Geomatics and Environmental Engineering, vol. 18, no. 5

Issue

Vol. 18 No. 5 (2024): Geomatics and Environmental Engineering

Date Log

Submitted
Mar 27, 2024
Accepted
Aug 21, 2024
Published
Sep 27, 2024
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Variability and Correlation among SST, Chlorophyll-a Levels, ENSO, and Pelagic Fishing in Southern Part of Madura Strait, Indonesia, Based on Landsat 9 OLI/TIRS Imagery

https://doi.org/10.7494/geom.2024.18.5.5
Taffy Elian
Universitas Pembangunan Nasional “Veteran,” Faculty of Mineral Technology, Geomatics Engineering, Yogyakarta, Indonesia
https://orcid.org/0009-0009-3311-7700
Naufal Setiawan
Universitas Pembangunan Nasional “Veteran,” Faculty of Mineral Technology, Geomatics Engineering, Yogyakarta, Indonesia
https://orcid.org/0000-0002-2350-4477

Corresponding Author(s) : Naufal Setiawan

naufal.setiawan@upnyk.ac.id

Geomatics and Environmental Engineering, Vol. 18 No. 5 (2024): Geomatics and Environmental Engineering

Abstract

Indonesia’s marine resources are abundant, with fishing being a primary focus. The effective management of these resources requires an understanding of the factors that influence them, such as sea surface temperature (SST), El Niño-Southern Oscillation (ENSO) as indicated by the Southern Oscillation Index (SOI), and chlorophyll-a levels as food sources. This research aimed to elucidate the relationships among those factors at Madura Strait by utilizing their characteristics in response to the electromagnetic wavelengths that can be found Landsat 9 OLI/TIRS satellite images.
This research utilized the satellite’s Thermal Infrared Sensor (or Band 10) (10.6–11.19 µm) to obtain the SST levels as well as the OceanColor 2 (OC2) algorithm to process Band 2 (0.45–0.51 µm) and Band 3 (0.53–0.59 µm) in order to obtain the chlorophyll-a levels. The results were the mean values of the SST (21.42 and 20.60°C) and the chlorophyll-a levels (0.77 and 0.87 mg/m3) from the periods of June through August 2022 and December 2022 through February 2023, respectively. Furthermore, a correlation test and t-test were conducted, which indicated that the chlorophyll-a levels were contradictory with the SST, SOI, and total pelagic fish catches (which were in alignment). The t-test results only indicated significant correlations between the SST and chlorophyll-a levels (–0.806) and between the SST and SOI (0.732), while the other correlation was not significant.

