Assessment of Chlorophyll-A, SST and Diffuse Attenuation Coefficient (Kd490) in Northwest of Persian Gulf using Landsat 8 Satellite Data

Assessment of Chlorophyll-A, SST and Diffuse Attenuation Coefficient (Kd490) in Northwest of Persian Gulf using Landsat 8 Satellite Data

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Author(s): Laleh Mosavi Dehmordi, Ahmad Savari, A Dostshenas, H Mohamad Asgari, Alireza Abasi

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DOI: 10.18483/ijSci.953 710 934 10-26 Volume 5 - May 2016


The objective of this research was to develop a model for estimating chlorophyll-a, SST and kd(490) on the Northwest Persian gulf water using relatively high resolution landsat8 image. A field compaign were conducted in Feb, March, April, May, July, Agust, Oct and Nov of 2014 concurrent to satellite over-pass. The field work were conducted of Mahshar estuary between Feb, 14th to Nov, 13th, 2014. Temperature, Secchi disk depth, chl-a, kd and zeu was measured in this study. We tested various regression models using combinations of bands. The regression models showed acceptable correlation and accuracy. The Chl-a concentrations ranged from 0.6 to 1.8 mg m−3, with an average of 1.01 ± 0.32 mg m−3. The values for Kd(490) were highest(0.86) in July and lowest (0.59m) in February. Deeper Zeu are observed in Feb (7.8m) and Shallower Zeu were observed in July (5.3m). The study of SST algorithm model for Landsat-8 data has been conducted using the method approached to SST derived from calibrated landsat8 data. The retrieval accuracy (R2) was 0.63, while the root mean square (RMSE) was 0.81. The highest (31c°) temperature was found in July and lowest temperature(15.1c°) was found in Feb. The approach employed in this research indicates that remote sensing is a valuable, low-cost and stable tool for water quality monitoring of estuary health.


Landsat8, Chl-a, SST, kd(490), zeu


  1. Arismendez, S., Kim, J., and Montagna, P., 2009. Application of watershed analyses and ecosystem modeling to investigate land-water nutrient coupling processes in the Guadalupe estuary, Texas, Ecological Informatics, 4(9): 243-253.
  2. Baban,S.,1997. Environmental Monitoring of Estuaries; Estimating and Mapping Various Environmental Indicators in Breydon Water Estuary, U.K., Using Landsat TM Imagery. Estuarine, Coastal and Shelf Science 44(2): 589–598.
  3. Chauhan, P., Nagur, C. R. C., Mohan, M., Nayak, S. R., and Navalgund, R. R., 2001. Surface chlorophyll distribution in Arabian Sea and Bay of Bengal using IRS-P4 ocean color monitor satellite data. Current Science, 80(6): 127– 129.
  4. Chen, C., P. Shi, and Q. Mao., 2003. Application of remote sensing techniques for monitoring the thermal pollution of cooling-water discharge from nuclear power plant. Journal Environmental Science Healthy,8(8): 1659-1668.
  5. Cheshire, H. M., Khorram, S. and Brockhans, J. A., 1985. Monitoring estuarine water quality from Landsat TM. International Conference on Advanced Technology for Monitoring and Processing Global Environmental Data, London U.K., pp 10-12.
  6. Duarte, C. M., 1991. Seagrass depth limits. Aquatic Botany, 40(7):363–377.
  7. KhalfehNilsaz, A., 1998. Investigation of primary production in Mahshahr creeks. MSc. thesis, Khoramshahr University of Science and Technology, 178 pp.
  8. Kim,S., Kim,H .,Sin,J., Park, S., Park, K.2014. High resolution ocean color products estimation in fjord of Svalbard, Arctic sea. EARSeL 34th Symposium Proceedings, 16-20 June.
  9. Lee, Z. P., Darecki, M., Carder, K., Davis, C., Stramski, D., and Rhea, W.,2005. Diffuse attenuation coefficient of downwelling irradiance: An evaluation of remote sensing methods. Journal of Geophysical Research, 11(5):12-23.
  10. McMillin, L.M., 1975. Estimation of Sea Surface Temperatures from Two Infrared Window Measurements with Different Absorption. Journal of Geophysic Research, 80(12): 5113–5117.
  11. Morel A, Berthon J F.,1989. “Surface pigments, algal biomass profiles and potential production of the euphotic layer: Relationships reinvestigated in view of remote-sensing applications”. Limnological Oceanogry,34, pp. 1545-1562.
  12. Moabed, P., Rangzan,K., Savari, A., Khaledi,H., 2006. An overview of temporal and spatial patterns in satellite- derived chlorophyll imagery.Journal of marine biology.4(2):34-45.
  13. Ritchie, J.C. and Cooper, C.M., 2001. Remote sensing techniques for determining water quality: Application to TMDLs. In: TMDL Science Issues Conference, WaterEnvironment Federation, Alexandria, VA. 367-374p.
  14. Suga, Y., Ogawa, H., Ohno, K., and Yamada, K., 2003. Detection of surface temperature from Landsat 7/ETM+. Advance. Space Research., 32(11):2235-2240.
  15. Schott, J.R., 1982. An application of heat capacity mapping mission data: thermal bar studies of Lake Ontario. Journal Applied Photography Engeeniring, 8(3):117-120.
  16. Schott, J.R., Barsi, J.A., Nordgren, B.L., Raqueٌo, N.G and de Alwis, D., 2001. Calibration of
  17. Landsat thermal data and application to water resource studies. Remote Sensing of Environment,78 (12):108-117.
  18. Stumpf, R.P. and Tayler, M.A., 1988. Satellite detection of bloom and pigment distributions in estuaries. Remote Sensing of Environment 24(9): 385–404.
  19. Thomas, A., Byrne, D. and Weatherbee, R., 2002. Coastal sea surface temperature variability from Landsat infrared data. Remote Sensing of Environment,81(3):262-272.
  20. Wang,M. H., Shi,W., and Tang, J.W., 2011. Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements. Remote Sensing of Environment, 115(11):841–854.

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International Journal of Sciences is Open Access Journal.
This article is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
Author(s) retain the copyrights of this article, though, publication rights are with Alkhaer Publications.

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