Exploratory and confirmatory spatial data analysis tools in transport demand modeling

Detalhes bibliográficos
Autor(a) principal: Lopes, Simone Becker
Data de Publicação: 2007
Outros Autores: Brondino, Nair Cristina Margarido [UNESP], Rodrigues Da Silva, Antônio Nélson
Tipo de documento: Artigo de conferência
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://hdl.handle.net/11449/227783
Resumo: The main goal of this paper is to discuss a method for the definition of spatial dependence indicators and their inclusion as variables into transportation demand models. The method is based on ESDA (Exploratory Spatial Data Analyses) and CSDA (Confirmatory Spatial Data Analyses) tools, which have been used in two ways, both in a GIS (Geographic Information Systems) environment: i) to produce indicators of spatial dependence; ii) to evaluate the models estimations. The proposed method is applied in a case study in the city of Porto Alegre, State of Rio Grande do Sul, Brazil, based on origin-destination data obtained through household surveys. The results of this work show that ESDA and CSDA tools are very important for the definition of spatial dependency indicators, identification and selection of the most significant spatial variables, specification and evaluation of demand forecast models and evaluation of the results.
id UNSP_6347ba99aa376141d8599e30258b5ada
oai_identifier_str oai:repositorio.unesp.br:11449/227783
network_acronym_str UNSP
network_name_str Repositório Institucional da UNESP
repository_id_str 2946
spelling Exploratory and confirmatory spatial data analysis tools in transport demand modelingCSDAESDAGISSpatial autocorrelationTransportation demandThe main goal of this paper is to discuss a method for the definition of spatial dependence indicators and their inclusion as variables into transportation demand models. The method is based on ESDA (Exploratory Spatial Data Analyses) and CSDA (Confirmatory Spatial Data Analyses) tools, which have been used in two ways, both in a GIS (Geographic Information Systems) environment: i) to produce indicators of spatial dependence; ii) to evaluate the models estimations. The proposed method is applied in a case study in the city of Porto Alegre, State of Rio Grande do Sul, Brazil, based on origin-destination data obtained through household surveys. The results of this work show that ESDA and CSDA tools are very important for the definition of spatial dependency indicators, identification and selection of the most significant spatial variables, specification and evaluation of demand forecast models and evaluation of the results.Department of Transportation, School of Engineering of São Carlos, University of São Paulo, Av. Trabalhador São-carlense, 400, São Carlos 13566-590Department of Mathematics, Faculty of Science, São Paulo State University, Av. Luis Edmundo C. Coube, 14-01, Bauru 17033-360Department of Mathematics, Faculty of Science, São Paulo State University, Av. Luis Edmundo C. Coube, 14-01, Bauru 17033-360Universidade de São Paulo (USP)Universidade Estadual Paulista (UNESP)Lopes, Simone BeckerBrondino, Nair Cristina Margarido [UNESP]Rodrigues Da Silva, Antônio Nélson2022-04-29T07:17:22Z2022-04-29T07:17:22Z2007-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1-15Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007, p. 1-15.http://hdl.handle.net/11449/2277832-s2.0-84903587120Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007info:eu-repo/semantics/openAccess2024-04-29T14:59:56Zoai:repositorio.unesp.br:11449/227783Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T19:29:16.464785Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Exploratory and confirmatory spatial data analysis tools in transport demand modeling
title Exploratory and confirmatory spatial data analysis tools in transport demand modeling
spellingShingle Exploratory and confirmatory spatial data analysis tools in transport demand modeling
Lopes, Simone Becker
CSDA
ESDA
GIS
Spatial autocorrelation
Transportation demand
title_short Exploratory and confirmatory spatial data analysis tools in transport demand modeling
title_full Exploratory and confirmatory spatial data analysis tools in transport demand modeling
title_fullStr Exploratory and confirmatory spatial data analysis tools in transport demand modeling
title_full_unstemmed Exploratory and confirmatory spatial data analysis tools in transport demand modeling
title_sort Exploratory and confirmatory spatial data analysis tools in transport demand modeling
author Lopes, Simone Becker
author_facet Lopes, Simone Becker
Brondino, Nair Cristina Margarido [UNESP]
Rodrigues Da Silva, Antônio Nélson
author_role author
author2 Brondino, Nair Cristina Margarido [UNESP]
Rodrigues Da Silva, Antônio Nélson
author2_role author
author
dc.contributor.none.fl_str_mv Universidade de São Paulo (USP)
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Lopes, Simone Becker
Brondino, Nair Cristina Margarido [UNESP]
Rodrigues Da Silva, Antônio Nélson
dc.subject.por.fl_str_mv CSDA
ESDA
GIS
Spatial autocorrelation
Transportation demand
topic CSDA
ESDA
GIS
Spatial autocorrelation
Transportation demand
description The main goal of this paper is to discuss a method for the definition of spatial dependence indicators and their inclusion as variables into transportation demand models. The method is based on ESDA (Exploratory Spatial Data Analyses) and CSDA (Confirmatory Spatial Data Analyses) tools, which have been used in two ways, both in a GIS (Geographic Information Systems) environment: i) to produce indicators of spatial dependence; ii) to evaluate the models estimations. The proposed method is applied in a case study in the city of Porto Alegre, State of Rio Grande do Sul, Brazil, based on origin-destination data obtained through household surveys. The results of this work show that ESDA and CSDA tools are very important for the definition of spatial dependency indicators, identification and selection of the most significant spatial variables, specification and evaluation of demand forecast models and evaluation of the results.
publishDate 2007
dc.date.none.fl_str_mv 2007-01-01
2022-04-29T07:17:22Z
2022-04-29T07:17:22Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/conferenceObject
format conferenceObject
status_str publishedVersion
dc.identifier.uri.fl_str_mv Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007, p. 1-15.
http://hdl.handle.net/11449/227783
2-s2.0-84903587120
identifier_str_mv Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007, p. 1-15.
2-s2.0-84903587120
url http://hdl.handle.net/11449/227783
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 1-15
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
_version_ 1808129076558299136

Registros relacionados