Identifying the Urban Development Pattern of Subway Cities Using Predictive Analysis

Abstract

Starting from the hypothesis that there are structural differences in urban development between cities that have implemented underground transport and those that have not, the paper aims to provide a predictive analysis model to identify cities that show the pattern for the development of the subway network. In order to identify the predictive analysis model capable of classifying urban settlements, the predictive analysis part consisted of two stages. In the first stage, a Random Forest classification model will be estimated on a sample of the 27 capitals of the European Member States. Subsequently, based on this model, 9 cities in Romania will be classified from the perspective of the existence of the urban development pattern for the development of underground public transport. In order for the classification error of the predictive model to be as low as possible, variables from all areas specific to urban development (economic development, population density, circular economy, green city, digitalization, urban mobility) were used. The element of originality of the paper consists in calculating variables on the area of urban mobility, urban infrastructure and circular economy, using GIS coordinates. Thus, in addition to official international data sources, variables calculated by using geospatial technology (average distances, densities of green spaces, etc.) were included in this research. The main results of the research show that there are cities in Romania that present the same pattern of development similar to the capitals of the Member States of the European Union that have implemented underground public transport. Therefore, it can be said that for these cities it is necessary to implement this type of transport, the depreciation of the investment representing an easy process, which can be achieved in a medium or short term.