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1. Identity statement
Reference TypeJournal Article
Siteplutao.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/3UGDGKK
Repositorysid.inpe.br/plutao/2019/12.03.17.37.20   (restricted access)
Last Update2019:12.05.19.15.14 (UTC) lattes
Metadata Repositorysid.inpe.br/plutao/2019/12.03.17.37.21
Metadata Last Update2020:01.08.15.04.05 (UTC) administrator
DOI10.1007/s41109-019-0211-7
ISSN2364-8228
Labellattes: 0654596992211296 7 LimaSantosCaSeCoMaQuMo:2019:HoUrMo
Citation KeySantosCaSeCoMaQuMo:2019:HoUrMo
TitleHow do urban mobility (geo)graph's topological properties fill a map?
Year2019
Access Date2024, Mar. 28
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size2075 KiB
2. Context
Author1 Santos, Leonardo Bacelar Lima
2 Carvalho, Luiz Max
3 Seron, Wilson
4 Coelho, Flávio C.
5 Macau, Elbert Einstein Nehrer
6 Quiles, Marcos G.
7 Monteiro, Antônio Miguel Vieira
Resume Identifier1
2
3
4
5 8JMKD3MGP5W/3C9JGUT
6
7 8JMKD3MGP5W/3C9JGJN
Group1
2
3
4
5 LABAC-COCTE-INPE-MCTIC-GOV-BR
6
7 DIDPI-CGOBT-INPE-MCTIC-GOV-BR
Affiliation1 Centro Nacional de Monitoramento e Alertas de Desastres Naturais (CEMADEN)
2 Fundação Oswaldo Cruz (FIOCRUZ)
3 Universidade Federal de São Paulo (UNIFESP)
4 Fundação Getúlio Vargas (FGV)
5 Instituto Nacional de Pesquisas Espaciais (INPE)
6 Universidade Federal de São Paulo (UNIFESP)
7 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 20santoslbl@gmail.com
2
3
4
5 elbert.macau@inpe.br
6
7 miguel.monteiro@inpe.br
JournalApplied Network Science
Volume4
Number1
Pages1-10
History (UTC)2019-12-03 17:37:21 :: lattes -> administrator ::
2019-12-04 22:15:37 :: administrator -> lattes :: 2019
2019-12-06 19:49:44 :: lattes -> administrator :: 2019
2020-01-08 15:04:05 :: administrator -> simone :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsComplex networks
Geographical information systems (GIS)
(geo)graphs
Traffic-topology correlation
AbstractUrban 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.
AreaCOMP
Arrangement 1urlib.net > BDMCI > Fonds > Produção anterior à 2021 > DIDPI > How do urban...
Arrangement 2urlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > How do urban...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
Languageen
Target Filesantos_how.pdf
User Grouplattes
Reader Groupadministrator
lattes
Visibilityshown
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3EQCCU5
8JMKD3MGPCW/3ESGTTP
DisseminationPORTALCAPES; SCOPUS.
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
6. Notes
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7. Description control
e-Mail (login)simone
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