Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting

Detalhes bibliográficos
Autor(a) principal: Gomes, Viviani Antunes
Data de Publicação: 2016
Outros Autores: Pitombo, Cira Souza, Rocha, Samille Santos, Salgueiro, Ana Rita Gonçalves Neves Lopes
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
Texto Completo: http://www.repositorio.ufc.br/handle/riufc/64354
Resumo: This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at São Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.
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spelling Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecastingGeostatisticsKrigingTravel Mode ChoiceSpatial EstimationThis paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at São Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.Open Journal of Statistics2022-03-09T19:00:04Z2022-03-09T19:00:04Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfGOMES, Viviani Antunes et al. Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting. Open Journal of Statistics, [s.l.], v. 6, n. 3, p. 514-527, 2016.2161-7198http://www.repositorio.ufc.br/handle/riufc/64354Gomes, Viviani AntunesPitombo, Cira SouzaRocha, Samille SantosSalgueiro, Ana Rita Gonçalves Neves Lopesinfo:eu-repo/semantics/openAccessengreponame:Repositório Institucional da Universidade Federal do Ceará (UFC)instname:Universidade Federal do Ceará (UFC)instacron:UFC2023-10-10T17:23:37Zoai:repositorio.ufc.br:riufc/64354Repositório InstitucionalPUBhttp://www.repositorio.ufc.br/ri-oai/requestbu@ufc.br || repositorio@ufc.bropendoar:2024-09-11T18:16:03.051215Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)false
dc.title.none.fl_str_mv Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
title Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
spellingShingle Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
Gomes, Viviani Antunes
Geostatistics
Kriging
Travel Mode Choice
Spatial Estimation
title_short Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
title_full Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
title_fullStr Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
title_full_unstemmed Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
title_sort Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting
author Gomes, Viviani Antunes
author_facet Gomes, Viviani Antunes
Pitombo, Cira Souza
Rocha, Samille Santos
Salgueiro, Ana Rita Gonçalves Neves Lopes
author_role author
author2 Pitombo, Cira Souza
Rocha, Samille Santos
Salgueiro, Ana Rita Gonçalves Neves Lopes
author2_role author
author
author
dc.contributor.author.fl_str_mv Gomes, Viviani Antunes
Pitombo, Cira Souza
Rocha, Samille Santos
Salgueiro, Ana Rita Gonçalves Neves Lopes
dc.subject.por.fl_str_mv Geostatistics
Kriging
Travel Mode Choice
Spatial Estimation
topic Geostatistics
Kriging
Travel Mode Choice
Spatial Estimation
description This paper aims to compare the results of two techniques of Kriging (Ordinary Kriging and Indicator Kriging) that are applied to estimate the Private Motorized (PM) travel mode use (car or motorcycle) in several geographical coordinates of non-sampled values of the concerning variable. The data used was from the Origin/Destination and Public Transportation Opinion Survey, carried out in 2007/2008 at São Carlos (SP, Brazil). The techniques were applied in the region with 110 sample points (households). Initially, Decision Tree was applied to estimate the probability of mode choice in surveyed households, thus determining the numeric variable to be used in Ordinary Kriging. For application of Indicator Kriging it was used the variable “main travel mode” in a discrete manner, where “1” represented the use of PM travel mode and “0” characterized others travel modes. The results obtained by the two spatial estimation techniques were similar (Kriging maps and cross-validation procedure). However, the Indicator Kriging (KI) obtained the highest number of hit rates. In addition, with the KI it was possible to use the variable in its original form, avoiding error propagation. Finally, it was concluded that spatial statistics was thriving in travel demand forecasting issues, giving rise, for the both Kriging methods, to a travel mode choice surface on a confirmatory way.
publishDate 2016
dc.date.none.fl_str_mv 2016
2022-03-09T19:00:04Z
2022-03-09T19:00:04Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv GOMES, Viviani Antunes et al. Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting. Open Journal of Statistics, [s.l.], v. 6, n. 3, p. 514-527, 2016.
2161-7198
http://www.repositorio.ufc.br/handle/riufc/64354
identifier_str_mv GOMES, Viviani Antunes et al. Kriging geostatistical methods for travel mode choice: a spatial data analysis to travel demand forecasting. Open Journal of Statistics, [s.l.], v. 6, n. 3, p. 514-527, 2016.
2161-7198
url http://www.repositorio.ufc.br/handle/riufc/64354
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Open Journal of Statistics
publisher.none.fl_str_mv Open Journal of Statistics
dc.source.none.fl_str_mv reponame:Repositório Institucional da Universidade Federal do Ceará (UFC)
instname:Universidade Federal do Ceará (UFC)
instacron:UFC
instname_str Universidade Federal do Ceará (UFC)
instacron_str UFC
institution UFC
reponame_str Repositório Institucional da Universidade Federal do Ceará (UFC)
collection Repositório Institucional da Universidade Federal do Ceará (UFC)
repository.name.fl_str_mv Repositório Institucional da Universidade Federal do Ceará (UFC) - Universidade Federal do Ceará (UFC)
repository.mail.fl_str_mv bu@ufc.br || repositorio@ufc.br
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