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A Study on Monitoring of Chlorophyll-a Level by Remote Sensing

Year 2023, , 41 - 47, 30.06.2023
https://doi.org/10.5281/zenodo.8074879

Abstract

In this study, the chlorophyll-a level of the part of the Kura river within the borders of Ardahan city center was determined and a chlorophyll-a map was made with the support of Göktürk-2 satellite imagery. Detection and monitoring of chlorophyll-a, which is an important parameter among water quality criteria, plays a very decisive role in the protection and management of water resources. Conventional determination of chlorophyll-a levels in lakes and streams is a time-consuming and laborious method that requires on-site sampling. For this purpose, on 30 August 2016, samples were taken from 5 suitable points for the study and the chlorophyll-a levels of these samples were determined. In addition, NDVI analysis was carried out using the infrared and red bands of the image taken from the Göktürk-2 satellite on the same date. Thus, the chlorophyll-a map of the Kura river was created. In addition, regression analysis was performed between the pixel values of the chlorophyll-a map and the results of the chlorophyll-a value obtained from the field studies and gave acceptable results. The predictive coefficient (R2) of the regression analysis was found to be 0.95, which is a high value.

References

  • K. Toming, T. Kutser, A. Laas, M. Sepp, B. Paavel, and T. Nõges, “First experiences in mapping lakewater quality parameters with sentinel-2 MSI imagery,” Remote Sens., vol. 8, no. 8, pp. 1–14, 2016, doi: 10.3390/rs8080640.
  • C. Zuccari Fernandes Braga, A. W. Setzer, and L. Drude de Lacerda, “Water quality assessment with simultaneous Landsat-5 TM data at Guanabara Bay, Rio de Janeiro, Brazil,” Remote Sens. Environ., vol. 45, no. 1, pp. 95–106, Jul. 1993, doi: 10.1016/0034-4257(93)90085-C.
  • S. Dlamini, I. Nhapi, W. Gumindoga, T. Nhiwatiwa, and T. Dube, “Assessing the feasibility of integrating remote sensing and in-situ measurements in monitoring water quality status of Lake Chivero, Zimbabwe,” Phys. Chem. Earth, vol. 93, pp. 2–11, 2016, doi: 10.1016/j.pce.2016.04.004.
  • F. S. Y. Watanabe, E. Alcântara, T. W. P. Rodrigues, N. N. Imai, C. C. F. Barbosa, and L. H. da S. Rotta, “Estimation of chlorophyll-a concentration and the trophic state of the barra bonita hydroelectric reservoir using OLI/landsat-8 images,” Int. J. Environ. Res. Public Health, vol. 12, no. 9, pp. 10391–10417, 2015, doi: 10.3390/ijerph120910391.
  • J. Zhang, T. Zou, and Y. Lai, “Novel method for industrial sewage outfall detection: Water pollution monitoring based on web crawler and remote sensing interpretation techniques,” J. Clean. Prod., vol. 312, no. June 2020, p. 127640, 2021, doi: 10.1016/j.jclepro.2021.127640.
  • Y. Guo et al., “Development and application of a new sensitivity analysis model for the remote sensing retrieval of heavy metals in water,” Heliyon, vol. 8, no. 12, p. e12033, 2022, doi: 10.1016/j.heliyon.2022.e12033.
  • P. L. Brezonik, L. G. Olmanson, J. C. Finlay, and M. E. Bauer, “Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters,” Remote Sens. Environ., vol. 157, pp. 199–215, 2015, doi: 10.1016/j.rse.2014.04.033.
  • A. I. Dogliotti, K. G. Ruddick, B. Nechad, D. Doxaran, and E. Knaeps, “A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters,” Remote Sens. Environ., vol. 156, pp. 157–168, 2015, doi: 10.1016/j.rse.2014.09.020.
  • J. L. Wu, C. R. Ho, C. C. Huang, A. L. Srivastav, J. H. Tzeng, and Y. T. Lin, “Hyperspectral sensing for turbid water quality monitoring in freshwater rivers: Empirical relationship between reflectance and turbidity and total solids,” Sensors (Switzerland), vol. 14, no. 12, pp. 22670–22688, 2014, doi: 10.3390/s141222670.
