Sains Malaysiana 47(7)(2018): 1369–1378

http://dx.doi.org/10.17576/jsm-2018-4707-03

Predicting Potential Rastrelliger kanagurta Fish Habitat using MODIS Satellite Data and GIS Modeling: A Case Study of Exclusive Economic Zone, Malaysia

(Peramalan Potensi Habitat Ikan Rastrelliger kanagurta menggunakan Data Satelit MODIS dan Pemodelan GIS: Kajian Kes di Zon Ekonomi Eksklusif, Malaysia)

SHAARI, N.R. & MUSTAPHA, M.A.*

School of Environmental Science and Natural Resources, Faculty of Science and Technology

Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor Darul Ehsan, Malaysia

Received: 14 September 2017/Accepted: 3 March 2018

ABSTRACT

Remote sensing and GIS are robust tools in detection of fishing grounds which is important in providing fish sustainability for human being. This recent tool allows fishing grounds detection at minimal cost and optimizes effort. The objectives of this study were to investigate the relationship between R. kanagurta fishing grounds with environmental factors and to determine its potential fishing grounds. MODIS derived satellite data of Chl-a and sea surface temperature (SST) and fisheries catch data of 2008 and 2009 were analyzed using suitability index (SI) and generalized additive model (GAM) in the Exclusive Economic Zone (EEZ) off the East Coast of Peninsular Malaysia. Distribution of R. kanagurta was associated with preferred range of 0.20 to 0.30 mg/m3 for Chl-a and 29 to 30°C for SST. GAM indicated that these parameters influenced fish distribution (p<0.001). Potential fishing ground maps derived from the SI and GAM model indicated accuracy at 75% with kappa of 0.7 and accuracy at 87.6% with kappa of 0.8, respectively. This study indicated the capability of GAM as an exploratory tool to map the potential fishing grounds of R. kanagurta in the EEZ waters.

Keywords: Fisheries spatial prediction; generalized additive model; MODIS; suitability index model

ABSTRAK

Penderiaan jauh dan GIS merupakan pendekatan yang digunakan untk mengesan kawasan tangkapan ikan yang sangat penting dalam memastikan kelangsungan ikan untuk keperluan manusia. Ia membantu dalam penentuan kawasan tangkapan ikan dengan kos yang minimum dan usaha yang optimum. Objektif dalam kajian ini adalah untuk mengkaji perhubungan antara kawasan tangkapan ikan R. kanagurta dengan faktor persekitaran dan menentukan kawasan potensi tangkapan ikan. Data satelit Klorofil-a dan suhu permukaan laut (SPL) yang diperoleh daripada MODIS dan juga data-data ikan bagi tahun 2008 dan 2009 dianalisis menggunakan indeks kesesuaian (SI) dan model aditif umum (GAM) di kawasan Zon Ekonomi Eksklusif (ZEE) pantai timur Semenanjung Malaysia. Keputusan kajian mendapati taburan ikan R. kanagurta berasosiasi dengan julat kesesuaian antara 0.20 hingga 0.30 mg/m3 bagi Klorofil-a dan 29 hingga 30°C bagi SPL. GAM menunjukkan parameter ini mempengaruhi taburan ikan (p<0.001). Peta kawasan potensi tangkapan ikan yang diperoleh daripada Indeks Kesesuaian (SI) dan model GAM menunjukkan ketepatan pada 75% masing-masing dengan Kappa 0.7 dan ketepatan 87.6% dengan kappa 0.8. Kajian ini menunjukkan kebolehan GAM sebagai kaedah dalam penentuan kawasan potensi tangkapan ikan R. kanagurta di perairan ZEE.

Kata kunci: Model aditif umum; model indeks kesuaian; MODIS; ramalan reruang perikanan

REFERENCES

Akhir, M.F. 2012. Surface circulation and temperature distribution of Southern South China Sea from global ocean model (OCCAM). Sains Malaysiana 41(6): 701-714.

Akhir, M.F., Zakaria, N.Z. & Tangang, F. 2014. Intermonsoon variation of physical characteristics and current circulation along the east coast of Peninsular Malaysia. International Journal of Oceanography 2014: 1-9.

