[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
Indexing




..
:: Volume 1, Issue 4 (12-2025) ::
Journalaer 2025, 1(4): 151-156 Back to browse issues page
A suitable algorithm for estimating chlorophyll- a using field data and satellite images in the waters of the Persian Gulf (Hormozgan Province)
Fereshteh Saraji * , Zahra Mansoori , Yousef Mousivand , Ali Salarpouri , Golamali Akbarzadeh , Hadi Kookan
Abstract:   (975 Views)
Introduction: This research was conducted to estimate the concentration of chlorophyll a using field data and satellite images and finding the appropriate algorithm.
Materials & Methods: In this research, 22 stations in the waters of the Persian Gulf of Hormozgan province, located on the coast and far from the coast, during December 2019 to December 2014, were examined monthly. Sampling of water to measure chlorophyll a was done using a Rotner bottle from half a meter below the water surface. Sentinel 3 (Sentinel 3) satellite images, which can be downloaded daily from international sites with a delay of up to 3 hours for free, were used. In this research, the difference between the collected ground chlorophyll values ​​and the values ​​obtained from different algorithms was estimated for each pixel.
Results: In the present study, the concentration of chlorophyll a in the coastal waters of Bandar Abbas was 3/391±0/118 and in the areas away from the coast 2/087±0/115 mg/m3, respectively. In coastal waters, chlorophyll a had a higher concentration. According to the field results and comparing different chl a estimation algorithms (OC4, OC5, OC6, OC4ME) and also comparing the results with the chlorophyll products of the European Space Organization OL_2_WFT among the discussed algorithms, the OC4ME algorithm has the highest coefficient of determination (R2) of 0/224 was for chlorophyll a. Based on the available results, the amount of chlorophyll a was estimated for a significant percentage of pixels with a difference of less than 2 mg/m3 compared to the actual values. In the OC4ME method, the values ​​of chlorophyll a were recorded for more than 78% of the pixels with a difference of less than 2 mg/m3 with the actual values, so they had a good relative accuracy. The results showed that the OC4ME algorithm and satellite images received from Sentinel 3 are suitable for determining the density of microalgae through chlorophyll a for the waters of the Persian Gulf (Hormozgan).
Conclusion: It is possible to monitor microalgae blooms with chlorophyll a satellite data and images with greater speed and less cost in coastal management, warning and preventing damages caused by microalgae blooms in the inlet waters of shrimp farms, the waters around fish cages and desalination water are used.
Keywords: Chlorophyll a, Satellite Images, Algorithm, Hormozgan Province
Full-Text [PDF 872 kb]   (333 Downloads)    
Type of Study: Research | Subject: Special
References
1. 1. Woldegiorgis, M.G., 2012. Quantification of primary production in Wadden Sea using remote sensing and field measurements (Master’s thesis, University of Twente). 46 p. (In Persian)
2. 2. Okati, N., Eynollahi, F. and Ghafari, M., 2019. Study of Seasonal Changes in Chlorophyll a Concentration in the Water of Chahnimeh Reservoirs in Sistan. Journal of Environmental Science and Technology. 2(1): 45-55. (In Persian)
3. 3. Ward, T.J., Butler, E.C. and Hill, B.J., 1998. Environmental indicators for national State of the Environment reporting: estuaries and the sea. Canberra, ACT, Environment Australia, Dept. of the Environment.
4. 4. Nouri, P., Gholamalifard, M. and Saravi, H.N.Z., 2020. Satellite Monitoring and Spatio -Temporal Variability of Net Primary Productions in the Southern Caspian Sea. Trabiat Modares University. 125 p. (In Persian)
5. 5. Gholamalifad, M., Ahmadi, B. and Nouri, P., 2020. Remote Sensing Monitoring of Sea Surface Temperature and Chlorophyll-a Variability in the Persian Gulf and Oman Sea: Influential Factors on Net Primary Production. Fisheries Science and Technology. 9(4): 305-333. (In Persian)
6. 6. Vinh, P.Q., Ha, N.T., Binh, N.T., Thang, N.N., Oanh, L.T. and Thao, N.T., 2019. Developing algorithm for estimating chlorophyll-a concentration in the Thac Ba Reservoir surface water using Landsat 8 Imagery. Earth Sci. 41: 10-20. doi: 10.15625/0866-7187/41/1/13542
7. 7. Kostianoy, A.G. and Kosarev, A.N., 2020. The Caspian Sea environment. Computing in Science & Engineering. Springer Science & Business Media.
