Problem Statement

The study of the urban is highly relevant not only in the social sciences, but also in mobility studies. Movement patterns of the urban population raise the fundamental question of how and why there is a connection between settlement structures and travel behavior. But defining what is urban, especially on an international level, is a challenging task. There is no uniform methodology, let alone data availability.

Objective

The development of the "Smart Urban Index" (SUI) on the basis of different data sources as well as the subsequent application of the SUI provide a uniform and comparative spatial attribution. The SUI assigns areas based on zip codes to spatial types (e.g. superurban, urban, suburban, rural). Using standardized SUI classifications, it is straightforward to make standalone comparisons of levels of urbanity both at national and international level or to perform analysis for specific studies such as mobility or market potential analysis (car usage, offering of mobility services etc.).

Methods

Using advanced GIS techniques and ML algorithms, freely available open data are enriched to classify urbanity with the developed SUI. As the SUI is a highly flexible urbanity measure, we are able to assign areas on zip-code level to spatial types for various European countries as well as the USA and China.