Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Repositório Institucional da UFG |
dARK ID: | ark:/38995/00130000014z9 |
Texto Completo: | http://repositorio.bc.ufg.br/tede/handle/tede/5406 |
Resumo: | Climate analysis, whether at global, regional or local level, it has been the subject of research in various fields of earth sciences. Among the climatic parameters, temperature and precipitation have gained importance in recent decades because of significant changes in their magnitudes. Thus, this work performs a detailed analysis of the temperature for the Greater Goiânia, using satellite images to generate surface temperature for the study area, at first, through an analysis between the years 1997 and 2008 and after in about twenty years, periodically every four years, for the years 1997, 2001, 2005, 2009 and 2014. The elaborate maps, besides showing the spatial variation of urban heat islands, show that there was significant changes to the minimum temperature, maximum and average. Between the period 1997 and 2008, the minimum decrease about 1.4°C and maximum jump of 31.2°C to 36.0°C. Test results for the five periods between 1997 and 2014, show that the year 2014 is presented as the hottest in the years studied. Through the resulting maps of this analysis, it can see that the range of temperatures, the difference between the maximum and minimum, grow with the years. An estimated temperature of satellite validation model was performed by direct comparison between the surface temperature and the data of GOIÂNIA weather station belonging to INMET, with differences of 0.7°C to 1.9°C between the temperatures demonstrating the applicability of satellite images to estimate temperatures in areas that do not have a dense meteorological network. The last analysis performed is forecast monthly temperatures for the period between the years 2040-2047, using the method of Holt-Winters. The model used for predicting allowed the computation of the seasonality of the minimum monthly temperatures, average and maximum for the historical period between the years 1970 to 2015. The predicted temperatures renew the expectation of increased minimum temperatures, average and maximum presented by the analysis of Historic data. As shown, in addition to the monthly increases in temperature, the occurrence of these will be situated in the highest classes of about 1.0° C warmer. We can see that, too, after 2000, all temperatures rise significantly, where their amplitudes between the minimum and maximum are located at a higher level than in previous years. |
id |
UFG-2_464f9a88c1260344d358bb417a21239c |
---|---|
oai_identifier_str |
oai:repositorio.bc.ufg.br:tede/5406 |
network_acronym_str |
UFG-2 |
network_name_str |
Repositório Institucional da UFG |
repository_id_str |
|
spelling |
Ferreira, Nilson Clementinohttp://lattes.cnpq.br/6466969611652630Ferreira, Nilson ClementinoSoares, Alexandre KepplerBoggione, Giovanni de Araújohttp://lattes.cnpq.br/8064559365983144Siqueira, Rubens Villar2016-04-04T11:52:29Z2015-12-03SIQUEIRA, R. V. Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores. 2015. 122 f. Dissertação (Mestrado em Engenharia do Meio Ambiente) - Universidade Federal de Goiás, Goiânia, 2015.http://repositorio.bc.ufg.br/tede/handle/tede/5406ark:/38995/00130000014z9Climate analysis, whether at global, regional or local level, it has been the subject of research in various fields of earth sciences. Among the climatic parameters, temperature and precipitation have gained importance in recent decades because of significant changes in their magnitudes. Thus, this work performs a detailed analysis of the temperature for the Greater Goiânia, using satellite images to generate surface temperature for the study area, at first, through an analysis between the years 1997 and 2008 and after in about twenty years, periodically every four years, for the years 1997, 2001, 2005, 2009 and 2014. The elaborate maps, besides showing the spatial variation of urban heat islands, show that there was significant changes to the minimum temperature, maximum and average. Between the period 1997 and 2008, the minimum decrease about 1.4°C and maximum jump of 31.2°C to 36.0°C. Test results for the five periods between 1997 and 2014, show that the year 2014 is presented as the hottest in the years studied. Through the resulting maps of this analysis, it can see that the range of temperatures, the difference between the maximum and minimum, grow with the years. An estimated temperature of satellite validation model was performed by direct comparison between the surface temperature and the data