Determining Parking Demand and Locating Parking Areas Using Geographic Analytics Methods

Abstract

Worldwide, growing populations and increasing numbers of vehicles have caused a parallel increase in demand for parking areas. Metropolitan cities, especially, are suffering from lack of parking areas. These areas are one of the significant parts of the modern urban transportation system and have significant effects on decreasing traffic loads. Finding the best location for parking areas has become a major challenge for both urban transportation planners and policy makers. This study aims to design an exemplary geographic analytics method for determining parking demand and locating parking areas using the Pendik district of Istanbul (Turkey) as a case study. Parking demand and supply analysis was performed using map algebra in the Geographic Information Systems (GIS) environment. Parking demand was calculated by integrating multiple selected parameters simultaneously, including housing demand, workplace demand, fixed demand, and dynamic demand. After calculating and evaluating parking demand, the location-allocation methods of network analysis were implemented to allocate parking locations based on parking demand and supply. In conclusion, this approach gives a novel data-processing method that determines parking facility locations more accurately to support transportation planning and support sustainable urbanization.