SITE SELECTION ANALYSIS FOR SUITABLE AQUACULTURE FISH POND IN ANDONI L.G.A. RIVERS STATE, NIGERIA

Richard J. U.; Chima Ogba

doi:10.29121/granthaalayah.v4.i3.2016.2806

Authors

Richard J. U. Department of Special Survey, Office of the Surveyor General, Moscow Road, Port Harcourt, NIGERIA
Dr. ChimaOgba MD. Geoid and Environmental Services, Limited, Rumuomasi, Portharcourt, NIGERIA

DOI:

https://doi.org/10.29121/granthaalayah.v4.i3.2016.2806

Keywords:

Aquaculture, DEM, Land Use/ Cover, Euclidean Distance, Site Selection, Suitability, Weighted Overlay

Abstract [English]

The Andoni Rivers, Creeks, and Lagoon have been under stress due to over fishing which has led to the extinction of many fishes and other aquatic species. The extinction of fish has also led to the modification of fishing methods from the previously known methods such as cast net, drag net, hook and line etc to a more sophisticated method like the cover bush, and Oyima in the big Rivers. The shortage of fish in the Rivers has also discourage youths from engaging themselves in fishing rather they choose to involved in crude oil theft, arm robbery, and kidnapping that are anti-people. This study utilizes GIS software and remote sensing technology for aquaculture site selection analysis in Andoni LGA, Rivers State, Nigeria that will create direct and indirect employment opportunities to the men, women, and the youths thereby eradicating youth’s restiveness in the area. The dataset used for the study are 2002 Landsat image, DEM data, and settlements point data. The software used is ArcGIS 10.1 for weighted over analysis and IDRISI TAIGA 16.0 for image classification. The three criteria (land use/ cover, DEM, settlement) were weighted in the weighted overlay tool with percentage of influence for lu/lc 40%, DEM 20%, and settlement 40%. The suitability model for aquaculture ponds was produced with seven (7) classes from not suitable class value “o” to very highly suitable class with value “6”. The very highly suitable class is made-up of 51 polygons with a total area of 278.1 Ha. this represents 1.0% of the total area (32928.4 Ha.), occurring more in the south and few in the northern map position along the Rivers. It was observed that the 51 polygons all have area that can support aquaculture ponds and also the location of it can support fresh and salt water ponds. The class o (not suitable) represents the water body in the study area covering an area of 8099.0 Ha. this represents 29.15% of the land area. It is not suitable because aquaculture cannot be sited in the water body since its serves as the food basket of the people. This study therefore justified that GIS and remote sensing integration can be used for aquaculture site selection because of the spatial components inherent in the criteria. The Local Government Authority should considered aquaculture programmes as key to the eradication of unemployment and youths restiveness through direct investment in the sector.

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References

Thompson O. A., and Mafimisebi T. E. Profitability of Selected Ventures in Catfish Aquaculture in Ondo State, Nigeria, Fish Aquac J, vol. 5, no. 2, http://dx.doi.org/10.4172/ 2150-3508.100096, 2014, 1 – 7.

FAO. Food and Agricultural Organization of the United Nations, Fisheries and Aquaculture Development, 2016, 1 -2.

FAO. Part 1 World Review of Fisheries and Aquaculture, the State of World Fisheries and Aquaculture 2014, Food and Agricultural Organisation of the United Nations, 2014, 1 – 6.

Green Economy and Trade. Fisheries and Aquaculture, 2013, 1 – 36, http://www.unep.org/greeneconomy/ Portal/88/ documents/ger/3.0_Fisheries.pdf.

FAO. The State of World Fisheries and Aquaculture 2010, FAO Fisheries and Aquaculture Department, Food and Agricultural Organisation of the United Nations, Rome, 2010, 21, http://www.fao.org/docrep/012/i1119t/i1119t.pdf.

Badmus O., Jabil I. Y., Adedeji F. A., and Yacim S. E. Small Scale Aquaculture: A Panacea to Poverty Alleviation and Food Security in Alimosho Area, Lagos State Nigeria, Department of Agriculture Extension, Federal College of Animal Health & Production, Jos Nigeria, 2013, 1 – 24.

Michael S. Aquaculture – The Benefits of Aquaculture, 2014, http://fishery.about.com/od/BenefitsofAquaculture/a/AquacultureBenefits.htm.

