ABSTRACT
There is a general belief that empirical urban analyses can benefit from processing ICT (big) data with the newly developed methods inspired by complex theory, social physics, etc. This chapter compares different geographical partitions of a city (Brussels), respectively based on community detection in phone data, on partitions based on built-up footprints and on the more traditional clustering of socio-economic attributes. The objective is to identify to what extent new ways of measuring urban realities modify more “classical” results. Our results not only confirm the complexity of the Brussels’ urban city centre, reflecting the superposition of several urban models, but also remind the need for controlling the methods and their objectives and the exact definition of the data. ICT data open new opportunities for spatial analyses, but at the condition that users clearly know what and how they measure, for what purpose and what the limitations are. The impact in further transport analysis and urban planning can be considerable.