8. 8. Kravitz, J., Matthews, M., Bernard, S. and Griffith, D., Application of Sentinel 3 OLCI for chl-a retrieval over small inland water targets: Successes and challenges. Remote Sensing of Environment. 237(2): 111562. doi: 10.1016/j.rse.2019.111562
9. 9. Regional Organization for the Protection of the Marine Environment. 1999. Manual of Oceanographic Observations and Pollutant Analyses Methods (MOOPAM). Regional Organization for the Protection of the Marine Environment.
10. 10. Zuhlke, M., Fomferra, N., Brockmann, C., Peters, M., Veci. L,, Malik, J. and Regner, P., 2015. SNAP (Sentinel Application Platform) and the ESA sentinel 3 toolbox. InSentinel-3 for Science Workshop. 734: 21 p. Corpus ID: 218062878
11. 11. Ebrahimi, M., Zarshenas, G.A., Eslami, F., Akbarzadeh, G., Khodadadi Jokar, K., Ayag, R. and Mokhaier, Z., 2013. Monitoring of algal bloom in Coastal water of the Persian Gulf and Omansea (Hormuzgan provience).58 p. (In Persian)
12. 12. Omidi, S., Noorinezhad, M., Marzbani, A., Esmaeili, A. and Kaviani, A., 2020. Investigation on the Fluctuations of Nutrients and Chlorophyll a in Coastal Waters of Bushehr to Delvar. Journal of Animal Environment. 12(2): 419-426. (In Persian)
13. 13. Shahri, E., Sayadi, M.H. and Yousefi, E., 2021. Monitoring of chlorophyll-A, organic carbon, salinity and water surface temperature off the coast of Sistan and Baluchestan using remote sensing data. Journal of RS and GIS for Natural Resources. 12(4): 119-134. doi: 10. 30495/girs.2021.684236 (In Persian)
14. 14. Rabbaniha, R., Aeinjamshid, Kh., Khalfeh nilsaz, M., Kamali, I., Mohsenizadeh, F., Fallahi, R., Riazi Otoofat shamsi, Sh.M., Ardestani, R. and Pourabbas, N., 2018. Study on fluctuations and correlation of chlorophyll-a as primary production indicator with commercial demersal fishes of the Persian Gulf and Oman Sea. 38 p. (In Persian)
15. 15. Kenarkoohi, M., Ahmadi Nadoushan, M. and Abolhasani, M.H., 2020. Estimation of Chlorophyll-A Concentration in Choghakhor wetland using remote sensing and in-situ measurements. Journal of Animal Environment. 12(3): 475-486. (In Persian)
16. 16. Navarro, G. and Ruiz, J., 2006. Spatial and temporal variability of phytoplankton in the Gulf of Cádiz through remote sensing images. Deep Sea Research Part II: topical studies in oceanography. 53(11-13): 1241-1260. doi: 10.1016/j.dsr2.2006.04.014
17. 17. Hendiarti, N., Suwarso, A.E., Amri, K., Andiastuti, R., Sachoemar, S.E. and Wahyono, I.B., 2005. Pelagic fish catch around Java. Oceanography. 18(4): 112-123. doi: 10.5670/oceanog.2005.12
18. 18. Mahdavifard, M., Valizadeh Kamran, K. and Atazadeh, E., 2020. Estimation of chlorophyll-a concentration using ground data and Sentinel-2 and Landsat-8 Satellite images processing (Case study: Tiab Estuary). Journal of RS and GIS for Natural Resources. 11(1): 72-83. doi: 10.30495/girs.2020.672377 (In Persian)
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Saraji F, Mansoori Z, Mousivand Y, Salarpouri A, Akbarzadeh G, Kookan H. A suitable algorithm for estimating chlorophyll- a using field data and satellite images in the waters of the Persian Gulf (Hormozgan Province). , Journalaer. 2025; 1 (4) :151-156
URL: http://journalaer.com/article-1-66-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 1, Issue 4 (12-2025) Back to browse issues page
پژوهش های محیط زیست جانوری Journal of Animal Environmental Research
Persian site map - English site map - Created in 0.21 seconds with 39 queries by YEKTAWEB 4780