Oluwasola O., and Ajayi D. Socio-Economic and Policy Issues Determining Sustainable Fish Farming in Nigeria, African Journal of Agriculture Economics and Rural Development, Vol. 1, No. 1, 2012, 035 – 041. DOI: https://doi.org/10.5897/IJLP12.013

James M. K., and Jose A. M. Geographic Information Systems, Remote Sensing and Mapping for the Development and Management of Marine Aquaculture, FAO Fisheries Technical Paper 458, 2007, 11 – 100.

Shree S. N., John P. B., Lindsay G. R., and Jose A. M. Application of Geographic Information Systems (GIS) for Spatial Decision Support in Aquaculture, Aquaculture Engineering Vol. 23 (2000), 1999, 233 – 278. DOI: https://doi.org/10.1016/S0144-8609(00)00051-0

Dao H. G., Yang Y., and Amararatne Y. GIS for Evaluation for Shrimp Farming in Haiphong of Vietnam, Ocean and Coastal Management, Vol. 48, Issue 1, 2005, 51 – 63. DOI: https://doi.org/10.1016/j.ocecoaman.2004.11.003

Shen L. GIS-Based Multi-criteria Analysis for Aquaculture Site Selection, Dr. Bin J. Examiner, Dr. Anders B. Supervisor, Department of Industrial Development, IT and Land Management, University of Gavle, 2010, 1 - 51.

Zainul H. Application of GIS for Assessing Prawn Farm Development in Tully-Cardwell, North Queensland, Jurnal KELAUTAN Vol. 4, No. 2, 2011, 62 – 67.

Raj C., and Karuppasamy S. Marine Fishery Information System and Aquaculture Site Selection Using Remote Sensing and GIS, International Journal of Advanced Remote Sensing and GIS, Vol. 1, Issue 1, ISSN 2320-0243, 2012, 20 – 33.

Raushan K. R., and Nikunj B. G. Study on Potential Application of Geographic Information Systems (GIS) to Find Out Suitable Aquaculture Site in Pune – Maharashtra India, International Journal of Advanced Remote Sensing and GIS, Vol. 3, Issue 1, (2014, 669 – 680.

Simms A. GIS and Aquaculture: Assessment of Soft-Shell Clam Sites, Journal of Coastal Conservation, Vol. 8, 2002, 35 – 47. DOI: https://doi.org/10.1652/1400-0350(2002)008[0035:GAAAOS]2.0.CO;2

Buitrago J., Rada M., Hernandez H., and Buitrago E. A Single-use Site Selection Technique, Using GIS, for Aquaculture Planning: Choosing Locations for Mangrove Oyster Raft Culture in Margarita Island, Venezuela, Environmental Management, Vol. 35, No. 5, 2005, 544 – 556. DOI: https://doi.org/10.1007/s00267-004-0087-9

Longdill P. C., Healy T. R., and Black K. P. An Intergrated GIS Approach for Sustainable Aquaculture Management Area Site Selection, Ocean & Coastal Management, Vol. 51, No. 8, 2008, 612 – 624. DOI: https://doi.org/10.1016/j.ocecoaman.2008.06.010

Giap D. H., Yi Y., Cuong N. X., Luu L. T., Diana J. S., and Lin C. K.. Application of GIS and Remote Sensing for Assessing Watershed Ponds for Aquaculture Development in Thai Nguyen, Vietnam, In Map Asia 2003 Conference, 2003.

Nwabueze A. A. The Role of Woman in Sustainable Aquaculture Development in Delta State, Journal of Sustainable Development in Africa, Vol 12, No. 5, 2010, 284 – 293.

Uqwunba C. O. A. Environmental Sustainability and Profitability of Integrated Fish Cum Crop Farming in Anambra State, Nigeria, Agricultural Journal, Vol. 5, No. 3, 2010, 229 – 233. DOI: https://doi.org/10.3923/aj.2010.229.233

Adeniyi B. T., Kuton M. P., Ayegbokiki A. O., and Lawal H. O. Economic Analysis of Costs and Return of Fish Farming in Sika-East Local Government Area of Oyo State, Nigeria, Aquac Res Development, Vol. 6, No. 2, 2015, 1 -5, http://dx.doi.org/10.4172/2155-9546.1000306. DOI: https://doi.org/10.4172/2155-9546.1000306

Ojiako J. C. , Okafor C. M., and Igbokwe E. C. Geospatial Mapping of Fish Farms in Anambra State Using GIS Approach, International Journal of Scientific & Engineering Research, Vol. 6, Issue, 11, 2015, 42 – 53.