Keywords

Landsat 9 sea surface temperature (SST) chlorophyll-a Southern Oscillation Index (SOI) small pelagic fish El Niño-Southern Oscillation (ENSO)
Elian, T., & Setiawan, N. (2024). Variability and Correlation among SST, Chlorophyll-a Levels, ENSO, and Pelagic Fishing in Southern Part of Madura Strait, Indonesia, Based on Landsat 9 OLI/TIRS Imagery. Geomatics and Environmental Engineering, 18(5), 5–26. https://doi.org/10.7494/geom.2024.18.5.5
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. Pratama O.: Konservasi Perairan Sebagai Upaya menjaga Potensi Kelautan dan Perikanan Indonesia. 2020. https://kkp.go.id/djprl/artikel/21045-konservasiperairan-sebagai-upaya-menjaga-potensi-kelautan-dan-perikanan-indonesia [access: 3.12.2023].
  2. Zhang C., Han M.I.N.: Mapping chlorophyll-a concentration in Laizhou Bay using Landsat 8 OLI data. [in:] Mynett A. (ed.), Proceedings of the 36th IAHR World Congress 2015: Deltas of the Future and What Happens Upstream: The Hague, The Netherlands, 28 June–3 July 2015, International Assn for Hydro-Environment Engineering and Research, 2015, pp. 12–17.
  3. Ma’mun A., Priatna A., Amri K., Nurdin E.: Hubungan Antara Kondisi Oseanografi dan Distribusi Spasial Ikan Pelagis di Wilayah Pengelolaan Perikanan Negara Republik Indonesia (WPP NRI) 712 Laut Jawa. Jurnal Penelitian Perikanan Indonesia, vol. 25(1), 2019, pp. 1–14.
  4. Atmadipoera A.S., Nugroho D., Jaya I., Akhir M.F.: Simulated seasonal oceanographic changes and their implication for the small pelagic fisheries in the Java Sea, Indonesia. Marine Environmental Research, vol. 188, 2023, 106012. https://doi.org/10.1016/j.marenvres.2023.106012.
  5. Chen H.H., Tang R., Zhang H.R., Yu Y., Wang Y.: Investigating the relationship between sea surface chlorophyll and major features of the South China Sea with satellite information. JoVE (Journal of Visualized Experiments), vol. 13(160), 2020, e61172. https://doi.org/10.3791/61172.
  6. Muskananfola M.R., Wirasatriya A.: Spatio-temporal distribution of chlorophyll-a concentration, sea surface temperature and wind speed using aqua-modis satellite imagery over the Savu Sea, Indonesia. Remote Sensing Applications: Society and Environment, vol. 22, 2021, 100483. https://doi.org/10.1016/j.rsase.2021.100483.
  7. Shen C., Yan Y., Zhao H., Pan J.T., Devlin A.: Influence of monsoonal winds on chlorophyll-α distribution in the Beibu Gulf. Plos One, vol. 13(1), 2018, e0191051. https://doi.org/10.1371/journal.pone.0191051.
  8. Syetiawan A.: Penentuan Zona Potensi Penangkapan Ikan Berdasarkan Sebaran Klorofil-a. Jurnal Ilmiah Geomatika, vol. 21(2), 2015, pp. 131–136.
  9. Sidik A., Agussalim A., Ridho M.R.: Akurasi nilai konsentrasi klorofil-a dan suhu permukaan laut menggunakan data penginderaan jauh di Perairan Pulau Alanggantang Taman Nasional Sembilang. Maspari Journal: Marine Science Research, vol. 7(2), 2015, pp. 25–32.
  10. Kurniawati F., Sanjoto T.B., Juhadi: Pendugaan Zona Potensi Penangkapan Ikan Pelagis Kecil di Perairan Laut Jawa pada Musim Barat dan Musim Timur dengan Menggunakan Citra Aqua-MODIS. Geo Image, vol. 4(2), 2015, pp. 9–19.
  11. Daming W.S., Amran M.A., Muhiddin A.H., Tambaru R.: Spatial-Temporal Distribution of Chlorophyll-a in Southern Part of the Makassar Strait. Jurnal Ilmu Kelautan SPERMONDE, vol. 4(1), 2018, pp. 42–46. https://doi.org/10.20956/jiks.v4i1.3804.
  12. Yuniarti A., Maslukah L., Helmi M.: Studi variabilitas suhu permukaan laut berdasarkan citra satelit aqua MODIS tahun 2007–2011 di Perairan Selat Bali. Journal of Oceanography, vol. 2(4), 2013, pp. 416–421. https://ejournal3.undip.ac.id/index.php/joce/article/view/4588.