of GOIÂNIA weather station belonging to INMET, with differences of 0.7°C to 1.9°C between the temperatures demonstrating the applicability of satellite images to estimate temperatures in areas that do not have a dense meteorological network. The last analysis performed is forecast monthly temperatures for the period between the years 2040-2047, using the method of Holt-Winters. The model used for predicting allowed the computation of the seasonality of the minimum monthly temperatures, average and maximum for the historical period between the years 1970 to 2015. The predicted temperatures renew the expectation of increased minimum temperatures, average and maximum presented by the analysis of Historic data. As shown, in addition to the monthly increases in temperature, the occurrence of these will be situated in the highest classes of about 1.0° C warmer. We can see that, too, after 2000, all temperatures rise significantly, where their amplitudes between the minimum and maximum are located at a higher level than in previous years.A análise do clima, seja em escala global, regional ou local, tem sido objeto de pesquisa em diversas áreas das ciências da terra. Dentre os parâmetros climáticos, a temperatura e a precipitação ganharam importância nas últimas décadas devido as alterações significativas em suas magnitudes. Desta forma, este trabalho executa uma análise particularizada da temperatura para a Região Metropolitana de Goiânia, utilizando imagens de satélites a fim de gerar a temperatura de superfície para a área de estudo, em um primeiro momento, por meio de uma análise entre os anos de 1997 e 2008 e após em cerca de vinte anos, periodicamente a cada quatro anos, para os anos de 1997, 2001, 2005, 2009 e 2014. Os mapas elaborados, além de mostrarem a variação espacial das ilhas de calor urbano, demonstram que houve variações significativas para as temperaturas mínimas, máximas e médias. Entre o período de 1997 e 2008, as mínimas decrescem aproximadamente em 1,4°C e as máximas saltam de 31,2°C para 36,0°C. Os resultados da análise para os cinco períodos entre 1997 e 2014, demonstram que o ano de 2014 se apresentou como o mais quente entre os anos estudados. Por meio dos mapas resultantes desta análise, é possível notar que a amplitude das temperaturas, diferença entre as máximas e mínimas, crescem com o decorrer dos anos. Um modelo de validação das temperaturas estimadas por satélite foi executado por meio da comparação direta entre a temperatura de superfície e os dados da estação meteorológica GOIÂNIA, pertencente ao INMET, apresentando diferenças de 0,7°C a 1,9°C entre as temperaturas, demonstrando a aplicabilidade de imagens de satélite para estimativa de temperaturas em áreas que não dispõem de uma rede meteorológica adensada. A última análise executada trata da previsão de temperaturas mensais para o período entre os anos de 2040 a 2047, utilizando o método de Holt-Winters. O modelo adotado para a previsão permitiu a computação da sazonalidade das temperaturas mensais mínimas, médias e máximas para o período histórico entre os anos de 1970 a 2015. As temperaturas previstas reafirmam a expectativa do aumento das temperaturas mínimas, médias e máximas apresentadas pela análise dos dados históricos. Conforme demonstrado, além dos aumentos nas temperaturas mensais, a ocorrência destas se situará em regiões mais altas, com cerca de 1,0°C mais quentes. Podemos notar que, também, após o ano 2000, todas as temperaturas se elevam de forma significativa, onde suas amplitudes entre as mínimas e máximas se situam em um patamar mais elevado que nos anos anteriores.Submitted by Cláudia Bueno (claudiamoura18@gmail.com) on 2016-04-01T19:43:27Z No. of bitstreams: 2 Dissertação - Rubens Villar Siqueira - 2015.pdf: 4882241 bytes, checksum: 3f8cb0b344dec7efd60e3c7564ed2c56 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-04-04T11:52:29Z (GMT) No. of bitstreams: 2 Dissertação - Rubens Villar Siqueira - 2015.pdf: 4882241 bytes, checksum: 3f8cb0b344dec7efd60e3c7564ed2c56 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5)Made available in DSpace on 2016-04-04T11:52:29Z (GMT). No. of bitstreams: 2 Dissertação - Rubens Villar Siqueira - 2015.pdf: 4882241 bytes, checksum: 3f8cb0b344dec7efd60e3c7564ed2c56 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2015-12-03Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPqapplication/pdfporUniversidade Federal de GoiásPrograma de Pós-graduação em Engenharia do Meio Ambiente (EEC)UFGBrasilEscola de Engenharia Civil - EEC (RG)http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessTemperatura de superfícieIlha