Research Article

SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province

Volume: 9 Number: 4 December 25, 2022
EN

SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province

Abstract

Temporal Sea Surface Temperature (SST) analyses by satellite images are quite vital in terms of understanding the sea water quality. Specific water quality criteria include dissolved oxygen, chlorophyll, temperature, depth, pH, salinity, and turbidity, and these criteria are used to determine water quality in seas. In the current study, three criteria which are chlorophyll, temperature (SST) and turbidity were examined through their correlation with SST derived from Landsat sensors. This let to know about the examined criteria at minimum and maximum temperature dates, the relation with respect to temperature change rates, and to understand the events that occur in certain dates. The regular or irregular increases of the detected SST are evidence of sea water quality or pollution resulted from the criteria in the study area. Therefore, first turbid water which contains a high amount of suspended sediment was studied. After the turbidity index was completed, the Chlorophyll study was carried out to detect the algae like substances. The aims of the study are to evaluate the temporal change of water quality in coastal region of Izmir province, using spectral indices, and to contribute to the development of more sensitive qualitative index algorithms in the future. At the end of the study, high correlation coefficients revealed the relationship between SST and indexes.

Keywords

References

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Details

Primary Language

English

Subjects

Photogrammetry and Remote Sensing

Journal Section

Research Article

Publication Date

December 25, 2022

Submission Date

January 31, 2022

Acceptance Date

April 16, 2022

Published in Issue

Year 2022 Volume: 9 Number: 4

APA
Kayalık, M., & Çorumluoğlu, Ö. (2022). SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. International Journal of Environment and Geoinformatics, 9(4), 35-45. https://doi.org/10.30897/ijegeo.1065482
AMA
1.Kayalık M, Çorumluoğlu Ö. SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. IJEGEO. 2022;9(4):35-45. doi:10.30897/ijegeo.1065482
Chicago
Kayalık, Mert, and Özşen Çorumluoğlu. 2022. “SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province”. International Journal of Environment and Geoinformatics 9 (4): 35-45. https://doi.org/10.30897/ijegeo.1065482.
EndNote
Kayalık M, Çorumluoğlu Ö (December 1, 2022) SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. International Journal of Environment and Geoinformatics 9 4 35–45.
IEEE
[1]M. Kayalık and Ö. Çorumluoğlu, “SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province”, IJEGEO, vol. 9, no. 4, pp. 35–45, Dec. 2022, doi: 10.30897/ijegeo.1065482.
ISNAD
Kayalık, Mert - Çorumluoğlu, Özşen. “SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province”. International Journal of Environment and Geoinformatics 9/4 (December 1, 2022): 35-45. https://doi.org/10.30897/ijegeo.1065482.
JAMA
1.Kayalık M, Çorumluoğlu Ö. SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. IJEGEO. 2022;9:35–45.
MLA
Kayalık, Mert, and Özşen Çorumluoğlu. “SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province”. International Journal of Environment and Geoinformatics, vol. 9, no. 4, Dec. 2022, pp. 35-45, doi:10.30897/ijegeo.1065482.
Vancouver
1.Mert Kayalık, Özşen Çorumluoğlu. SST Correlation Between Chlorophyll and Turbidity by Landsat MS Image Analysis for the Coast of Izmir Province. IJEGEO. 2022 Dec. 1;9(4):35-4. doi:10.30897/ijegeo.1065482

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