Application of GIS and remote sensed data in assessing suitable sites for fish farming :

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dc.contributor.author Komakech, Daniel
dc.date.accessioned 2022-04-05T06:22:56Z
dc.date.available 2022-04-05T06:22:56Z
dc.date.issued 2022
dc.identifier.citation Komakech, Daniel. (2022). Application of GIS and remote sensed data in assessing suitable sites for fish farming : case study : Greater Apac. Busitema University. Unpublished dissertation. en_US
dc.identifier.uri http://hdl.handle.net/20.500.12283/1016
dc.description Dissertation. en_US
dc.description.abstract Site selection for aquaculture development is a complex task involving identification of areas that are economically, socially and environmentally suitable, which can also be available for aquaculture. Geographic information systems and remote sensing technologies, which facilitate the integration and analysis of spatial and attribute data from multiple sources, have been widely used for selecting suitable sites for different land uses. This study used these technologies to identify sites suitable for fish farming in Greater Apac and assessed it for validation. The study developed map-based site selection criteria, using soil quality, stream water availability, DEM and slope. These criteria were then implemented, fish farm potential sites identified, the total area estimated and the suitability area validated. The study predicted that about 483.91 km2 (15%) were highly suitable of the total arable area in Greater Apac. The study estimates that most of the soil samples collected from the sample villages and tested corresponded with the results from the model. en_US
dc.description.sponsorship Mr. Mugisha Moses, Busitema University en_US
dc.language.iso en en_US
dc.publisher Busitema University en_US
dc.subject Aquaculture en_US
dc.subject Land uses en_US
dc.subject Fish farming en_US
dc.subject Soil quality en_US
dc.title Application of GIS and remote sensed data in assessing suitable sites for fish farming : en_US
dc.title.alternative case study : Greater Apac. en_US
dc.type Thesis en_US


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