  • I. M. Hasmadi and U. Norsaliza, “Analysis of SPOT- 5 Data for Mapping Turbidity Level of River Klang,” Water, vol. 1, no. 2, pp. 14–18, 2010.
  • F. L. Hellweger, W. Miller, and K. S. Oshodi, “Mapping turbidity in the Charles River, Boston using a high-resolution satellite,” Environ. Monit. Assess., vol. 132, no. 1–3, pp. 311–320, 2007, doi: 10.1007/s10661-006-9535-8.
  • T. Kutser, D. C. Pierson, K. Y. Kallio, A. Reinart, and S. Sobek, “Mapping lake CDOM by satellite remote sensing,” Remote Sens. Environ., vol. 94, no. 4, pp. 535–540, 2005, doi: 10.1016/j.rse.2004.11.009.
  • K. W. Abdelmalik, “Role of statistical remote sensing for Inland water quality parameters prediction,” Egypt. J. Remote Sens. Sp. Sci., 2016, doi: 10.1016/j.ejrs.2016.12.002.
  • M. Hartnett and S. Nash, “An integrated measurement and modeling methodology for estuarine water quality management,” Water Sci. Eng., vol. 8, no. 1, pp. 9–19, Jan. 2015, doi: 10.1016/j.wse.2014.10.001.
  • N. Strömbeck and D. C. Pierson, “The effects of variability in the inherent optical properties on estimations of chlorophyll a by remote sensing in Swedish freshwaters,” Sci. Total Environ., vol. 268, no. 1–3, pp. 123–137, 2001, doi: 10.1016/S0048-9697(00)00681-1.
  • N. K. Sönmez and M. Sarı, “Uzaktan algılama temel prensipleri ve uygulama alanları,” Derim, vol. 19, no. 2, pp. 16–30, 2002.
  • M. Gholizadeh, A. Melesse, and L. Reddi, “A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques,” Sensors, vol. 16, no. 8, p. 1298, 2016, doi: 10.3390/s16081298.
  • R. G. Lathrop and T. M. Lillesand, “Use of thematic mapper data to assess water quality in Green Bay and Central Lake Michigan,” Photogramm. Eng. Remote Sensing, vol. 52, no. 5, pp. 671–680, 1986.
  • T. M. Lillesand, W. L. Johnson, and R. L. Deuell, “Use of landsat data to predict the trophic state of Minnesota lakes,” Photogramm. Eng. Remote Sensing, vol. 49, no. 2, pp. 219–229, 1983, [Online]. Available: http://eserv.asprs.org/PERS/1983journal/feb/1983_feb_219-229.pdf
  • Somvanshi.S, Kunwar.P, Singh.N.B, Shukla.S.P, and Pathak.V, “Integrated remote sensing and GIS approach for water quality analysis of Gomti river , Uttar Pradesh,” Int. J. Environ. Sci., vol. 3, no. 1, pp. 62–75, 2012, doi: 10.6088/ijes.2012030131008.
  • I. Barut, H. Keskin-Citiroglu, M. Oruc, and A. M. Marangoz, “Determination by Landsat Satellite Imagery to Local Scales in Land and Pollution Monitoring: a Case of Buyuk Melen Watershed (Turkey),” J. Sustain. Dev. Energy, Water Environ. Syst., vol. 3, no. 4, pp. 389–404, 2015, doi: 10.13044/j.sdewes.2015.03.0029.
  • C. B. Mouw et al., “Aquatic color radiometry remote sensing of coastal and inland waters: Challenges and recommendations for future satellite missions,” Remote Sens. Environ., vol. 160, pp. 15–30, 2015, doi: 10.1016/j.rse.2015.02.001.
  • S. C. J. Palmer, T. Kutser, and P. D. Hunter, “Remote sensing of inland waters: Challenges, progress and future directions,” Remote Sens. Environ., vol. 157, pp. 1–8, 2015, doi: 10.1016/j.rse.2014.09.021.
  • K. Shi et al., “Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250 m MODIS-Aqua data,” Remote Sens. Environ., vol. 164, pp. 43–56, Jul. 2015, doi: 10.1016/J.RSE.2015.02.029.
  • Z. Zhou and Y. Zhao, “Research on the water quality monitoring system for inland lakes based on remote sensing,” Procedia Environ. Sci., vol. 10, no. PART B, pp. 1707–1711, 2011, doi: 10.1016/j.proenv.2011.09.268.
  • “Wikipedi,” 2023. https://tr.wikipedia.org/wiki/Ardahan
  • V. O. Atak, M. Erdoğan, and A. Yılmaz, “Göktürk-2 Uydu Görüntü Testleri,” Harit. Derg., pp. 18–33, 2015.
  • Su kirliliği kontrolü yönetmeliği numune alma ve analiz metodlar tebliği. Türkiye, 2009.

