Socio-spatial Segregation Using Computational Algorithms: Case Study in Ambato, Ecuador

Abstract

Access to basic services, housing, and social security influence people’s quality of life. Within the cities, it is common for there to be specific sectors where the presence of those groups that have an abundance of resources predominates. The same occurs with the opposite group, motivated by various social and economic conditions. For this reason, this study explicitly considers the population of Ambato, Ecuador, to evaluate the existence of socio-spatial segregation. The data are obtained from the latest census base of 2010, which is publicly accessible by the Institute of Statistics and Census. The socioeconomic characterization of the population consists of the calculation of the condition index. A programming algorithm developed in the statistical software RStudio has been used to process the information. With the calculations obtained, we proceeded to generate geographic maps where the location of the different social groups could be seen. The results show that the values 0.77 and 0.90 predominate in the city’s west. Also, we identify that only the fourth quartile achieves well-being and an abundance of resources, while those in the first quartile are well below the average. The information describes a very low and positive spatial autocorrelation, where most of the population is concentrated in the city’s southwest. Thus, this proposal, which combines computational algorithms for the exposition of social and spatial characteristics of a specific population, is validated.