5003(03)00022-2
[5]	A. Morel and L. Prieur, “Analysis of Variances in Ocean Color,” Limnology and Oceanography, Vol. 22, 1977, pp. 709-722. doi:10.4319/lo.1977.22.4.0709
[6]	H. R. Gordon and A. Y. Morel. “Remote Assessment Ocean for Color Interpretation of Satellite Visible Imagery,” 1st Edition, New York, Springer Verlag, England, 1983, pp. 31-107.
[7]	C. D. Mobley, “Light and Water: Radiative Transfer in Natural Waters,” 1st Edition, Academic Press, London, England, 1994, pp. 21-69.
[8]	S. Tassan, “A Numerical Model for the Detection of Sediment Concentration in Stratified River Plumes Using Thematic Mapper Data,” Internal Journal of Remote Sensing, Vol. 18, No. 12, 1997, pp. 2699-2705. doi:10.1080/014311697217567
[9]	P. Chauhan, M. Mohan, R. K. Sarngi, B. Kumari and S. G. P. Matondkar, “Surface Chlorophyll-A Estimation in the Arabian Sea Using IRS-P4 Ocean Colour Monitor (OCM) Satellite Data,” Internal Journal of Remote Sensing, Vol. 23, No. 8, 2002, pp. 1663-1676. doi:10.1080/01431160110075866
[10]	H. R. Gordon, O. B. Brown, R. H. Evans, J. W. Brown, R. C. Smith, K. S. Baker and D. K. Clark. “A Semi-Analytic Radiance Model of Ocean Color,” Journal of Geophysical Research, Vol. 93, No. D9, 1988, pp. 10909-10924. doi:10.1029/JD093iD09p10909
[11]	I. Joint and S. B. Groom, “Estimation of Phytoplankton Production from Space: Current Status and Future Potential of Satellite Remote Sensing,” Journal of Experimental Marine Biology and Ecology, Vol. 250, No. 1, 2000, pp. 233-255. doi:10.1016/S0022-0981(00)00199-4
[12]	C. F. Le, Y. M. Li, Y. Zha, D. Y. Sun, C. C. Huang and H. Lu, “A Four-Band Semi-Analytical Model for Estimating Chlorophyll-A in Highly Turbid Lakes: The Case of Taihu Lake, China,” Remote Sensing of Environment, Vol. 113, No. 6, 2009, pp. 1175-1182. doi:10.1016/j.rse.2009.02.005
[13]	H. J. Gons, M. Rijkeboer, S. Bagheri and K. G. Ruddick, “Optical Teledetection of Chlorophyll-A in Estuarine and Coastal Waters,” Environmental Science and Technology, Vol. 34, No. 24, 2000, pp. 5189-5192. doi:10.1021/es0012669
[14]	S. Tiemann and H. Kaufman, “Determination of Chlorophyll-A Contentand Tropic State of Lakes Using Field Spectralmeter and IRS-IC Satellite Data in Mecklenburg Lake Distract, Germany,” Remote Sensing of Environment, Vol. 73, No. 2, 2000, pp. 227-235.
[15]	A. A. Gitelson, G. D. Olmo, W. Moses, D. C. Rundquist, T. Barrow, T. R. Fisher, D. Gurlin and J. Holz, “A Simple Semi-Analytical Model for Remote Estimation of Chlorophyll-A in Turbid Waters; Validation,” Remote Sensing of Environment, Vol. 112, No. 9, 2008, pp. 3582-3593. doi:10.1016/j.rse.2008.04.015
[16]	G. K. Yew-Hoong, S. T. Koh, I. I. Lin and E. S. Chan, “Application of Spectral Signatures and Colour Ratios to Estimate Chlorophyll-A in Singapore’S Coastal Waters,” Journal of Photogrammetry and Remote Sensing, Vol. 55, 2001, pp. 719-748.
[17]	A. G. Dekker, R. J. Vos and S. W. M. Peters, “Analytical Algorithms for Lake Water TSM Estimation for Retrospective Analysis of TM and SPOT Sensor Data,” International Journal of Remote Sensing, Vol. 23, No. 1, 2002, pp. 15-35. doi:10.1080/01431160010006917
[18]	G. Dall’Olmo and A. A. Gitelson, “Effect of Bio-Optical Parameter Variability and Uncertainties in Reflectance Measurements on the Remote Sensing Estimation Of Chlorophyll-A Concentration in Turbid Productive Waters: Modeling Results,” Applied Optics, Vol. 45, No. 15, 2006, pp. 3577-3592. doi:10.1364/AO.45.003577
[19]	Y. L. Zhang, B. Zhang, X. L. Wang, S. Feng and Q. H. Zhao, “A Study of Absorption Characteristics of Chromophoric Dissolved Organic Matter and Particles in Lake Taihu, China,” Hydrobiologia, Vol. 592, 2007, pp. 105- 120. doi:10.1007/s10750-007-0724-4
[20]	ASD, “Analytic Spectral Devices, Inc. Technical Guide,” 3rd Edition, Boulder, Colorado, 1999.