Uzaktan Algılama İle Klorofil-a İzlenmesi Üzerine Bir Çalışma

Year 2023, , 41 - 47, 30.06.2023
https://doi.org/10.5281/zenodo.8074879

Abstract

Bu çalışmada, Kura nehrinin Ardahan il merkezi sınırları içerisinde bulunan kısmının klorofil-a düzeyinin belirlenip Göktürk-2 uydu görüntüsü desteği ile klorofil-a haritası yapılmıştır. Su kalitesi kriterlerinden önemli bir parametre olan klorofil-a’nın tespiti ve izlenmesi su kaynaklarının korunması ve yönetilmesi konusunda oldukça belirleyici rol oynamaktadır. Göllerin ve akarsuların klorofil-a seviyelerinin geleneksel tespiti, yerinde örneklemeyi gerektiren, zaman alıcı ve zahmetli bir yöntemdir. Bu amaçla 30 Ağustos 2016 tarihinde olmak üzere çalışma için uygun 5 noktadan numune alınmış ve alınan bu numunelerin klorofil-a düzeyleri belirlenmiştir. Ayrıca Göktürk-2 uydusundan aynı tarihte alınan görüntünün kızılötesi ve kırmızı bantları kullanılarak NDVI analizi yapılmıştır. Böylece Kura nehrinin klorofil-a haritası oluşturulmuştur. Ayrıca oluşturulan klorofil-a haritasının piksel değerleri ile saha çalışmalarından elde edilen klorofil-a değeri sonuçları arasında regresyon analizi yapılmış ve kabul edilebilir sonuçlar vermiştir. Yapılan regresyon analizinin belirleyicilik katsayısı (R2) yüksek bir değer olan 0.95 olarak bulunmuştur.