National Bureau of Statistics, “Official Gazette (FGP 71/52007/2500 OL24), National and State Provisional Total 2006 Census,” 2006.

Isebor C. E., Ajayi T. O., and Anyanwu A. The Incidence of NypaFruticans (Wurmb) and it’s Impact on Fisheries Production in the Nger Delta Mangrove Ecosystem, Nigerian Institute for Oceanography and Marine Research, Victoria Island Lagos, Nigeria, 2003, 1- 4.

Imaobong E. E., and Mandu A. E. Development, Prospects and Challenges of Artisanal Fisheries in Akwa Ibom State, Nigeria, International Journal of Environmental Science, Management and Engineering Research, Vol 2, No. 3, 2013, 68 – 86.

Thomas L. W. Site Selection of Levee-Type Fish Production Ponds, Southern Regional Aquaculture Center, SRAC Production No. 100, 1988, 1 – 2.

James T. D. Red Drum Site Selection and Pond Construction, Southern Regional Aquaculture Center, SRAC Production No. 321, 1990, 1 – 4.

Hoffmann E. Generating High-Resolution Digital Elevation Models for Wetland

Research Using Google Earth (TM) Imagery- an Example from South Africa, water, 2010, 1-24.

Sadeg H. A. Accuracy Evaluation of SRTM (use in Google Earth) by Comparison with National Topographic Map (1:50,000) in North of Iraq, Eng. & Tech. Journal, Vol. 28, No. 21, 2010, 1-10.

Heywood I., Cornelius S., and Carver S. An Introduction to Geographic Information System, 3rd Edition, Pearson Education Limited, Edinburgh Gate Harlow Essex CM20 2JE England, 2006, 77 - 91.

Richard J. U. Object-Oriented Classification Using Aerial Photograph and Spot Image of Eagle Island Port Harcourt, Rivers State, Nigeria, International Journal of Advance Research, IJOAR .ORG, Vol. 3, Issue 12, December 2015, Online: ISSN 2320-9186, 2015, 11 – 23.

Lucky C. C. Object-Oriented Image Classification of Individual Tree Using Erdas Imagine Objective: Case Study of Wanjohi Area, Lake Naivasha Basin, Proceedings, Kenya Geothermal Conference 2011, Kenyatta International Conference Centre Nairobi, November 21- 22, 2011, 2011, 1 – 9.

Li F., Jian C., and Yongheng Z. Object-Oriented Classification of High-Resolution Remotely Sensed Imagery, International Conference on Computer Technology and Science (ICCTS), IPCSIT vol. 47, LACSIT Press, Singapore, DOI: 10.7763/IPCSIT.2012. V47.76, 2012, 411 – 416.

Anderson J. R., Ernest E. H., John T. R., and Richard E. W. A Land Use and Land Cover Classification System for Use With Remote Sensor Data, Geological Survey Professional Paper 964, A Revision of the Land Use Classification System as Presented in U.S. Geological Survey Circular 671, 1976, 1 – 41. DOI: https://doi.org/10.3133/pp964

Khalid E. Developing a GIS-Based MCE Site Selection Tool in ArcGIS using COM Technology, the International Arab Journal of Information Technology, Vol. 10, No. 3, (2013, 1 - 7.

Jimmy L. A. Site Selection of Levee-Type Fish Production Ponds, Southern Regional Aquaculture Center, SRAC Publication No. 100, 2010, 1 – 8.

John W. J. Watershed Fish Production Ponds Site Selection and Construction, Texas Agricultural Extension Service, Southern Regional Aquaculture Center, SRAC Publication No. 102, 1989, 1 – 4.

Louis A. H., and Garland B. P. Pond Construction: Some Practical Considerations, Wirginia Cooperative Extension, Fisheries and Wildlife, Publication 420-011, 1997, 1 – 4.

Gregory N. W. Watershed Fish Production Ponds Guide to Site Selection and Construction, Southern Regional Aquaculture Center, SRAC Publication No. 102, 2002, 1 – 6.

Michael P. M. Cage Culture Site Selection and Water Quality, Southern Regional Aquaculture Center, SRAC Publication No. 161, 1997, 1 – 4.

Larry W. B. and Robert P. R. Crawfish Culture Site Selection, Pond Construction and Water Quality, Southern Regional Aquaculture Center, SRAC Publication No. 240, 1990, 1 – 4.