de calor urbano (ICU)Imagens de satélitesPrevisão de temperaturasSurface temperatureUrban heat island (UHI)Satellite imagesTemperature forecastENGENHARIA CIVIL::ENGENHARIA HIDRAULICAEstimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posterioresEstimated surface temperature in the region in metropolitan Goiânia Landsat images media and temperatures forecast for subsequent periodsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesis10097020919728748476006006006007240872516263155857548969681814834114-2555911436985713659reponame:Repositório Institucional da UFGinstname:Universidade Federal de Goiás (UFG)instacron:UFGLICENSElicense.txtlicense.txttext/plain; charset=utf-82165http://repositorio.bc.ufg.br/tede/bitstreams/58b6e1ec-bdd2-44b7-8381-63a490c1050c/downloadbd3efa91386c1718a7f26a329fdcb468MD51CC-LICENSElicense_urllicense_urltext/plain; charset=utf-849http://repositorio.bc.ufg.br/tede/bitstreams/1bd1dd9a-9577-4b65-9cbe-8e44e7bdf1be/download4afdbb8c545fd630ea7db775da747b2fMD52license_textlicense_texttext/html; charset=utf-822064http://repositorio.bc.ufg.br/tede/bitstreams/97b5c2c7-c7de-4715-843d-8896decf8554/downloadef48816a10f2d45f2e2fee2f478e2fafMD53license_rdflicense_rdfapplication/rdf+xml; charset=utf-823148http://repositorio.bc.ufg.br/tede/bitstreams/9669e505-2410-4bd2-812b-448292d34985/download9da0b6dfac957114c6a7714714b86306MD54ORIGINALDissertação - Rubens Villar Siqueira - 2015.pdfDissertação - Rubens Villar Siqueira - 2015.pdfapplication/pdf4882241http://repositorio.bc.ufg.br/tede/bitstreams/5098ccfc-7358-4580-b103-bf02adc1945a/download3f8cb0b344dec7efd60e3c7564ed2c56MD55tede/54062016-04-04 08:52:29.495http://creativecommons.org/licenses/by-nc-nd/4.0/Acesso Abertoopen.accessoai:repositorio.bc.ufg.br:tede/5406http://repositorio.bc.ufg.br/tedeRepositório InstitucionalPUBhttp://repositorio.bc.ufg.br/oai/requesttasesdissertacoes.bc@ufg.bropendoar:2016-04-04T11:52:29Repositório Institucional da UFG - Universidade Federal de Goiás (UFG)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 |
dc.title.por.fl_str_mv |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
dc.title.alternative.eng.fl_str_mv |
Estimated surface temperature in the region in metropolitan Goiânia Landsat images media and temperatures forecast for subsequent periods |
title |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
spellingShingle |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores Siqueira, Rubens Villar Temperatura de superfície Ilha de calor urbano (ICU) Imagens de satélites Previsão de temperaturas Surface temperature Urban heat island (UHI) Satellite images Temperature forecast ENGENHARIA CIVIL::ENGENHARIA HIDRAULICA |
title_short |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
title_full |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
title_fullStr |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
title_full_unstemmed |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
title_sort |
Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores |
author |
Siqueira, Rubens Villar |
author_facet |
Siqueira, Rubens Villar |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Ferreira, Nilson Clementino |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/6466969611652630 |
dc.contributor.referee1.fl_str_mv |
Ferreira, Nilson Clementino |
dc.contributor.referee2.fl_str_mv |
Soares, Alexandre Keppler |
dc.contributor.referee3.fl_str_mv |
Boggione, Giovanni de Araújo |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/8064559365983144 |
dc.contributor.author.fl_str_mv |
Siqueira, Rubens Villar |
contributor_str_mv |
Ferreira, Nilson Clementino Ferreira, Nilson Clementino Soares, Alexandre Keppler Boggione, Giovanni de Araújo |
dc.subject.por.fl_str_mv |
Temperatura de superfície Ilha de calor urbano (ICU) Imagens de satélites Previsão de temperaturas |
topic |
Temperatura de superfície Ilha de calor urbano (ICU) Imagens de satélites Previsão de temperaturas Surface temperature Urban heat island (UHI) Satellite images Temperature forecast ENGENHARIA CIVIL::ENGENHARIA HIDRAULICA |
dc.subject.eng.fl_str_mv |
Surface temperature Urban heat island (UHI) Satellite images Temperature forecast |
dc.subject.cnpq.fl_str_mv |
ENGENHARIA CIVIL::ENGENHARIA HIDRAULICA |
description |
