Published August 23, 2017 | Version v1
Journal article Open

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

  • 1. Department of Special Survey, Office of the Surveyor General, Moscow Road, Port Harcourt, NIGERIA
  • 2. MD. Geoid and Environmental Services, Limited, Rumuomasi, Portharcourt, NIGERIA

Description

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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