Regresar

Clustering model for the use of public space using data mining techniques

Abstract:

Informal occupations are urban situations, especially in Latin America, which, despite being within a framework of economic progress, both economic and social inequality are part of the urban landscape. Large cities in the region are its economic engine; therefore, they require adequate urban planning. This research presents a model of the use of public space for development in spatial terms of urban planning and design. The research presents a model applied as a case study to four places in Quito, and the data sample employs two data mining techniques, euclidean distance, and hierarchical clustering, that will allow making visible those informal spatial situations for real and optimal use and design of public space. Moreover, this research can serve as a reference in future studies related to urban design.