Climate analysis, whether at global, regional or local level, it has been the subject of research in various fields of earth sciences. Among the climatic parameters, temperature and precipitation have gained importance in recent decades because of significant changes in their magnitudes. Thus, this work performs a detailed analysis of the temperature for the Greater Goiânia, using satellite images to generate surface temperature for the study area, at first, through an analysis between the years 1997 and 2008 and after in about twenty years, periodically every four years, for the years 1997, 2001, 2005, 2009 and 2014. The elaborate maps, besides showing the spatial variation of urban heat islands, show that there was significant changes to the minimum temperature, maximum and average. Between the period 1997 and 2008, the minimum decrease about 1.4°C and maximum jump of 31.2°C to 36.0°C. Test results for the five periods between 1997 and 2014, show that the year 2014 is presented as the hottest in the years studied. Through the resulting maps of this analysis, it can see that the range of temperatures, the difference between the maximum and minimum, grow with the years. An estimated temperature of satellite validation model was performed by direct comparison between the surface temperature and the data of GOIÂNIA weather station belonging to INMET, with differences of 0.7°C to 1.9°C between the temperatures demonstrating the applicability of satellite images to estimate temperatures in areas that do not have a dense meteorological network. The last analysis performed is forecast monthly temperatures for the period between the years 2040-2047, using the method of Holt-Winters. The model used for predicting allowed the computation of the seasonality of the minimum monthly temperatures, average and maximum for the historical period between the years 1970 to 2015. The predicted temperatures renew the expectation of increased minimum temperatures, average and maximum presented by the analysis of Historic data. As shown, in addition to the monthly increases in temperature, the occurrence of these will be situated in the highest classes of about 1.0° C warmer. We can see that, too, after 2000, all temperatures rise significantly, where their amplitudes between the minimum and maximum are located at a higher level than in previous years. |
publishDate |
2015 |
dc.date.issued.fl_str_mv |
2015-12-03 |
dc.date.accessioned.fl_str_mv |
2016-04-04T11:52:29Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
SIQUEIRA, R. V. Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores. 2015. 122 f. Dissertação (Mestrado em Engenharia do Meio Ambiente) - Universidade Federal de Goiás, Goiânia, 2015. |
dc.identifier.uri.fl_str_mv |
http://repositorio.bc.ufg.br/tede/handle/tede/5406 |
dc.identifier.dark.fl_str_mv |
ark:/38995/00130000014z9 |
identifier_str_mv |
SIQUEIRA, R. V. Estimativa da temperatura de superfície na região metropolitana de Goiânia por meio de imagens Landsat e previsão de temperaturas para períodos posteriores. 2015. 122 f. Dissertação (Mestrado em Engenharia do Meio Ambiente) - Universidade Federal de Goiás, Goiânia, 2015. ark:/38995/00130000014z9 |
url |
http://repositorio.bc.ufg.br/tede/handle/tede/5406 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.program.fl_str_mv |
1009702091972874847 |
dc.relation.confidence.fl_str_mv |
600 600 600 600 |
dc.relation.department.fl_str_mv |
724087251626315585 |
dc.relation.cnpq.fl_str_mv |
7548969681814834114 |
dc.relation.sponsorship.fl_str_mv |
-2555911436985713659 |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.publisher.program.fl_str_mv |
Programa de Pós-graduação em Engenharia do Meio Ambiente (EEC) |
dc.publisher.initials.fl_str_mv |
UFG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
Escola de Engenharia Civil - EEC (RG) |
publisher.none.fl_str_mv |
Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFG instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Repositório Institucional da UFG |
collection |
Repositório Institucional da UFG |
bitstream.url.fl_str_mv |
http://repositorio.bc.ufg.br/tede/bitstreams/58b6e1ec-bdd2-44b7-8381-63a490c1050c/download http://repositorio.bc.ufg.br/tede/bitstreams/1bd1dd9a-9577-4b65-9cbe-8e44e7bdf1be/download http://repositorio.bc.ufg.br/tede/bitstreams/97b5c2c7-c7de-4715-843d-8896decf8554/download http://repositorio.bc.ufg.br/tede/bitstreams/9669e505-2410-4bd2-812b-448292d34985/download http://repositorio.bc.ufg.br/tede/bitstreams/5098ccfc-7358-4580-b103-bf02adc1945a/download |
bitstream.checksum.fl_str_mv |
bd3efa91386c1718a7f26a329fdcb468 4afdbb8c545fd630ea7db775da747b2f ef48816a10f2d45f2e2fee2f478e2faf 9da0b6dfac957114c6a7714714b86306 3f8cb0b344dec7efd60e3c7564ed2c56 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 MD5 MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFG - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
tasesdissertacoes.bc@ufg.br |
_version_ |
1815172520826896384 |