Andrade, H.A. & Garcia, C.A.E. 1999. Skipjack tuna fishery in relation to sea surface temperature off the southern Brazilian Coast. Fisheries Oceanography 8(4): 245-254.

Chandran, R.V., Jeyaram, A., Jayaraman, V., Manoj, S., Rajitha, K. & Mukherjee, C.K. 2009. Prioritization of satellite derived potential fishery grounds: An analytical hierarchical approach-based model using spatial and non-spatial data. International Journal of Remote Sensing 30(17): 4479-4491.

Checkley, D.M., Dotson, R.C. & Griffith, D.A. 2000. Continuous, underway sampling of eggs of Pacific sardine (Sardinops sagax) and northern anchovy (Engraulis mordax) in spring 1996 and 1997 off southern and central California. Deep Sea Research Part II 47: 1139-1155.

Daryabor, F., Tangang, F. & Juneng, L. 2014. Simulation of southwest monsoon current circulation and temperature in the east coast of Peninsular Malaysia. Sains Malaysiana 43(3): 389-398.

Fox, M.F., Kester, D.R. & Yoder, J.A. 2005. Spatial and temporal distributions of surface temperature and chlorophyll in the Gulf of Maine during 1998 using SeaWiFS and AVHRR imagery. Marine Chemistry 97: 104-123.

Hastie, T.J. & Tibshirani, R.J. 1990. Generalized Additive Models. London: Chapman & Hall.

Lanz, E., Manuel, N.M., Juana, L.M. & Dworak, J.A. 2009. Small pelagic fish catches in the Gulf of California associated with sea surface temperature and chlorophyll. CalCOFI Report 50: 134-146.

Lau, K.M., Wu, H.T. & Yang, S. 1998. Hydrologic processes associated with the first transition of the Asian Summer Monsoon: A pilot satellite study. Bulletin American Meteorological Society 79: 1871-1882.

Maddock, I. 1999. The importance of physical habitat assessment for evaluating river health. Freshwater Biology 41: 373-391.

Maged, M. 2009. Linear algorithm for salinity distribution modelling from MODIS data. Proceedings of Geoscience and Remote Sensing Symposium, Cape Town, South Africa.

Mustapha, A.M., Chan, Y.L. & Lihan, T. 2010. Mapping of potential fishing grounds of Rastrelliger kanagurta (Cuvier, 1817) using satellite images. Proceedings of Map Asia & ISG 2010, July 2010, Kuala Lumpur, Malaysia.

Nurdin, S., Lihan, T. & Mustapha, A.M. 2012. Mapping of potential fishing grounds of Rastrelliger kanagurta (Cuvier, 1816) in the Archipelagic Waters of Spermonde Indonesia Using Satellite Images. Proceedings of Malaysia Geospatial Forum, March 2013, Melaka, Malaysia.

Nurdin, S., Mustapha, M.A., Lihan, T. & Ghaffar, M.A. 2015. Determination of potential fishing grounds of Rastrelliger kanagurta using satellite remote sensing and GIS technique. Sains Malaysiana 44(2): 225-232.

O’Reilly, J.E., Maritorena, S., Mitchell, B.G., Siegel, D.A., Carder, K.L., Garver, S.A., Kahru, M. & McClain, C.R. 1998. Ocean color chlorophyll algorithms for SeaWiFS. Journal of Geophysical Research 103: 24937-24953.

Palacios, D.M., Bograd, S.J., Foley, D.G. & Scwing, F.B. 2006. Oceanographic characteristics of biological hot spots in the North Pacific: A remote sensing perspective. Deep-Sea Research Part II 53: 250-269.

Rajapaksha, J.K., Samarakoon, L. & Gunathilaka, A.A.J.K. 2013. Environmental preferences of Yellowfin Tuna in the Northeast Indian Ocean: An application of satellite data to longline Catches. International Journal of Fisheries and Aquatic Sciences 2(4): 72-80.

Razib, N.A. & Mustapha, M.A. 2013. Spatial distribution of Rastrelliger kanagurta (cuvier 1817) in the South China Sea exclusive economic zone (eez). UKM-FST Postgraduate Colloqium 2013, American Institute of Physics Conference Proceedings, July 2013, Bangi, Malaysia.

Saadon, M.N. & Camerlengo, A. 1994. Interannual and seasonal variability of the mixed layer depth of the South China Sea. Paper Read at National Conference on Climate Change. pp. 141-151.

