Argo Galih Suhadha, Wikanti Asriningrum


Research in Potential Fishing Zone (PFZ) has undergone many developments, including parameter suitability selection. The thermal front has become the primary parameter input of ZPPI (LAPAN's PFZ). The accuracy of the thermal front parameter to predict PFZ cannot be known with certainty because of the radius between ZPPI with fishing areas, so it is necessary to develop parameters to support the thermal front. The thermal front described the meeting area of two water masses with different temperature characteristics associated with high nutrients (chlorophyll-a) and indicate an upwelling's appearance. This study aims to determine ZPPI by approaching the thermal front and mesotrophic area's matching area (chlorophyll-a concentration 0.2-0.5 mg/m3). Chlorophyll-a and sea surface temperature data for thermal fronts detection are derived from Aqua MODIS satellite on Google Earth Engine (GEE). The matching area's approach between the thermal front and mesotrophic area is used in the analysis of ZPPI. The results show thermal front and mesotrophic area on WPPNRI 715 have a variation seasonally where December appears like the peak event. The two parameters are distributed evenly from coastal areas to high seas. This method generates thermal fronts that have more than 60.3% matching with the mesotrophic area where the amount is acceptable due to has more than 50% amount of moderate ZPPI. The accuracy improvement in ZPPI both on the coast and open sea can be determined through this approach.


