Demand for residential houses in urban areas has become a major problem facing town planners today. With the high increase in urbanization due to the increase in population, residential houses are becoming more difficult to find. Planners aim at developing new ideas to combat the high increase in the demand for residential buildings. In recent times, different methods of analysis have been introduced that will help planners select best locations to erect residential houses. A Geographic information system (GIS) is one of the tools for analyzing and storing a great deal of information. Over the years, GIS technology has been introduced into planning and the result has been of great help to urban planners in planning sustainable environment for residents. This research aims at using GIS technology and multi-criteria decision analysis (MCDA) to determine possible locations to build residential houses and analyzing different methods of selecting suitability areas within the study area. An MCDA map was produced from the combination of different factors and constraint which include elevation, orientation of the building (direction), the soil type and land use type. Proximity analysis was also done to find out how infrastructures (existing roads, shopping malls and health care enter) are close to the study area. Results show that the southern, eastern, and a part of western side of the study area is better to build residential houses than other areas. Three different methods (visual interpretation method, seeding method and neighborhood method) where used to find out which method produces the most suitable locations within the study area. In order to calculate the suitability areas and suitability values, the sum of pixel values were calculated for each method. The visual interpretation method servers as a standard method of deciding the suitability area covers 15,375 m² and has the highest suitability values of about 500 pixels. The seeding method was used as an automatic method for selecting the suitability area; result shows that the suitability area covers 17,421 m² and has the highest suitability value of about 1200 pixels. The neighborhood method was calculated using two different statistics (mean statistics and majority statistics). The mean statistics covers an area of 12,439 m² while the majority statistics covers an area of 14,332 m². From analysis carried out, the seeding method is preferred for selecting suitability areas than the visual interpretation method and the neighborhood method but the visual interpretation method covers more suitability area than the seeding method and neighborhood method.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hig-23643 |
| Date | January 2013 |
| Creators | Agbauduta, Stephen Ogba |
| Publisher | Högskolan i Gävle, Samhällsbyggnad, GIS |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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