References

  • K. Toming, T. Kutser, A. Laas, M. Sepp, B. Paavel, and T. Nõges, “First experiences in mapping lakewater quality parameters with sentinel-2 MSI imagery,” Remote Sens., vol. 8, no. 8, pp. 1–14, 2016, doi: 10.3390/rs8080640.
  • C. Zuccari Fernandes Braga, A. W. Setzer, and L. Drude de Lacerda, “Water quality assessment with simultaneous Landsat-5 TM data at Guanabara Bay, Rio de Janeiro, Brazil,” Remote Sens. Environ., vol. 45, no. 1, pp. 95–106, Jul. 1993, doi: 10.1016/0034-4257(93)90085-C.
  • S. Dlamini, I. Nhapi, W. Gumindoga, T. Nhiwatiwa, and T. Dube, “Assessing the feasibility of integrating remote sensing and in-situ measurements in monitoring water quality status of Lake Chivero, Zimbabwe,” Phys. Chem. Earth, vol. 93, pp. 2–11, 2016, doi: 10.1016/j.pce.2016.04.004.
  • F. S. Y. Watanabe, E. Alcântara, T. W. P. Rodrigues, N. N. Imai, C. C. F. Barbosa, and L. H. da S. Rotta, “Estimation of chlorophyll-a concentration and the trophic state of the barra bonita hydroelectric reservoir using OLI/landsat-8 images,” Int. J. Environ. Res. Public Health, vol. 12, no. 9, pp. 10391–10417, 2015, doi: 10.3390/ijerph120910391.
  • J. Zhang, T. Zou, and Y. Lai, “Novel method for industrial sewage outfall detection: Water pollution monitoring based on web crawler and remote sensing interpretation techniques,” J. Clean. Prod., vol. 312, no. June 2020, p. 127640, 2021, doi: 10.1016/j.jclepro.2021.127640.
  • Y. Guo et al., “Development and application of a new sensitivity analysis model for the remote sensing retrieval of heavy metals in water,” Heliyon, vol. 8, no. 12, p. e12033, 2022, doi: 10.1016/j.heliyon.2022.e12033.
  • P. L. Brezonik, L. G. Olmanson, J. C. Finlay, and M. E. Bauer, “Factors affecting the measurement of CDOM by remote sensing of optically complex inland waters,” Remote Sens. Environ., vol. 157, pp. 199–215, 2015, doi: 10.1016/j.rse.2014.04.033.
  • A. I. Dogliotti, K. G. Ruddick, B. Nechad, D. Doxaran, and E. Knaeps, “A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters,” Remote Sens. Environ., vol. 156, pp. 157–168, 2015, doi: 10.1016/j.rse.2014.09.020.
  • J. L. Wu, C. R. Ho, C. C. Huang, A. L. Srivastav, J. H. Tzeng, and Y. T. Lin, “Hyperspectral sensing for turbid water quality monitoring in freshwater rivers: Empirical relationship between reflectance and turbidity and total solids,” Sensors (Switzerland), vol. 14, no. 12, pp. 22670–22688, 2014, doi: 10.3390/s141222670.
  • I. M. Hasmadi and U. Norsaliza, “Analysis of SPOT- 5 Data for Mapping Turbidity Level of River Klang,” Water, vol. 1, no. 2, pp. 14–18, 2010.
  • F. L. Hellweger, W. Miller, and K. S. Oshodi, “Mapping turbidity in the Charles River, Boston using a high-resolution satellite,” Environ. Monit. Assess., vol. 132, no. 1–3, pp. 311–320, 2007, doi: 10.1007/s10661-006-9535-8.
  • T. Kutser, D. C. Pierson, K. Y. Kallio, A. Reinart, and S. Sobek, “Mapping lake CDOM by satellite remote sensing,” Remote Sens. Environ., vol. 94, no. 4, pp. 535–540, 2005, doi: 10.1016/j.rse.2004.11.009.
  • K. W. Abdelmalik, “Role of statistical remote sensing for Inland water quality parameters prediction,” Egypt. J. Remote Sens. Sp. Sci., 2016, doi: 10.1016/j.ejrs.2016.12.002.
  • M. Hartnett and S. Nash, “An integrated measurement and modeling methodology for estuarine water quality management,” Water Sci. Eng., vol. 8, no. 1, pp. 9–19, Jan. 2015, doi: 10.1016/j.wse.2014.10.001.