Sachoemar, S.I.T., Yanagi, N., Hendiarti, M., Sadly & Meliani, F. 2010. Seasonal variability of sea surface chlorophyll-a and abundance of pelagic fish in Lampung Bay, Southern Coastal Area of Sumatra, Indonesia. Coastal Marine Science 34: 82-90.

Santos, A.M.P. 2000. Fisheries oceanography using satellite and airborne remote sensing methods: a review. Fisheries Research 49: 1-20.

Selvin, J. & Lipton, A.P. 2012. Impact of environmental variables on pelagic fish landings: Special emphasis on Indian oil sardine off Tiruchendur coast, Gulf of Mannar. Journal of Oceanography and Marine Science 3(3): 56-67.

Shaari, F. & Mustapha, M.A. 2017. Factors influencing the distribution of chl-a along coastal waters of East Peninsular Malaysia. Sains Malaysiana 46(8): 1191-1200.

Solanki, H.U., Dwivedi, R.M., Nayak, S.R., Naik, S.K., John, M.E. & Somvanshi, V.S. 2005. Cover: Application of remotely sensed closely coupled biological and physical process for marine fishery resources exploration. International Journal of Remote Sensing 26(10): 2029-2034.

Nazmi, S.M., Mustapha, A.M. & Lihan, T. 2013. Satellite derived measurements of coastal water chlorophyll-a variability. World Applied Sciences Journal 21(6): 879-887.

Terrel, J.W. 1984. Proceedings of a Workshop on Fish Habitat Suitability Index Models. US Fish and Wildlife Service Biological Report 85(6): 1-393.

Vasconcelos, R.P., Le Pape, O., Costa, M.J. & Cabral, H.N. 2013. Predicting estuarine use patterns of juvenile fish with generalized linear models. Estuarine, Coastal and Shelf Science 120: 64-74.

Wakeley, J.S. 1988. A method to create simplified versions of existing Habitat Suitability Index (HSI) models. Environmental Management 1: 79-83.

Walton, C.C., Pichel, W.G., Sapper, J.F. & May, D.A. 1998. The development and operational application of nonlinear algorithms for the measurement of sea surface temperatures with the NOAA polar-orbiting environmental satellites. Journal of Geophysical Research 103(C12): 27999-28012.

Wang, W., Zhou, C., Shao, Q. & Mulla, D.J. 2010. Remote sensing of sea surface temperature and Chlorophyll-a: Implications for squid fisheries in the north-west Pacific Ocean. International Journal of Remote Sensing 31(17-18): 4515-4530.

Xian, T., Sun, L., Yang, Y. & Fu, Y. 2012. Monsoon and eddy forcing of Chlorophyll-a variation in the northeast South China Sea. International Journal of Remote Sensing 33(23): 7431-7443.

Yee, T.W. & Mitchell, N.D. 1991. Generalized additive models in plant ecology. Journal of Vegetation Science 2: 587-602.

Yu, W., Chen, X., Yi, Q., Chen, Y. & Zhang, Y. 2015. Variability of suitable habitat of western winter-spring cohort for neon flying squid in the northwest pacific under anomalous environments. PLoS ONE 10(4): e0122997.

Zainuddin, M., Saitoh, K. & Saitoh, S. 2004. Detection of potential fishing ground for albacore tuna using synoptic measurements of ocean color and thermal remote sensing in the Northwestern North Pacific. Geophysical Research Letters 31: L20311.

Zainuddin, M., Kiyofuji, H., Saitoh, K. & Saitoh, S. 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: Topical Studies in Oceanography 53(3-4): 419-431.

Zainuddin, M., Saitoh, K. & Saitoh, S. 2008. Albacore (Thunnus alalunga) fishing ground in relation to oceanographic conditions in the western North Pacific Ocean using remotely sensed satellite data. Fisheries Oceanography 17: 61-73.

Zainuddin, M. 2011. Skipjack Tuna in relation to sea surface temperature and Chlorophyll-a concentration of Bone Bay using remotely sensed satellite data. Jurnal Ilmu dan Teknologi Kelautan Tropis 3(1): 82-90.

*Corresponding author; email: muzz@ukm.edu.my