Research Article
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Year 2022, Volume: 9 Issue: 4, 68 - 77, 25.12.2022
https://doi.org/10.30897/ijegeo.1066168

Abstract

References

  • Acar, U., Yılmaz, O. S., Çelen, M., Ateş, A. M., Gülgen, F. & Balık Şanlı, F. (2021). Determination of Mucilage in The Sea of Marmara Using Remote Sensing Techniques with Google Earth Engine. International Journal of Environment and Geoinformatics, 8 (4), 423-434. DOI: 10.30897/ijegeo.957284
  • Amani, Meisam, Arsalan Ghorbanian, Seyed Ali Ahmadi, Mohammad Kakooei, Armin Moghimi, S. Mohammad Mirmazloumi, Sayyed Hamed Alizadeh Moghaddam, Sahel Mahdavi, Masoud Ghahremanloo, and Saeid Parsian. 2020. “Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13:5326–50.
  • Barnes, William L., Thomas S. Pagano, and Vincent V. Salomonson. 1998. “Prelaunch Characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1.” IEEE Transactions on Geoscience and Remote Sensing 36(4):1088–1100.
  • Dierssen, Heidi M., and Kaylan Randolph. 2013. “Remote Sensing of Ocean Color.” Pp. 439–72 in Earth system monitoring. Springer.
  • Dierssen, Heidi M., Richard C. Zimmerman, Robert A. Leathers, T. Valerie Downes, and Curtiss O. Davis. 2003. “Ocean Color Remote Sensing of Seagrass and Bathymetry in the Bahamas Banks by High-Resolution Airborne Imagery.” Limnology and Oceanography 48(1part2):444–55.
  • Gazioğlu, C., Çelik, Oİ., Çelik, S., 2022. “Marmara Denizi için 2002-2021 Yılları Arasında Klorofil-A Değerlerinin Google Earth Engine Yardımı ile İzlenmesi” Proceedings of the Symposium "The Marmara Sea 2022", 25-35
  • Gorelick, Noel. 2013. “Google Earth Engine.” P. 11997 in EGU General Assembly Conference Abstracts. Vol. 15. American Geophysical Union Vienna, Austria.
  • Kavzoğlu, T., Tonbul, H., Çölkesen, İ. & Sefercik, U. G. (2021). The Use of Object-Based Image Analysis for Monitoring 2021 Marine Mucilage Bloom in the Sea of Marmara. International Journal of Environment and Geoinformatics, 8 (4), 529-536. DOI: 10.30897/ijegeo.990875
  • Mutanga, Onisimo, and Lalit Kumar. 2019. “Google Earth Engine Applications.” Remote Sensing 11(5):591.
  • O’Reilly, John E., Stephane Maritorena, B. Greg Mitchell, David A. Siegel, Kendall L. Carder, Sara A. Garver, Mati Kahru, and Charles McClain. 1998. “Ocean Color Chlorophyll Algorithms for SeaWiFS.” Journal of Geophysical Research: Oceans 103(C11):24937–53.
  • Rigaux, Ph, Michel Scholl, and Agnes Voisard. 2002. Spatial Databases: With Application to GIS. Morgan Kaufmann.
  • Wang, Wenhui, and Shunlin Liang. 2009. “Estimation of High-Spatial Resolution Clear-Sky Longwave Downward and Net Radiation over Land Surfaces from MODIS Data.” Remote Sensing of Environment 113(4):745–54.
  • Werdell, P. Jeremy, Sean W. Bailey, Bryan A. Franz, Lawrence W. Harding Jr, Gene C. Feldman, and Charles R. McClain. 2009. “Regional and Seasonal Variability of Chlorophyll-a in Chesapeake Bay as Observed by SeaWiFS and MODIS-Aqua.” Remote Sensing of Environment 113(6):1319–30.
  • Yilmaz, İzzet Noyan. 2008. “Marmara Denizi Zooplankton Dinamiği.”

Evaluation on 2002-2021 CHL-A Concentrations in the Sea of Marmara with GEE Enhancement of Satellite Data

Year 2022, Volume: 9 Issue: 4, 68 - 77, 25.12.2022
https://doi.org/10.30897/ijegeo.1066168

Abstract

Remote sensing data, especially satellite observations make available large databases related to marine biosphere. This tremendous amount of the data causes a difficulty to acquisition, processing and evaluation processes. Google Earth Engine (GEE) platform make possible to overcome this difficulty by its state of art structure. Thus, GEE platform was included to study to process and evaluate the chlorophyll-a data for the sea of Marmara. The Sea of Marmara was considered in 2 main parts as North and South Marmara. These parts also divided into 6 sub-regions and analyzed as 12 different regions in total. MODIS (Moderate Resolution Imaging Spectroradiometer)-Aqua data were acquired between the years 2003-2021 with the GEE platform for all examined sub-regions and make them available for analysis. Approximately 19 years of arranged chl-a concentration data were visualized and evaluated by grouping them according to sub-regions, months and years. As expected, the highest concentration of chl-a was observed in the Sea of Marmara in square KM6, which includes the Gulf of Izmit and has limited regeneration The lowest concentration values throughout the years were found in the areal average values of the KM4 square under the influence of the jet stream formed by the upper water from the Black Sea. When the monthly data are examined, it can be said that the primary production in general takes place intensively in the whole of the Marmara Sea in the spring season. In the context of this study, the accuracy of the division of the Sea of Marmara in two main axes as North and South is clearly seen in the analyzes within the time series. We evaluate that the similarity of chl-a concentrations in the Marmara Sea to the period before 2007 and 2020 requires a special attention as evidence of a repetitive process rather than an ecological coincidence.