  13. Brosset P., Fromentin J.M., Van Beveren E., Lloret J., Marques V., Basilone G., Bonanno A., Carpi P., Donato F., Čikeš Keč V., De Felice A., Ferreri R., Gašparević D., Giráldez A., Gücü A., Iglesias M., Leonori I., Palomera I., Somarakis S., Tičina V., Torres P., Ventero A., Zorica B., Ménard F., Saraux C.: Spatio-temporal patterns and environmental controls of small pelagic fish body condition from contrasted Mediterranean areas. Progress in Oceanography, vol. 151, 2017, pp. 149–162. https://doi.org/10.1016/j.pocean.2016.12.002.
  14. Rahadian L.D., Khan A.M., Dewanti L.P., Apriliani I.M.: Analisis Sebaran Suhu Permukaan Laut pada Musim Barat dan Musim Timur Terhadap Produksi Hasil Tangkapan Ikan Lemuru (Sardinella lemuru) Di Perairan Selat Bali. Jurnal Perikanan Kelautan, vol. 10(2), 2019, pp. 28–34.
  15. Wirasatriya A., Prasetyawan I.B., Triyono C.D., Maslukah L.: Effect of ENSO on the variability of SST and Chlorophyll-a in Java Sea. IOP Conference Series: Earth and Environmental Science, vol. 116(1), 2018, 012063. https://doi.org/10.1088/1755-1315/116/1/012063.
  16. Wang M., Guo J.R., Song J., Fu Y.Z., Sui W.Y., Li Y.Q., Zhu Z.M., Li S., Li L.L., Guo X.F., Zuo W.T.: The correlation between ENSO events and sea surface temperature anomaly in the Bohai Sea and Yellow Sea. Regional Studies in Marine Science, vol. 35, 2020, 101228. https://doi.org/10.1016/j.rsma.2020.101228.
  17. Toding J.E., Widagdo S., Bintoro R.S.: Variabilitas Temperatur Permukaan Laut, Salinitas, dan, Curah Hujan Pada Periode El Niño-Southern Oscillation (Enso) di Perairan Selat Madura. Jurnal Riset Kelautan Tropis (Journal of Tropical Marine Research) (J-Tropimar ), vol. 4(1), 2022, pp. 52–66. https://doi.org/10.30649/jrkt.v4i1.60.
  18. Isa N.S., Akhir M.F., Kok P.H., Daud N.R., Khalil I., Roseli N.H.: Spatial and temporal variability of sea surface temperature during El-Niño Southern Oscillation and Indian Ocean Dipole in the Strait of Malacca and Andaman Sea. Regional Studies in Marine Science, vol. 39, 2020, 101402. https://doi.org/10.1016/j.rsma.2020.101402.
  19. Nababan B., Sihombing E.G.B., Panjaitan J.P.: Variabilitas suhu permukaan laut (SPL) dan konsentrasi klorofil-a di Samudera Hindia bagian Timur Laut sebelah barat Sumatera. Jurnal Teknologi Perikanan dan Kelautan, vol. 12(2), 2021, pp. 143–159. https://doi.org/10.24319/jtpk.12.143-159.
  20. Fery J., Haeruddin, Faizin N., Aminah S., Fanteri Aji D.S., Kristianta F.X.: The use of remote sensing in mining prospecting in Situbondo, East Java, Indonesia. AIP Conference Proceedings, vol. 2278(1), 2020, 020007. https://doi.org/10.1063/5.0014683.
  21. Lillesand T., Kiefer R.W., Chipman J.: Remote Sensing and Image Interpretation. 7th ed. John Wiley & Sons, 2015.
  22. Milne B.F., Toker Y., Rubio A., Nielsen S.B.: Unraveling the intrinsic color of chlorophyll. Angewandte Chemie International Edition, vol. 54(7), 2015, pp. 2170–2173. https://doi.org/10.1002/anie.201410899.
  23. Morel A., Prieur L.: Analysis of variations in ocean color 1. Limnology and Oceanography, vol. 22(4), 1977, pp. 709–722. https://doi.org/10.4319/lo.1977.22.4.0709.
  24. O’Reilly J.E., Maritorena S., O’Brien M.C., Siegel D.A., Toole D., Menzies D., Smith R.C., Mueller J.L., Mitchell B.G., Kahru M., Chavez R.P., Strutton P., Cota G.F., Hooker S.B., McClain C.R., Carder K.L., Mueller-Karger F., Harding L., Magnusion A., ..., Phinney D.: SeaWiFS Postlaunch Calibration and Validation Analyses, Part 3. SeaWiFS Postlaunch Technical Report Series, vol. 11, NASA Center for AeroSpace Information, Goddard Space Flight Center, Greenbelt, Maryland 2000.