[21]	J. L. Mueller and R. W. Austin, “Ocean Optics Protocols for Seawifs Validation,” NASA Techmical Memorandum 104566, Greenbelt, MD, NASA Goddard Space Flight Center, 1992.
[22]	K. Y. Ding and H. R. Gordon, “Atmospheric Correction of Ocean-Color Sensors: Effects of the Earth’S Curvature,” Applied Optics, Vol. 33, No. 30, 1994, pp. 7096- 7106. doi:10.1364/AO.33.007096
[23]	H. R. Gordon and M. H. Wang, “Retrieval of Water- Leaving Radiance and Aerosol Optical Thickness over the Oceans with Seawifs: A Preliminary Algorithm,” Applied Optics, Vol. 33, No. 3, 1994, pp. 443-452. doi:10.1364/AO.33.000443
[24]	H. R. Gordon and D. K. Clark, “Clear Water Radiances for Atmospheric Correction of Coastal Zone Color Scanner Imagery,” Applied Optics, Vol. 20, No. 24, 1981, pp. 4175-4180. doi:10.1364/AO.20.004175
[25]	M. Putsay, “A Simple Atmospheric Correction Method for the Short Wave Satellite Image,” International Journal of Remote Sensing, Vol. 13, No. 8, 1992, pp. 1549- 1558. doi:10.1080/01431169208904208
[26]	H. Ouaidrari and E. F. Vernote, “Operational Atmospheric Correction of Landsat TM Data,” Remote Sensing of Environment, Vol. 70, 1999, pp. 4-15. doi:10.1016/S0034-4257(99)00054-1
[27]	J. R. Apel, “An Improved Model of the Ocean Surface Wave Vector Spectrum and Its Effects on Radar Backscatter,” Journal of Geophysical Research, Vol. 99, No. C8, 1994, pp. 16269-16291. doi:10.1029/94JC00846
[28]	W. H. Farrand, R. B. Singer and E. Merenyi, “Retrieval of Apparent Surface Reflectance from AVIRIS Data: A Comparison of Empirical Line, Radiative Transfer, and Spectral Mixture Methods,” Remote Sensing of Environment, Vol. 47, No. 3, 1994, pp. 311-321. doi:10.1016/0034-4257(94)90099-X
[29]	G. Ferrier, “Evaluation of Apparent Surface Reflectance Estimation Methodologies,” International Journal of Remote Sensing, Vol. 17, No. 12, 1995, pp. 2291-2297. doi:10.1080/01431169508954557
[30]	IOCCG, “Remote Sensing of Inherent Optical Properties: Fundamentals, Tests of Algorithms, and Applications,” No. 3. S. Sathyendranath. Dartmouth, 2006.
[31]	D. P. Shrestha, D. E. Margate, F. V. D. Meer and H. V. Anh, “Analysis and Classification Of Hyperspectral Data for Mapping Land Degradation: An Application in South- ern Spain,” International Journal of Applied Earth Observation, Vol. 7, No. 2, 2005, pp. 85-96. doi:10.1016/j.jag.2005.01.001
[32]	S. J. Walsh, A. L. McCleary, C. F. Mena, Y. Shao, J. P. Tuttle, A. González and R. Atkinson, “Quickbird and Hyperion Data Analysis of an Invasive Plant Species in the Galapagos Islands of Ecuador: Implications for Control and Land Use Management,” Remote Sensing of Environment, Vol. 112, No. 5, 2008, pp. 1927-1941. doi:10.1016/j.rse.2007.06.028
[33]	P. B. Robert, S. Alexander and Y. K. Kirill, “Optical Properties and Remote Sensing of Inland and Coastal Waters,” 1st Edition, CRC Press, New York, 1995
[34]	C. D. Vries, T. Danaher, R. Denham, R. Scarth and S. Phinn, “An Operational Radiometric Calibration Procedure for the Landsat Sensors Based on Pseudo-Invariant Target Sites,” Remote Sensing of Environment, Vol. 107, No. 3, 2007, pp. 414-429. doi:10.1016/j.rse.2006.09.019