Authors : Abdullahi Fatima; Yahaya Ilemona; Rose Peter; Ameh Friday; Victor Taiwo Salami; John Ogbole

Volume/Issue : Volume 11 - 2026, Issue 9 - September

Google Scholar : https://tinyurl.com/yc4cb9hh

DOI : https://doi.org/10.38124/ijisrt/26sep068

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Due to the influx of people and the increase in the population in urban centers, the demand for residential houses has become a major concern for town planners today. With the high increase in urbanization as a result of the increase in the population, residential houses are becoming more difficult to find. Planners aim at developing new ideas to solve the problem of the high increase in the demand for residential buildings. In recent times, different approaches to analysis have been introduced that will help planners select the most suitable locations for building residential houses. This study aims to analyze suitable sites for future housing development in Osogbo Local Government Area of Osun State. A combination of nearest neighbour analysis, Chi-square, geographical information system, and analytical hierarchical process techniques (AHP) were used in the present study. A total of nine thematic layers, such as land use/land cover, elevation, slope, aspect, population density, proximity to road networks, proximity to tourist centres, and geology, were prepared and studied for site suitability analysis. The weights assigned to each class in all the thematic maps are based on their characteristics and significance for selection of suitable sites through the AHP method. The site suitability map thus obtained was categorized into five classes-not suitable, less suitable, slightly suitable, more suitable and most suitable. The study reveals that the southern, eastern, and a part of the western sides of the study area are suitable for building residential houses.

Keywords : Geographic Information System; Remote Sensing; Suitability Analysis.

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