TDX
author
Santa Guzmán, Luis Fernando
authoremail
fernando.santa@isegi.unl.pt
authoremailshow
false
director
Henriques, Roberto
codirector
Torres-Sospedra, Joaquín
codirector
Pebesma, Edzer
2019-04-17T10:00:21Z
2019-04-17T10:00:21Z
2018-11-30
http://hdl.handle.net/10803/666680
http://dx.doi.org/10.6035/14123.2018.738830
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.
eng
Urban dynamics
Urban studies
Social media
A statistical approach for studying urban human dynamics
info:eu-repo/semantics/doctoralThesis
URL
http://www.tdx.cat/bitstream/10803/666680/1/2018_Tesis_Santa%20Guzman_Luis%20Fernando.pdf
File
MD5
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application/pdf
2018_Tesis_Santa Guzman_Luis Fernando.pdf