References

  • Acar, U., Yılmaz, O. S., Çelen, M., Ateş, A. M., Gülgen, F. & Balık Şanlı, F. (2021). Determination of Mucilage in The Sea of Marmara Using Remote Sensing Techniques with Google Earth Engine. International Journal of Environment and Geoinformatics, 8 (4), 423-434. DOI: 10.30897/ijegeo.957284
  • Amani, Meisam, Arsalan Ghorbanian, Seyed Ali Ahmadi, Mohammad Kakooei, Armin Moghimi, S. Mohammad Mirmazloumi, Sayyed Hamed Alizadeh Moghaddam, Sahel Mahdavi, Masoud Ghahremanloo, and Saeid Parsian. 2020. “Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13:5326–50.
  • Barnes, William L., Thomas S. Pagano, and Vincent V. Salomonson. 1998. “Prelaunch Characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1.” IEEE Transactions on Geoscience and Remote Sensing 36(4):1088–1100.
  • Dierssen, Heidi M., and Kaylan Randolph. 2013. “Remote Sensing of Ocean Color.” Pp. 439–72 in Earth system monitoring. Springer.
  • Dierssen, Heidi M., Richard C. Zimmerman, Robert A. Leathers, T. Valerie Downes, and Curtiss O. Davis. 2003. “Ocean Color Remote Sensing of Seagrass and Bathymetry in the Bahamas Banks by High-Resolution Airborne Imagery.” Limnology and Oceanography 48(1part2):444–55.
  • Gazioğlu, C., Çelik, Oİ., Çelik, S., 2022. “Marmara Denizi için 2002-2021 Yılları Arasında Klorofil-A Değerlerinin Google Earth Engine Yardımı ile İzlenmesi” Proceedings of the Symposium "The Marmara Sea 2022", 25-35
  • Gorelick, Noel. 2013. “Google Earth Engine.” P. 11997 in EGU General Assembly Conference Abstracts. Vol. 15. American Geophysical Union Vienna, Austria.
  • Kavzoğlu, T., Tonbul, H., Çölkesen, İ. & Sefercik, U. G. (2021). The Use of Object-Based Image Analysis for Monitoring 2021 Marine Mucilage Bloom in the Sea of Marmara. International Journal of Environment and Geoinformatics, 8 (4), 529-536. DOI: 10.30897/ijegeo.990875
  • Mutanga, Onisimo, and Lalit Kumar. 2019. “Google Earth Engine Applications.” Remote Sensing 11(5):591.
  • O’Reilly, John E., Stephane Maritorena, B. Greg Mitchell, David A. Siegel, Kendall L. Carder, Sara A. Garver, Mati Kahru, and Charles McClain. 1998. “Ocean Color Chlorophyll Algorithms for SeaWiFS.” Journal of Geophysical Research: Oceans 103(C11):24937–53.
  • Rigaux, Ph, Michel Scholl, and Agnes Voisard. 2002. Spatial Databases: With Application to GIS. Morgan Kaufmann.
  • Wang, Wenhui, and Shunlin Liang. 2009. “Estimation of High-Spatial Resolution Clear-Sky Longwave Downward and Net Radiation over Land Surfaces from MODIS Data.” Remote Sensing of Environment 113(4):745–54.
  • Werdell, P. Jeremy, Sean W. Bailey, Bryan A. Franz, Lawrence W. Harding Jr, Gene C. Feldman, and Charles R. McClain. 2009. “Regional and Seasonal Variability of Chlorophyll-a in Chesapeake Bay as Observed by SeaWiFS and MODIS-Aqua.” Remote Sensing of Environment 113(6):1319–30.
  • Yilmaz, İzzet Noyan. 2008. “Marmara Denizi Zooplankton Dinamiği.”
There are 14 citations in total.

Details

Primary Language English
Subjects Environmental Sciences, Photogrammetry and Remote Sensing, Oceanography
Journal Section Research Articles
Authors

Osman İsa Çelik 0000-0002-3788-9988

Selin Çelik 0000-0003-2003-688X

Cem Gazioğlu 0000-0002-2083-4008

Publication Date December 25, 2022
Published in Issue Year 2022 Volume: 9 Issue: 4

Cite

APA Çelik, O. İ., Çelik, S., & Gazioğlu, C. (2022). Evaluation on 2002-2021 CHL-A Concentrations in the Sea of Marmara with GEE Enhancement of Satellite Data. International Journal of Environment and Geoinformatics, 9(4), 68-77. https://doi.org/10.30897/ijegeo.1066168