@Article{SantosCaSeCoMaQuMo:2019:HoUrMo,
author = "Santos, Leonardo Bacelar Lima and Carvalho, Luiz Max and Seron,
Wilson and Coelho, Fl{\'a}vio C. and Macau, Elbert Einstein
Nehrer and Quiles, Marcos G. and Monteiro, Ant{\^o}nio Miguel
Vieira",
affiliation = "{Centro Nacional de Monitoramento e Alertas de Desastres Naturais
(CEMADEN)} and {Funda{\c{c}}{\~a}o Oswaldo Cruz (FIOCRUZ)} and
{Universidade Federal de S{\~a}o Paulo (UNIFESP)} and
{Funda{\c{c}}{\~a}o Get{\'u}lio Vargas (FGV)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal
de S{\~a}o Paulo (UNIFESP)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)}",
title = "How do urban mobility (geo)graph's topological properties fill a
map?",
journal = "Applied Network Science",
year = "2019",
volume = "4",
number = "1",
pages = "1--10",
keywords = "Complex networks, Geographical information systems (GIS),
(geo)graphs, Traffic-topology correlation.",
abstract = "Urban mobility data are important to areas ranging from traffic
engineering to the analysis of outbreaks and disasters. In this
paper, we study mobility data from a major Brazilian city from a
geographical viewpoint using a Complex Network approach. The case
study is based on intra-urban mobility data from the Metropolitan
area of Rio de Janeiro (Brazil), presenting more than 480 spatial
network nodes. While for the mobility flow data a log-normal
distribution outperformed the power law, we also found moderate
evidence for scale-free and small word effects in the flow
networks degree distribution. We employ a novel open-source GIS
tool to display (geo)graphs topological properties in maps and
observe a strong traffic-topology association and also a fine
adjustment for hubs location for different flow threshold
networks. In the central commercial area for lower thresholds and
in high population residential areas for higher thresholds. This
set of results, including statistical, topological and
geographical analysis may represent an important tool for
policymakers and stakeholders in the urban planning area,
especially by the identification of zones with few but strong
links in a real data-driven mobility networ.",
doi = "10.1007/s41109-019-0211-7",
url = "http://dx.doi.org/10.1007/s41109-019-0211-7",
issn = "2364-8228",
label = "lattes: 0654596992211296 7 LimaSantosCaSeCoMaQuMo:2019:HoUrMo",
language = "en",
targetfile = "santos_how.pdf",
urlaccessdate = "2024, Apr. 25"
}