@InProceedings{SantosSantQuilMaca:2017:TiVaGe,
               author = "Santos, J{\'e}ssica Domingues and Santos, Leonardo Bacelar Lima 
                         and Quiles, Marcos Gon{\c{c}}alves and Macau, Elbert Einstein 
                         Nehrer",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Centro 
                         Nacional de Monitoramento e Alerta de Desastre Naturais (CEMADEN)} 
                         and {Universidade Federal de S{\~a}o Paulo (UNIFESP)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Urban mobility in a typical day: time varying (geo)graphs",
            booktitle = "Anais...",
                 year = "2017",
         organization = "Workshop dos Cursos de Computa{\c{c}}{\~a}o Aplicada do INPE, 
                         17. (WORCAP)",
             keywords = "Complex Networks, (Geo)Graphs, Time Varying Graphs.",
             abstract = "In this work we create and analyse a set of urban mobility 
                         networks, each one corresponding to a consecutive timestamp in a 
                         same city. It was used, as case study, actual data from Sao Jose 
                         dos Campos-Brazil. This data consist of an Origin-Destination 
                         survey: a list with place (traffic zone) and time of both leave 
                         and arrival of each travel. An Origin-Destination graph was 
                         generated based on a 3-dimension matrix representation, in which 
                         each node represents a traffic zone and the edges weight is the 
                         flow of people between these nodes. The igraph library, in 
                         language C, was applied to calculate the topological properties 
                         (degree, clustering, diameter). The Geographical Information 
                         System QuatumGIS was used to spatial visualization of both nodes 
                         and edges and their topological properties, using the framework of 
                         (geo)graphs. Our results show, for the 24-hours network, that the 
                         greatest diameter occurs at 4 a.m, and that between 6 a.m and 8 
                         p.m the clustering is always greater than 0.62.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP",
      conference-year = "20-22 nov. 2017",
             language = "en",
           targetfile = "Santos_urban.pdf",
        urlaccessdate = "2024, May 01"
}