Evaluating the area sports facilities serve and providing an optimal model for site selection - Case study: Kashan

IntroductionAs a land use specially designed for physical activity, recreation and leisure, sports facilities are considered to be a public space vital for the society, improving health and well-being of the community. Therefore, special attention should be paid to the pattern of distribution, easy access to these land uses, and spatial organization of these facilities in accordance with the pattern of road networks. Accordingly, the pattern in which sport facilities are distributed across urban areas can have a direct impact on the desired operational efficiency of the city. Therefore, optimal site selection and easy access to sports facilities are of great importance for a healthy city and a healthy community. A huge difference between per capita sports areas and the standard per capita or imbalanced distribution of sports facilities in the region may result in reduced interest in physical activities and threaten the health of individual and society. Accordingly, the present study has evaluated per capita sports spaces in Kashan, and the spatial distribution of these facilities. The average time required for accessing these spaces has also been measured in accordance with the local road network and the total area each facility serves. Finally, an optimal model has been proposed for sports related land use in Kashan. Materials & MethodsThe present descriptive-analytical study is applied in nature and uses ArcGIS and SuperDecisions software to analyze its descriptive and spatial data. To provide an optimal model, 11 indicators including area each land use serves, its quality, urban land use, population density, health centers, educational centers, distance from faults, distance from urban waterways, fuel centers, distance from industries, parks and green spaces were identified based on expert opinions. The importance of each indicator was also determined based on expert opinions using the ANP model, and weighted linear combination was used to combine the previously mentioned indicators in GIS. A brief summary of the models used are presented in the following section.  Results and discussionThe nearest neighbor algorithm is used to evaluate the spatial distribution regardless of the total area of each sports facility. Results indicate the presence of a completely clustered distribution (P = 0.000 and Z = -3.368) at the level of 99%. Finally, the relative weight of each criteria is combined with the relative weight of each option obtained from ANP model using the weighted combination in GIS to reach an optimal model for site selection. The resulting value actually indicates the necessity of new sports facilities. In other words, higher values show higher priority and as it is shown, about 40% of the total area of Kashan is potentially appropriate for new sports facilities while about 60% of the city area is not suitable for such facilities. ConclusionOptimal site selection maximizes the efficiency of sports facilities and improves the quality of services for those using the areas. Therefore, the present study aims to evaluate the area each sports center is serving and provide an optimal model for site selection in Kashan. In 2016, Kashan had a population of about 304 thousand people and about 202 thousand meters of sports related land use. Thus, there was a 0.67 square meters per capita sports related land use in Kashan. Finally, 11 indicators were combined using the weighted combination to reach an optimal model. Results showed that about 40% of the total area of Kashan is potentially appropriate (relatively appropriate and completely appropriate) for new sports centers while about 60% of this urban area is not suitable for construction of such facilities. Moreover, results proves the efficiency of spatial statistics used to evaluate spatial distribution of land uses. As it is shown in the present study, GIS can provide an optimal model for site selection using practical indicators and appropriate data analysis methods. In general, results indicate that sports facilities in Kashan are not generally in a good condition in terms of per capita and distribution pattern which confirms the fact that these issues were not considered important in the process of site selection.