%0 Conference Proceedings
%4 sid.inpe.br/mtc-m21b/2023/08.29.11.45
%2 sid.inpe.br/mtc-m21b/2023/08.29.11.45.22
%T Urban mobility in a typical day: time varying (geo)graphs
%D 2017
%A Santos, Jéssica Domingues,
%A Santos, Leonardo Bacelar Lima,
%A Quiles, Marcos Gonçalves,
%A Macau, Elbert Einstein Nehrer,
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@affiliation Centro Nacional de Monitoramento e Alerta de Desastre Naturais (CEMADEN)
%@affiliation Universidade Federal de São Paulo (UNIFESP)
%@affiliation Instituto Nacional de Pesquisas Espaciais (INPE)
%@electronicmailaddress jessica.dominguess@gmail.com
%@electronicmailaddress
%@electronicmailaddress quiles@unifesp.br
%@electronicmailaddress elbert.macau@inpe.br
%B Workshop dos Cursos de Computação Aplicada do INPE, 17 (WORCAP)
%C São José dos Campos, SP
%8 20-22 nov. 2017
%S Anais
%K Complex Networks, (Geo)Graphs, Time Varying Graphs.
%X 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.
%@language en
%3 Santos_urban.pdf