Quantifying the effect of waterways and green areas on the surface temperature
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Tipo de documento: | Artigo |
Idioma: | eng por |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469 |
Resumo: | The cooling effects of urban parks and green areas, which form the “Park Cool Island” (PCI) can help decrease the surface temperature and mitigate the effects of urban heat islands (UHI). Therefore, the objective of this research was to know the temporal variability of PCI intensity, as well as analyze the factors that determines it and propose an equation to predict the PCI intensity in Iporá, Goiás State, Brazil. To this purpose, the PCI intensity values were obtained using the Landsat-8 satellite (band 10), and then correlated with the NDVI and the LAI, in which proposes equations through multiple linear regression to estimate the PCI intensity. The results indicated that: 1) the greater the distance of the natural area, greater the surface temperature; 2) there is a great seasonality in PCI, in which the intensity of PCI is much higher in the spring (or close to it); 3) the relationship between NDVI and LAI variables, showed good coefficients of determination; 4) the equations for the buffer of 200 and 500 m, had low RMSE with high coefficients of determination (r2 = 0.924 and r2 = 0.957 respectively). |
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Acta scientiarum. Technology (Online) |
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Quantifying the effect of waterways and green areas on the surface temperatureurban heat island (UHI)Park Cool Island (PCI)surface temperature.The cooling effects of urban parks and green areas, which form the “Park Cool Island” (PCI) can help decrease the surface temperature and mitigate the effects of urban heat islands (UHI). Therefore, the objective of this research was to know the temporal variability of PCI intensity, as well as analyze the factors that determines it and propose an equation to predict the PCI intensity in Iporá, Goiás State, Brazil. To this purpose, the PCI intensity values were obtained using the Landsat-8 satellite (band 10), and then correlated with the NDVI and the LAI, in which proposes equations through multiple linear regression to estimate the PCI intensity. The results indicated that: 1) the greater the distance of the natural area, greater the surface temperature; 2) there is a great seasonality in PCI, in which the intensity of PCI is much higher in the spring (or close to it); 3) the relationship between NDVI and LAI variables, showed good coefficients of determination; 4) the equations for the buffer of 200 and 500 m, had low RMSE with high coefficients of determination (r2 = 0.924 and r2 = 0.957 respectively). Universidade Estadual De Maringá2017-02-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3046910.4025/actascitechnol.v39i1.30469Acta Scientiarum. Technology; Vol 39 No 1 (2017); 89-96Acta Scientiarum. Technology; v. 39 n. 1 (2017); 89-961806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMengporhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469/751375144469Copyright (c) 2017 Acta Scientiarum. Technologyinfo:eu-repo/semantics/openAccessAlves, Elis Dener Lima2017-02-24T10:36:53Zoai:periodicos.uem.br/ojs:article/30469Revistahttp://periodicos.uem.br/ojs/index.php/ActaSciTechnolPUBhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2017-02-24T10:36:53Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Quantifying the effect of waterways and green areas on the surface temperature |
title |
Quantifying the effect of waterways and green areas on the surface temperature |
spellingShingle |
Quantifying the effect of waterways and green areas on the surface temperature Alves, Elis Dener Lima urban heat island (UHI) Park Cool Island (PCI) surface temperature. |
title_short |
Quantifying the effect of waterways and green areas on the surface temperature |
title_full |
Quantifying the effect of waterways and green areas on the surface temperature |
title_fullStr |
Quantifying the effect of waterways and green areas on the surface temperature |
title_full_unstemmed |
Quantifying the effect of waterways and green areas on the surface temperature |
title_sort |
Quantifying the effect of waterways and green areas on the surface temperature |
author |
Alves, Elis Dener Lima |
author_facet |
Alves, Elis Dener Lima |
author_role |
author |
dc.contributor.author.fl_str_mv |
Alves, Elis Dener Lima |
dc.subject.por.fl_str_mv |
urban heat island (UHI) Park Cool Island (PCI) surface temperature. |
topic |
urban heat island (UHI) Park Cool Island (PCI) surface temperature. |
description |
The cooling effects of urban parks and green areas, which form the “Park Cool Island” (PCI) can help decrease the surface temperature and mitigate the effects of urban heat islands (UHI). Therefore, the objective of this research was to know the temporal variability of PCI intensity, as well as analyze the factors that determines it and propose an equation to predict the PCI intensity in Iporá, Goiás State, Brazil. To this purpose, the PCI intensity values were obtained using the Landsat-8 satellite (band 10), and then correlated with the NDVI and the LAI, in which proposes equations through multiple linear regression to estimate the PCI intensity. The results indicated that: 1) the greater the distance of the natural area, greater the surface temperature; 2) there is a great seasonality in PCI, in which the intensity of PCI is much higher in the spring (or close to it); 3) the relationship between NDVI and LAI variables, showed good coefficients of determination; 4) the equations for the buffer of 200 and 500 m, had low RMSE with high coefficients of determination (r2 = 0.924 and r2 = 0.957 respectively). |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-02-24 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469 10.4025/actascitechnol.v39i1.30469 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469 |
identifier_str_mv |
10.4025/actascitechnol.v39i1.30469 |
dc.language.iso.fl_str_mv |
eng por |
language |
eng por |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469/pdf http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/30469/751375144469 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2017 Acta Scientiarum. Technology info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2017 Acta Scientiarum. Technology |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 39 No 1 (2017); 89-96 Acta Scientiarum. Technology; v. 39 n. 1 (2017); 89-96 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1750315283778633728 |