  25. Poddar S., Chacko N., Swain D.: Estimation of chlorophyll-a in the northern coastal Bay of Bengal using Landsat-8 OLI and Sentinel-2 MSI sensors. Frontiers in Marine Science, vol. 6, 2019, 598. https://doi.org/10.3389/fmars.2019.00598.
  26. O’Reilly J.E., Maritorena S., Mitchell B.G., Siegel D.A., Carder K.L., Garver S.A., Kahru M., McClain C.: Ocean color chlorophyll algorithms for SeaWiFS. Journal of Geophysical Research: Oceans, vol. 103(C11), 1998, pp. 24937–24953. https://doi.org/10.1029/98JC02160.
  27. Dierssen H.M.: Perspectives on empirical approaches for ocean color remote sensing of chlorophyll in a changing climate. Proceedings of the National Academy of Sciences, vol. 107(40), 2010, pp. 17073–17078. https://doi.org/10.1073/pnas.0913800107.
  28. Gordon H.R., Brown O.B., Evans R.H., Brown J.W., Smith R.C., Baker K.S., Clark D.K.: A semianalytic radiance model of ocean color. Journal of Geophysical Research: Atmospheres, vol. 93(D9), 1988, pp. 10909–10924. https://doi.org/10.1029/JD093iD09p10909.
  29. Zeng C., Xu H., Fischer A.M.: Chlorophyll-a estimation around the Antarctica peninsula using satellite algorithms: hints from field water leaving reflectance. Sensors, vol. 16(12), 2016, 2075. https://doi.org/10.3390/s16122075.
  30. Handoko E., Hayati N., Syariz M., Hanansyah M.: Analysis of chlorophyll-a variability in the Eastern Indonesian waters using Sentinel-3 OLCI from 2020–2021. Forum Geografi, vol. 38(1), 2024, pp. 74–82. https://doi.org/10.23917/forgeo.v38i1.2361.
  31. Hendiarti N., Suwarso E.A., Amri K., Andiastuti R., Sachoemar S.I., Wahyono I.B.: Seasonal variation of pelagic fish catch around Java. Oceanography, vol. 18(4), 2005, pp. 112–123. https://doi.org/10.5670/oceanog.2005.12.
  32. Wijaya A., Zakiyah U.M.I., Sambah A.B., Setyohadi D.: Spatio-temporal variability of temperature and chlorophyll-a concentration of sea surface in Bali Strait, Indonesia. Biodiversitas Journal of Biological Diversity, vol. 21(11), 2020, pp. 5283–5290. https://doi.org/10.13057/biodiv/d211132.
  33. Puspasari R., Rahmawati P.F., Prianto E.: The effect of ENSO (El Nino Southern Oscillation) phenomenon on fishing season of small pelagic fishes in Indonesia waters. IOP Conference Series: Earth and Environmental Science, vol. 934(1), 2021, 012018. https://doi.org/10.1088/1755-1315/934/1/012018.
  34. Maisyarah S., Wirasatriya A., Marwoto J., Subardjo P., Prasetyawan I.B.: The effect of the ENSO on the variability of SST and chlorophyll-a in the South China Sea. IOP Conference Series: Earth and Environmental Science, vol. 246(1), 2019, 012027. https://doi.org/10.1088/1755-1315/246/1/012027.
  35. Dwiyanti A., Maslukah L., Rifai A.: Pengaruh Suhu Permukaan Laut (SPL) dan Klorofil-A Terhadap Hasil Tangkapan Ikan Layang (Decapterus macrosoma) di Perairan Kabupaten Rembang, Jawa Tengah. Indonesian Journal of Oceanography, vol. 4(4), 2023, pp. 109–120. https://doi.org/10.14710/ijoce.v4i4.15708.
  36. Ahmad K., Conci N., Boato G., De Natale F.G.: USED: A large-scale social event detection dataset. [in:] MMSys ’16: Proceedings of the 7th International Conference on Multimedia Systems: Klagenfurt, Austria, May 10–13, 2016, Association for Computing Machinery, New York 2016, pp. 1–6. https://doi.org/10.1145/2910017.2910624.
  37. NASA Earth Observatory: Sea Surface Temperature & Chlorophyll. https://earthobservatory.nasa.gov/global-maps/MYD28M/MY1DMM_CHLORA [access: 22.06.2024].
Read More
Author biographies is not available.
Download this PDF file
PDF
Statistic
Read Counter : 148 Download : 75

Downloads

Download data is not yet available.