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Campo DC | Valor | Idioma |
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dc.contributor.author | Lopes, Simone | - |
dc.contributor.author | Brondino, Nair Cristina Margarido | - |
dc.contributor.author | Silva, Antônio Nélson Rodrigues da | - |
dc.date.accessioned | 2016-03-02T13:03:36Z | - |
dc.date.accessioned | 2016-10-25T21:33:07Z | - |
dc.date.available | 2016-03-02T13:03:36Z | - |
dc.date.available | 2016-10-25T21:33:07Z | - |
dc.date.issued | 2014 | - |
dc.identifier | http://dx.doi.org/10.3390/ijgi3020565 | - |
dc.identifier.citation | ISPRS International Journal of Geo-Information, v. 3, n. 2, p. 565-583, 2014. | - |
dc.identifier.issn | 2220-9964 | - |
dc.identifier.uri | http://hdl.handle.net/11449/135629 | - |
dc.identifier.uri | http://acervodigital.unesp.br/handle/11449/135629 | - |
dc.description.abstract | Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial autocorrelation, spatial dependence patterns should be incorporated in the models, since that dependence may affect the predictive power of these models. The results obtained with the spatial regression models were also compared with the results of a multiple linear regression model that is typically used in trips generation estimations. The findings support the hypothesis that the inclusion of spatial effects in regression models is important, since the best results were obtained with alternative models (spatial regression models or the ones with spatial variables included). This was observed in a case study carried out in the city of Porto Alegre, in the state of Rio Grande do Sul, Brazil, in the stages of specification and calibration of the models, with two distinct datasets. | en |
dc.format.extent | 565-583 | - |
dc.language.iso | eng | - |
dc.source | Currículo Lattes | - |
dc.subject | Transport planning | en |
dc.subject | Transport demand | en |
dc.subject | Spatial dependence | en |
dc.subject | Spatial regression | en |
dc.title | GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast | en |
dc.type | outro | - |
dc.contributor.institution | Universidade Estadual Paulista (UNESP) | - |
dc.contributor.institution | Universidade de São Paulo (USP) | - |
dc.description.affiliation | Universidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Matemática, Faculdade de Ciências de Bauru, Bauru, Av. Eng. Luiz E. Carrijo Coube S/N, Vargem Limpa, CEP 17033-360, SP, Brasil | - |
dc.description.affiliation | Department of Transportation Engineering, São Carlos School of Engineering, University of São Paulo, Av. Trabalhador São-carlense 400, 13566-590 São Carlos, Brazil | - |
dc.description.affiliationUnesp | Universidade Estadual Paulista Júlio de Mesquita Filho, Departamento de Matemática, Faculdade de Ciências de Bauru, Bauru, Av. Eng. Luiz E. Carrijo Coube S/N, Vargem Limpa, CEP 17033-360, SP, Brasil | - |
dc.identifier.doi | 10.3390/ijgi3020565 | - |
dc.rights.accessRights | Acesso restrito | - |
dc.relation.ispartof | ISPRS International Journal of Geo-Information | - |
dc.identifier.lattes | 5603234988255497 | - |
Aparece nas coleções: | Artigos, TCCs, Teses e Dissertações da Unesp |
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