  • N. Strömbeck and D. C. Pierson, “The effects of variability in the inherent optical properties on estimations of chlorophyll a by remote sensing in Swedish freshwaters,” Sci. Total Environ., vol. 268, no. 1–3, pp. 123–137, 2001, doi: 10.1016/S0048-9697(00)00681-1.
  • N. K. Sönmez and M. Sarı, “Uzaktan algılama temel prensipleri ve uygulama alanları,” Derim, vol. 19, no. 2, pp. 16–30, 2002.
  • M. Gholizadeh, A. Melesse, and L. Reddi, “A Comprehensive Review on Water Quality Parameters Estimation Using Remote Sensing Techniques,” Sensors, vol. 16, no. 8, p. 1298, 2016, doi: 10.3390/s16081298.
  • R. G. Lathrop and T. M. Lillesand, “Use of thematic mapper data to assess water quality in Green Bay and Central Lake Michigan,” Photogramm. Eng. Remote Sensing, vol. 52, no. 5, pp. 671–680, 1986.
  • T. M. Lillesand, W. L. Johnson, and R. L. Deuell, “Use of landsat data to predict the trophic state of Minnesota lakes,” Photogramm. Eng. Remote Sensing, vol. 49, no. 2, pp. 219–229, 1983, [Online]. Available: http://eserv.asprs.org/PERS/1983journal/feb/1983_feb_219-229.pdf
  • Somvanshi.S, Kunwar.P, Singh.N.B, Shukla.S.P, and Pathak.V, “Integrated remote sensing and GIS approach for water quality analysis of Gomti river , Uttar Pradesh,” Int. J. Environ. Sci., vol. 3, no. 1, pp. 62–75, 2012, doi: 10.6088/ijes.2012030131008.
  • I. Barut, H. Keskin-Citiroglu, M. Oruc, and A. M. Marangoz, “Determination by Landsat Satellite Imagery to Local Scales in Land and Pollution Monitoring: a Case of Buyuk Melen Watershed (Turkey),” J. Sustain. Dev. Energy, Water Environ. Syst., vol. 3, no. 4, pp. 389–404, 2015, doi: 10.13044/j.sdewes.2015.03.0029.
  • C. B. Mouw et al., “Aquatic color radiometry remote sensing of coastal and inland waters: Challenges and recommendations for future satellite missions,” Remote Sens. Environ., vol. 160, pp. 15–30, 2015, doi: 10.1016/j.rse.2015.02.001.
  • S. C. J. Palmer, T. Kutser, and P. D. Hunter, “Remote sensing of inland waters: Challenges, progress and future directions,” Remote Sens. Environ., vol. 157, pp. 1–8, 2015, doi: 10.1016/j.rse.2014.09.021.
  • K. Shi et al., “Long-term remote monitoring of total suspended matter concentration in Lake Taihu using 250 m MODIS-Aqua data,” Remote Sens. Environ., vol. 164, pp. 43–56, Jul. 2015, doi: 10.1016/J.RSE.2015.02.029.
  • Z. Zhou and Y. Zhao, “Research on the water quality monitoring system for inland lakes based on remote sensing,” Procedia Environ. Sci., vol. 10, no. PART B, pp. 1707–1711, 2011, doi: 10.1016/j.proenv.2011.09.268.
  • “Wikipedi,” 2023. https://tr.wikipedia.org/wiki/Ardahan
  • V. O. Atak, M. Erdoğan, and A. Yılmaz, “Göktürk-2 Uydu Görüntü Testleri,” Harit. Derg., pp. 18–33, 2015.
  • Su kirliliği kontrolü yönetmeliği numune alma ve analiz metodlar tebliği. Türkiye, 2009.
There are 28 citations in total.

Details

Primary Language Turkish
Subjects Engineering, Environmental Engineering (Other), Remote Sensing
Journal Section Research Articles
Authors

Mustafa Akgün 0000-0002-7172-1855

Early Pub Date June 23, 2023
Publication Date June 30, 2023
Submission Date April 19, 2023
Published in Issue Year 2023

Cite

IEEE M. Akgün, “Uzaktan Algılama İle Klorofil-a İzlenmesi Üzerine Bir Çalışma”, JSAT, vol. 1, no. 1, pp. 41–47, 2023, doi: 10.5281/zenodo.8074879.