Graph-Theoretic Approach to Resolving the Accessibility and Site Selection Issues in Planning and Development

Ayotunde Olawande Oni, Dolapo Bose Akindele, Omolade Akinjare

Abstract


The basic goal of an investment in real estate is to make the highest positive net return possible, and the process of attaining this commences at the site selection stage with accessibility being of paramount consideration. Many investors, appraisers, planners and developers often base site selection and analysis of accessibility on intuition and mere physical observation of neighborhoods without scientific approach. The aim of this study is therefore to examine the application of graph-theoretic analysis in resolving the challenge of improper site selection process and accessibility issues in real estate planning development. In attaining the aim, the satellite map of the study area was derived and converted into linear graph regardless of the width, length and quality of roads. The nodal points of roads that form the network were serially numbered and translated into simple matrix of the number to obtain the accessibility indices for the ranking of access routes in the study area. The study found that the graph-theoretic approach was useful in analyzing and resolving the accessibility and site selection issues in real estate development process. The findings would provide better understanding of determination of accessibility which hitherto had been done by mere intuition by real estate appraisers and planners through the application of the approach. This is applicable to inform developers take decision relating to choice of locations by scientifically establishing the most accessibility location and thus assists in site selection. Also, it would assist the development appraisers in the ranking of several of locations along arterial routes with a view to determining sustainable physical developments.

DOI: 10.5901/mjss.2014.v5n8p11


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This work is licensed under Creative Commons Attribution 3.0 License.

Mediterranean Journal of Social Sciences ISSN 2039-9340(Print) ISSN 2039-2117(Online)

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