Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil

Detalhes bibliográficos
Autor(a) principal: Teixeira, Danielle Cardozo Frasca [UNESP]
Data de Publicação: 2022
Outros Autores: Amorim, Margarete Cristiane de Costa Trindade [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/cli10040056
http://hdl.handle.net/11449/239918
Resumo: Several studies demonstrate the potential of models for the representation of phenomena such as urban heat islands. This article aimed to analyze atmospheric heat islands (UHIucl) by inte-grating primary air temperature data with spatial information such as land use and relief from a multicriteria model based on multiple linear regression. Furthermore, we compared the measured and estimated air temperature at 11 p.m. with the surface temperature at 10:51 p.m. (local time). These temperatures were obtained through the thermal band of the Landsat 8 satellite considering extraction points of interest in Presidente Prudente city, Brazil. The multicriteria model showed re-liability in UHIucl spatialization, reaching the confidence interval (p‐value ≤ 0.05). The model proves that urban surface materials are the main energy sources modulating heat transfer to the atmos-phere, while vegetation has a temperature‐reducing effect. Precise mappings such as the one pro-posed here are relevant for the formulation of measures that support decision‐making by public authorities. These mappings aim at urban planning that is resilient to the effects of urban climate and can be replicated in other realities.
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spelling Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazilland usemulticriteria modelingsurface heat islandurban canopy heat islandurban climatevegetationSeveral studies demonstrate the potential of models for the representation of phenomena such as urban heat islands. This article aimed to analyze atmospheric heat islands (UHIucl) by inte-grating primary air temperature data with spatial information such as land use and relief from a multicriteria model based on multiple linear regression. Furthermore, we compared the measured and estimated air temperature at 11 p.m. with the surface temperature at 10:51 p.m. (local time). These temperatures were obtained through the thermal band of the Landsat 8 satellite considering extraction points of interest in Presidente Prudente city, Brazil. The multicriteria model showed re-liability in UHIucl spatialization, reaching the confidence interval (p‐value ≤ 0.05). The model proves that urban surface materials are the main energy sources modulating heat transfer to the atmos-phere, while vegetation has a temperature‐reducing effect. Precise mappings such as the one pro-posed here are relevant for the formulation of measures that support decision‐making by public authorities. These mappings aim at urban planning that is resilient to the effects of urban climate and can be replicated in other realities.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)National Council for Scientific and Technological Development (CNPq) School of Technology and Sciences São Paulo State University (UNESP)Department of Geography School of Technology and Sciences São Paulo State University (UNESP)National Council for Scientific and Technological Development (CNPq) School of Technology and Sciences São Paulo State University (UNESP)Department of Geography School of Technology and Sciences São Paulo State University (UNESP)CNPq: 151597/2020‐0FAPESP: 2014/16350‐3FAPESP: 2015/50439‐4Universidade Estadual Paulista (UNESP)Teixeira, Danielle Cardozo Frasca [UNESP]Amorim, Margarete Cristiane de Costa Trindade [UNESP]2023-03-01T19:53:17Z2023-03-01T19:53:17Z2022-04-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.3390/cli10040056Climate, v. 10, n. 4, 2022.2225-1154http://hdl.handle.net/11449/23991810.3390/cli100400562-s2.0-85128592961Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengClimateinfo:eu-repo/semantics/openAccess2023-03-01T19:53:18Zoai:repositorio.unesp.br:11449/239918Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-03-01T19:53:18Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
title Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
spellingShingle Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
Teixeira, Danielle Cardozo Frasca [UNESP]
land use
multicriteria modeling
surface heat island
urban canopy heat island
urban climate
vegetation
title_short Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
title_full Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
title_fullStr Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
title_full_unstemmed Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
title_sort Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil
author Teixeira, Danielle Cardozo Frasca [UNESP]
author_facet Teixeira, Danielle Cardozo Frasca [UNESP]
Amorim, Margarete Cristiane de Costa Trindade [UNESP]
author_role author
author2 Amorim, Margarete Cristiane de Costa Trindade [UNESP]
author2_role author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv Teixeira, Danielle Cardozo Frasca [UNESP]
Amorim, Margarete Cristiane de Costa Trindade [UNESP]
dc.subject.por.fl_str_mv land use
multicriteria modeling
surface heat island
urban canopy heat island
urban climate
vegetation
topic land use
multicriteria modeling
surface heat island
urban canopy heat island
urban climate
vegetation
description Several studies demonstrate the potential of models for the representation of phenomena such as urban heat islands. This article aimed to analyze atmospheric heat islands (UHIucl) by inte-grating primary air temperature data with spatial information such as land use and relief from a multicriteria model based on multiple linear regression. Furthermore, we compared the measured and estimated air temperature at 11 p.m. with the surface temperature at 10:51 p.m. (local time). These temperatures were obtained through the thermal band of the Landsat 8 satellite considering extraction points of interest in Presidente Prudente city, Brazil. The multicriteria model showed re-liability in UHIucl spatialization, reaching the confidence interval (p‐value ≤ 0.05). The model proves that urban surface materials are the main energy sources modulating heat transfer to the atmos-phere, while vegetation has a temperature‐reducing effect. Precise mappings such as the one pro-posed here are relevant for the formulation of measures that support decision‐making by public authorities. These mappings aim at urban planning that is resilient to the effects of urban climate and can be replicated in other realities.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-01
2023-03-01T19:53:17Z
2023-03-01T19:53:17Z
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 http://dx.doi.org/10.3390/cli10040056
Climate, v. 10, n. 4, 2022.
2225-1154
http://hdl.handle.net/11449/239918
10.3390/cli10040056
2-s2.0-85128592961
url http://dx.doi.org/10.3390/cli10040056
http://hdl.handle.net/11449/239918
identifier_str_mv Climate, v. 10, n. 4, 2022.
2225-1154
10.3390/cli10040056
2-s2.0-85128592961
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Climate
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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
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