Modelling and mapping the urban thermal environment
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/227784 |
Resumo: | In order to develop a methodology and tools that could help on thermal urban planning, this paper proposes a modelling of urban thermal environment based on the application of Artificial Neural Networks (ANN) and GIS tools. The study area was a residential neighbourhood in a medium sized city, where urban air temperatures at the pedestrian level could be collected. At the same time, rural temperatures that were registered and made available by the city meteorological station site, have been obtained. Urban features of these points were determined by the following characteristics: street's orientation, building volumes, proportion of green areas, proportion of built and non-built areas and sky view factors (SVF). Based on the differences of urban and rural air temperatures registered at 7 p.m., a model applying Artificial Neural Networks was developed. The results of that model allowed the simulation of values for the entire area and the creation of thermal maps in a GIS environment. |
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Modelling and mapping the urban thermal environmentArtificial neural networks (ANR)Geographic information systems (GIS)Sky view factors (SVF)Urban heat island (UHI)In order to develop a methodology and tools that could help on thermal urban planning, this paper proposes a modelling of urban thermal environment based on the application of Artificial Neural Networks (ANN) and GIS tools. The study area was a residential neighbourhood in a medium sized city, where urban air temperatures at the pedestrian level could be collected. At the same time, rural temperatures that were registered and made available by the city meteorological station site, have been obtained. Urban features of these points were determined by the following characteristics: street's orientation, building volumes, proportion of green areas, proportion of built and non-built areas and sky view factors (SVF). Based on the differences of urban and rural air temperatures registered at 7 p.m., a model applying Artificial Neural Networks was developed. The results of that model allowed the simulation of values for the entire area and the creation of thermal maps in a GIS environment.Department of Architecture, Urbanism and Landscape Architecture, Faculty of Architecture, Arts and Communication, São Paulo State University, Av. Luis Edmundo C. Coube, 14-01, Bauru 17033-360Department of Architecture, Urbanism and Landscape Architecture, Faculty of Architecture, Arts and Communication, São Paulo State University, Av. Luis Edmundo C. Coube, 14-01, Bauru 17033-360Universidade Estadual Paulista (UNESP)Souza, Léa Cristina Lucas de [UNESP]2022-04-29T07:17:22Z2022-04-29T07:17:22Z2007-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject1-9Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007, p. 1-9.http://hdl.handle.net/11449/2277842-s2.0-84903608757Scopusreponame: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/openAccess2024-04-16T19:24:29Zoai:repositorio.unesp.br:11449/227784Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-16T19:24:29Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Modelling and mapping the urban thermal environment |
title |
Modelling and mapping the urban thermal environment |
spellingShingle |
Modelling and mapping the urban thermal environment Souza, Léa Cristina Lucas de [UNESP] Artificial neural networks (ANR) Geographic information systems (GIS) Sky view factors (SVF) Urban heat island (UHI) |
title_short |
Modelling and mapping the urban thermal environment |
title_full |
Modelling and mapping the urban thermal environment |
title_fullStr |
Modelling and mapping the urban thermal environment |
title_full_unstemmed |
Modelling and mapping the urban thermal environment |
title_sort |
Modelling and mapping the urban thermal environment |
author |
Souza, Léa Cristina Lucas de [UNESP] |
author_facet |
Souza, Léa Cristina Lucas de [UNESP] |
author_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Souza, Léa Cristina Lucas de [UNESP] |
dc.subject.por.fl_str_mv |
Artificial neural networks (ANR) Geographic information systems (GIS) Sky view factors (SVF) Urban heat island (UHI) |
topic |
Artificial neural networks (ANR) Geographic information systems (GIS) Sky view factors (SVF) Urban heat island (UHI) |
description |
In order to develop a methodology and tools that could help on thermal urban planning, this paper proposes a modelling of urban thermal environment based on the application of Artificial Neural Networks (ANN) and GIS tools. The study area was a residential neighbourhood in a medium sized city, where urban air temperatures at the pedestrian level could be collected. At the same time, rural temperatures that were registered and made available by the city meteorological station site, have been obtained. Urban features of these points were determined by the following characteristics: street's orientation, building volumes, proportion of green areas, proportion of built and non-built areas and sky view factors (SVF). Based on the differences of urban and rural air temperatures registered at 7 p.m., a model applying Artificial Neural Networks was developed. The results of that model allowed the simulation of values for the entire area and the creation of thermal maps in a GIS environment. |
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. 1-9. http://hdl.handle.net/11449/227784 2-s2.0-84903608757 |
identifier_str_mv |
Proceedings of 10th International Conference on Computers in Urban Planning and Urban Management, CUPUM 2007, p. 1-9. 2-s2.0-84903608757 |
url |
http://hdl.handle.net/11449/227784 |
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 |
1-9 |
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_ |
1803046672346906624 |