A statistical approach for studying urban human dynamics

Research output: ThesisDoctoral Thesis


This doctoral dissertation proposed several statistical approaches to analyse urban dynamics with aiming to provide tools for decision making processes and urban studies. It assumed that human activity and human mobility compose urban dynamics. Initially, it studied geolocated social media data and considered them as a proxy for where and when people carry out what it is defined as the human activity. It employed techniques associated with generalised linear models, functional data analysis, hierarchical clustering, and epidemic data, to explain the spatio-temporal distribution of the places where people interact with their social networks. Afterwards, to understand the mobility in urban environments, data coming from an underground railway system were used. The information was considered repeated daily measurements to capture the regularity of human behaviour. By implementing methods from functional principal components data analysis and hierarchical clustering, it was possible to describe the system and identify human mobility patterns.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • NOVA Information Management School (NOVA IMS)
  • Universidad Jaume I
  • University of Münster
  • Henriques, Roberto, Supervisor
  • Torres-Sospedra, Joaquín, Supervisor, External person
  • Pebesma, E., Supervisor, External person
Award date30 Nov 2018
Publication statusPublished - 30 Nov 2018


  • Urban dynamics
  • Urban studies
  • Social media


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