Bourke, P. 1988. Calculating the area and centroid of a polygon. http://local.wasp.uwa.edu.au/˜pbourke/geometry/lineline/polyarea/. [Retrieved on November 1, 2019]
Cayula, J. & P. Cornillon. 1992. Edge detection algorithm for SST images. J. Atmospheric and Oceanic Technology, 9(1): 67-80. https://doi.org/10.1175/1520-0426(1992)009<0067:EDAFSI>2.0.CO;2
Chang, Y. & P. Cornillon. 2015. A comparison of satellite-derived sea surface temperature fronts using two edge detection algorithms. Deep-Dea Research Part II: Topical Studies in Oceanography, 119(1): 40-47. https://doi.org/10.1016/j.dsr2.2013.12.001
El-Serehy, H.A., H.S. Abdallah, F.A. Al-Misned, S.A. Al-Farraj, & K.A. Al-Rasheid. 2018. Assessing water quality and classifying trophic status for scientifically based managing the water resources of the Lake Timsah, the lake with salinity stratification along the Suez Canal Saudi. J. Biol. Sci., 25(1): 1247-1256. https://doi.org/10.1016/j.sjbs.2018.05.022
ESRI. 2018. Melakukan automasi tugas dengan model builder. https://community.esri.com/groups/arcnesia/blog/2018/02/07/melakukan-automasi-tugas-dengan-model-builder. [Retrieved on October 1, 2019]
Gorelick, N., M. Hancher, M. Dixon, S. Ilyushenchenko, D. Thau, & R. Moore. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment, 202(1): 18-17. https://doi.org/10.1016/j.rse.2017.06.031
Lumban-Gaol, J., R.R. Leben, S. Vignudelli, K. Mahapatra, Y. Okada, B. Nababan, M. Mei-Ling, K. Amri, R.E. Arhatin, & M. Syahdan. 2015. Variability of satellite-derived sea surface height anomaly, and its relationship with Bigeye tuna (Thunnus obesus) catch in the Eastern Indian Ocean. European J. of Remote Sensing, 48(1): 465–477. https://doi.org/10.5721/EuJRS20154826
Gordon, A.L., A. Ffield, & A.G. Ilahude. 1994. Thermocline of the Flores and Banda Seas. J. of Geophysical Research, 99(C9): 18235-18242. http://doi.org/10.1029/94jc01434
Hamzah, R., T. Prayogo, & W.K. Harsanugraha. 2014. Identifikasi thermal front dari data satelit Terra/Aqua MODIS menggunakan metode Single Image Edge Detection (SIED) (Studi kasus: Perairan utara dan selatan Pulau Jawa). In: Kartasasmita et al. (eds.). Prosiding Seminar Nasional Penginderaan Jauh 2014, IPB International Convention Center, Bogor, 21 April 2014. 552-559 pp.
Hamzah, R., T. Prayogo, & S. Marpaung. 2016. Metode penentuan titik koordinat zona potensi penangkapan ikan pelagis berdasarkan hasil deteksi termal front suhu permukaan laut. J. Penginderaan Jauh, 13(2): 97-108. http://doi.org/10.30536/j.pjpdcd.2016.v13.a2364
Hanintyo, R., S. Hadianti, R.M.P. Mahardhika, A.J. Saputra, & F. Islamy. 2015. Sebaran musiman kejadian thermal front berdasarkan citra Aqua- MODIS di WPP-RI 715, 715, WPP-RI 716. In: Sambodo et al. (eds.). Prosiding Seminar Nasional Penginderaan Jauh 2015, IPB International Convention Center, Bogor, 11-12 November 2015. 523–635 pp.
Harsanugraha, W.K., T. Prayogo, S. Marpaung, R. Hamzah, B. Hasyim, G. Sitanggang, & A. Supriyono S.W. 2014. Pemanfaatan data satelit NPP dan Altimetri untuk penentuan Zona Potensi Penangkapan Ikan. Lembaga Penerbangan dan Antariksa Nasional. Jakarta. 97 p.
Iskandar, I., W. Mardiansyah, D.O. Lestari, & Y. Masumoto. 2020. What did determine the warming trend in the Indonesian sea?. Prog. Earth Planet Sci, 7(20): 1-11. https://doi.org/10.1186/s40645-020-00334-2
Jatisworo, D. & A. Murdimanto. 2013. Identifikasi thermal front di Selat Makassar dan Laut Banda. In: Wicaksono, P. et al. (eds.). Simposium Nasional Sains Geoinformasi III, University Club, Universitas Gadjah Mada, Yogyakarta, 25-26 September 2013. 226–232 pp.
Jishad, M., R.K. Sarangi, S. Ratheesh, S.M. Ali, & R. Sharma. 2019. Tracking fishing ground parameters in cloudy region using ocean colour and satellite-derived surface flow estimates: A study in the Bay of Bengal. J. of Operational Oceanography, 12(1): 1-12. https://doi.org/10.1080/1755876X.2019.1658566
Kang, J., L. Sui, X. Yang, Y. Liu, Z. Wang, J. Wang, F. Yang, B. Liu, & Y. Ma. 2019. Sea surface-visible aquaculture spatial-temporal distribution remote sensing: a case study in Liaoning Province, China from 2000 to 2018. Sustainability, 11(24): 1-23. https://doi.org/10.3390/su11247186
Nurdin, S., M.A. Mustapha, T. Lihan, & M. Zainuddin. 2017. Applicability of remote sensing oceanographic data in the detection of potential fishing grounds of Rastrelliger kanagurta in the archipelagic waters of Spermonde, Indonesia. Fisheries Research, 196(1): 1–12. https://doi.org/10.1016/j.fishres.2017.07.029
Podestá, G.P., J.A. Browder, & J.J. Hoey. 1993. Exploring the association between swordfish catch rates and thermal fronts on U.S. longline grounds in the Western North Atlantic. Continental Shelf Research, 13(2–3): 253–277. https://doi.org/10.1016/0278-4343(93)90109-B
Reese, D.C., R.T. O’Malley, R.D. Brodeur, & J.H. Churnside. 2011. Epipelagic fish distributions in relation to thermal fronts in a coastal upwelling system using high-resolution techniques. ICES J. of Marine Science, 68(9): 1865-1874. https://doi.org/10.1093/icesjms/fsr107
Rustini, H.A., E. Harsono, & I. Ridwansyah. 2018. Potential area for floating net fishery in Lake Toba. IOP Conf. Ser: Earth Environ. Sci. 118(1): 1-7. https://doi.org/10.1088/1755-1315/118/1/012032
Syah, A.F., L.W. Ramdani, & K.I. Suniada. 2020. Prediction of potential fishing zones for mackerel tuna (Euthynnus sp) in Bali strait using remotely sensed data. IOP Conf. Ser.: Earth Environ. Sc, 500(1): 1-11. https://doi.org/10.1088/1755-1315/500/1/012070
Sholva Y., B. Sitohang, & K. Wikantika. 2013. New approach to locate upwelling and thermal-front from satellite imagery data. Procedia Technology, 11(1): 317-326. http://doi.org/10.1016/j.protcy.2013.12.197
Sun, Q., Z. Wu, & J. Tan. 2012. The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environ. Earth Sci., 65(6): 1687-1694. https://doi.org/10.1007/s12665-011-1145-2
Suman, E., Wudianto, B. Sumiono, H.E. Irianto, Badrudin, & K. Amri. 2014. Potensi dan tingkat pemanfaatan sumberdaya ikan di Wilayah Pengelolaan Perikanan Republik Indonesia (WPP RI). Ref Grafika, Jakarta. 224 p.
Wen, Z., K. Song, L. Lyu, C. Fang, Y. Shang, G. Liu, & J. Du. 2020. A national-scale data set for dissolved carbon and its spatial pattern in lakes and reservoirs across China. Sci. Data, 7(82): 1-10. https://doi.org/10.1038/s41597-020-0419-5
Wijesekera, H.W., E. Shroyer, A. Tandon, M. Ravichandran, D. Sengupta, S. Jinadasa, H.J. Fernando, N. Agrawal, K. Arulananthan, & G. Bhat. 2016. ASIRI: an ocean-atmosphere initiative for Bay of Bengal. American Meteorological Society, 97(10): 1859-1884. https://doi.org/10.1175/BAMS-D-14-00197.1
Wyrtki, K. 1961. Physical oceanography of the southeast asian waters. NAGA REPORT. California. 195 p. https://doi.org/10.1001/archneur.1994.00540230067015
Zainuddin, M., H. Kiyofuji, K. Saitoh, & S.I. Saitoh. 2006. Using multi-sensor satellite remote sensing and catch data to detect ocean hot spots for Albacore (Thunnus alalunga) in the Northwestern North Pacific. DEEP-SEA RESEARCH Part II, 53(3-4): 419-431. http://doi.org/10.1016/j.dsr2.2006.01.007
Zainuddin, M. 2011. Skipjack tuna in relation to sea surface temperature and chlorophyll-a concentration of Bone Bay using remotely sensed satellite data. J. Ilmu dan Teknologi Kelautan Tropis, 3(1): 82-90. http://doi.org/10.29244/jitkt.v3i7837
Zhang, Y. & X. Hou. 2020. Characteristics of coastline changes on southeast Asia islands from 2000 to 2015. Remote Sensing, 12(3): 1-22. https://doi.org/10.3390/rs12030519


Argo Galih Suhadha
argo.galih@lapan.go.id (Primary Contact)
Wikanti Asriningrum
Author Biographies

Argo Galih Suhadha, Indonesian National Institute of Aeronautics and Space (LAPAN)

Remote Sensing Application Center

Wikanti Asriningrum, Indonesian National Institute of Aeronautics and Space (LAPAN)

Remote Sensing Application Center
SuhadhaA. G., & AsriningrumW. (2020). POTENTIAL FISHING ZONES ESTIMATION BASED ON APPROACH OF AREA MATCHING BETWEEN THERMAL FRONT AND MESOTROPHIC AREA. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 12(2), 565-581. https://doi.org/10.29244/jitkt.v12i2.28305

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