Thử nghiệm mô hình hóa sự phân bố không gian của hàm lượng chlorophyll-a và chỉ số trạng thái phú dưỡng nước Hồ Tây sử dụng ảnh Sentinel-2A
Main Article Content
Abstract
Tóm tắt:Tính toán hàm lượng chlorophyll-a trong nước sử dụng dữ liệu ảnh vệ tinh là một trong những ứng dụng cơ bản của công nghệ viễn thám cho môi trường nước. Giám sát sự phân bố và biến động hàm lượng chlorophyll-a trong nước giúp chúng ta hiểu rõ trạng thái và quá trình phú dưỡng diễn ra trong nước hồ. Nghiên cứu này sử dụng các kết quả đo hiện trường và phân tích ảnh vệ tinh Sentinel-2A thu được trong tháng 6/2016 để xây dựng phương trình tính toán hàm lượng chlorophyll-a trong nước Hồ Tây. Kết quả bước đầu cho thấy hàm lượng chlorophyll-a trong nước hồ có quan hệ chặt chẽ với tỷ số kênh 5 trên kênh 4 của ảnh Sentinel-2A bằng phương trình hàm mũ (r2=0,78, sai số trung bình 0,12). Sơ đồ phân bố hàm lượng chlorophyll-a và chỉ số trạng thái phú dưỡng (TSI) tương ứng của nước Hồ Tây góp phần giải thích hiện tượng cá chết được ghi nhận tại hồ vào đầu tháng 7/2016. Phương pháp và dữ liệu ảnh Sentinel-2A trình bày trong nghiên cứu thử nghiệm này cần được kiểm chứng và áp dụng cho các hồ khác tại Hà Nội để quản lý có hiệu quả hơn chất lượng nước và giảm thiểu ô nhiễm môi trường ở các hồ.
Từ khóa:Viễn thám, chlorophyll-a, phú dưỡng, Hồ Tây, Sentinel-2A.
References
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[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: Richardson L. L. and LeDew E.F., editors, Remote sensing of Aquatic Coastal Ecosystem Processes: Science and Management Application. Netherlands: Springer, 27-78, 2009.
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[7] Palmer, S.C.J., Kutser, T., Peter, D.H., Remote sensing of inland waters: Challenges, progress and future directions. Remote Sensing of Environment, 157, pp. 1-8, 2014.
[8] Toming K., Kutser T., Laas A., Sepp M., Paavel B., and Nõges T., 2016. First Experiences in Mapping Lake Water Quality Parameters with Sentinel-2 MSI Imagery. Remote Sens, 2016.
[9] Vanhellemont Q., and Ruddick K., Acolite for Sentinel-2: Aquatic Applications of MSI Imagery. The proceedings of the 2016 ESA Living Planet Symposium, Prague, Czech Republic, 9-13 May 2016, ESA Special Publication SP-740, 2016.
[10] Bukata, R.P., Bruton, J.E., Jerome, J.H., Jain, S.C., Zwick, H.H., Optical water quality model of Lake Ontario. 2: Determination of chlorophyll a and suspended mineral concentrations of natural waters from submersible and low altitude optical sensors. Applied Optics, 20, pp. 1704-1714, 1981.
[11] Dekker, A.G., Malthus, T., Seyhan, E., Quantitative modelling of inland water quality for high-resolution MSS systems. IEEE Transactions on Geoscience and Remote Sensing, 29, pp. 89-95, 1991.
[12] Gitelson, A., Gurlin, D., Moses, W.J., Barrow, T., A bio-optical algorithm for the remote estimation of the chlorophyll-a concentration in case 2 waters. Environmental Research Letters, 4/045003, pp. 5, 2009.
[13] 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. International Journal of Remote Sensing, 24, pp. 3771-3790, 2003.
[14] Koponen, S., Attila, J., Pulliainen, J., Kallio, K., Pyhälahti, T., Lindfors, A., A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland. Continental Shelf Research, 27, pp. 228-244, 2007.
[15] Matthews, M.W., Bernard, S., Winter, K., Remote sensing of cyanobacteria-dominant algal blooms and water quality parameters in Zeekoevlei, a small hypertrophic lake, using MERIS. Remote Sensing of Environment, 114 (9), pp. 2070-2087, 2010.
[16] Dekker, A., Detection of the optical water quality parameters for eutrophic waters by high resolution remote sensing, Ph.D. thesis, Free University, Amsterdam, The Netherlands, 1993.
[17] Gilerson, A.A., Gitelson, A.A., Zhou, J., Gurlin, D., Moses, W.J., Ioannou, I., Ahmed, S.A., Algorithms for remote estimation of chlorophyll-a in coastal and inland waters using red and near-infrared bands. Optics Express, 18, pp. 24109-24125, 2010.
[18] Gitelson, A., The peak near 700 nm on radiance spectra of algae and water: Relationships of its magnitude and position with chlorophyll concentration. International Journal of Remote Sensing, 13, pp. 3367–3373, 1992.
[19] Han, L., Rundquist, D., Comparison of NIR/RED ratio and first derivative of reflectance in estimating algal-chlorophyll concentration: a case study in a turbid reservoir. Remote Sensing of Environment, 62, pp. 253-261, 1997.
[20] Natural Environment Research Council, Post-processing field spectra in MATLAB (for GER 1500 only), 2009. Online at: http://fsf.nerc.ac.uk/user_group/post_processing_in_MATLAB/Post_processing_field_spectra_in_MATLAB.pdf (assessed on 30 May 2016).
[21] American Public Health Association (APHA), American Water Works Association, Water Environment Federation. Spectrophotometric determination of chlorophyll: 10200H.2. In Standard methods for the examination of water and wastewater, 22nd Edition; Rice, E. W., Baird, R. B., Eaton, A. D., Clesceri, L. S., Eds.; APHA: Washington, DC, USA, pp. 10-23:
10-24, 2012.
[22] Parsons, T.R., Maita, Y., Lalli, C.M., A Manual of Chemical and Biological methods for seawater analysis, Pergamon Press, Oxford, 1984.
[23] Carlson, R.E., Simpson, J., A Coordinator’s Guide to Volunteer Lake Monitoring Methods. North American Lake Management Society, Madison, WI, 1996.
[24] Chavez, P. S. J., An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data. Remote sensing of Environment, 24:
459-479, 1988.
[25] Carlson, R.E., 1977. A Trophic State Index for Lakes. Limnol Oceanography, 22, pp. 361-369.
[26] Mai Đình Yên, Tổng quan các điều tra nghiên cứu về đa dạng sinh học của hồ Tây, Báo cáo Hội thảo KH Dự án Nâng cao chất lượng nước Hồ Tây, 2001.