Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1117/12.2277588 http://hdl.handle.net/11449/159948 |
Resumo: | In the northwestern side of Sao Paulo state, irrigated crops are replacing natural vegetation, bringing importance for the development and applications of tools to quantify the energy and water balances. Remote sensing together with geostatistical tools are suitable for these tasks, being the surface temperature (T-0) one of the radiation balance modelling input parameters. However, due to the importance of high both spatial and temporal resolutions to capture the dynamics of water and vegetation conditions, when the thermal bands are absent in several high-resolution satellites, applications on water resources studies are limited. This paper aimed to test the Moving Average (MA) and the Nearest Point (NP) geostatistical interpolation methods for estimate T-0 with and without the Landsat 8 (L8) thermal bands by using a net of agrometeorological stations. In the case of using the L8 satellite thermal radiances, the Plank. s low was applied to its bands 10 and 11. Without these bands, T-0 was retrieved as residue in the radiation balance. Up scaling the satellite overpass T-0 to daily scale resulted in a root mean square error (RMSE) of only 1.72 and 1.74 K when compared with values resulted from the MA and NP applications with the residual method, respectively. However, the MA method seemed to be more suitable than the NP one, being concluded that the coupled use of high spatial resolution images without a thermal band and interpolated weather data throughout the MA method is suitable for large-scale energy and water balance studies. |
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Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo stategeosciencesradiation balanceinterpolation methodsIn the northwestern side of Sao Paulo state, irrigated crops are replacing natural vegetation, bringing importance for the development and applications of tools to quantify the energy and water balances. Remote sensing together with geostatistical tools are suitable for these tasks, being the surface temperature (T-0) one of the radiation balance modelling input parameters. However, due to the importance of high both spatial and temporal resolutions to capture the dynamics of water and vegetation conditions, when the thermal bands are absent in several high-resolution satellites, applications on water resources studies are limited. This paper aimed to test the Moving Average (MA) and the Nearest Point (NP) geostatistical interpolation methods for estimate T-0 with and without the Landsat 8 (L8) thermal bands by using a net of agrometeorological stations. In the case of using the L8 satellite thermal radiances, the Plank. s low was applied to its bands 10 and 11. Without these bands, T-0 was retrieved as residue in the radiation balance. Up scaling the satellite overpass T-0 to daily scale resulted in a root mean square error (RMSE) of only 1.72 and 1.74 K when compared with values resulted from the MA and NP applications with the residual method, respectively. However, the MA method seemed to be more suitable than the NP one, being concluded that the coupled use of high spatial resolution images without a thermal band and interpolated weather data throughout the MA method is suitable for large-scale energy and water balance studies.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Embrapa Satellite Monitoring, Campinas, SP, BrazilSao Paulo State Univ, Ilha Solteira, SP, BrazilSao Paulo State Univ, Ilha Solteira, SP, BrazilSpie-int Soc Optical EngineeringEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA)Universidade Estadual Paulista (Unesp)Teixeira, Antonio H. de C.Hernandez, Fernando B. T. [UNESP]Leivas, Janice F.Nunez, Daniel N. C. [UNESP]Momesso, Renato F. A. [UNESP]SPIENeale, CMUMaltese, A.2018-11-26T15:45:51Z2018-11-26T15:45:51Z2017-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject9application/pdfhttp://dx.doi.org/10.1117/12.2277588Remote Sensing For Agriculture, Ecosystems, And Hydrology Xix. Bellingham: Spie-int Soc Optical Engineering, v. 10421, 9 p., 2017.0277-786Xhttp://hdl.handle.net/11449/15994810.1117/12.2277588WOS:000417373000011Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengRemote Sensing For Agriculture, Ecosystems, And Hydrology Xixinfo:eu-repo/semantics/openAccess2023-10-12T06:08:17Zoai:repositorio.unesp.br:11449/159948Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-10-12T06:08:17Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
title |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
spellingShingle |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state Teixeira, Antonio H. de C. geosciences radiation balance interpolation methods |
title_short |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
title_full |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
title_fullStr |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
title_full_unstemmed |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
title_sort |
Surface temperature estimated with Landsat 8 images and geostatistical tools in the northwestern Sao Paulo state |
author |
Teixeira, Antonio H. de C. |
author_facet |
Teixeira, Antonio H. de C. Hernandez, Fernando B. T. [UNESP] Leivas, Janice F. Nunez, Daniel N. C. [UNESP] Momesso, Renato F. A. [UNESP] SPIE Neale, CMU Maltese, A. |
author_role |
author |
author2 |
Hernandez, Fernando B. T. [UNESP] Leivas, Janice F. Nunez, Daniel N. C. [UNESP] Momesso, Renato F. A. [UNESP] SPIE Neale, CMU Maltese, A. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Teixeira, Antonio H. de C. Hernandez, Fernando B. T. [UNESP] Leivas, Janice F. Nunez, Daniel N. C. [UNESP] Momesso, Renato F. A. [UNESP] SPIE Neale, CMU Maltese, A. |
dc.subject.por.fl_str_mv |
geosciences radiation balance interpolation methods |
topic |
geosciences radiation balance interpolation methods |
description |
In the northwestern side of Sao Paulo state, irrigated crops are replacing natural vegetation, bringing importance for the development and applications of tools to quantify the energy and water balances. Remote sensing together with geostatistical tools are suitable for these tasks, being the surface temperature (T-0) one of the radiation balance modelling input parameters. However, due to the importance of high both spatial and temporal resolutions to capture the dynamics of water and vegetation conditions, when the thermal bands are absent in several high-resolution satellites, applications on water resources studies are limited. This paper aimed to test the Moving Average (MA) and the Nearest Point (NP) geostatistical interpolation methods for estimate T-0 with and without the Landsat 8 (L8) thermal bands by using a net of agrometeorological stations. In the case of using the L8 satellite thermal radiances, the Plank. s low was applied to its bands 10 and 11. Without these bands, T-0 was retrieved as residue in the radiation balance. Up scaling the satellite overpass T-0 to daily scale resulted in a root mean square error (RMSE) of only 1.72 and 1.74 K when compared with values resulted from the MA and NP applications with the residual method, respectively. However, the MA method seemed to be more suitable than the NP one, being concluded that the coupled use of high spatial resolution images without a thermal band and interpolated weather data throughout the MA method is suitable for large-scale energy and water balance studies. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-01-01 2018-11-26T15:45:51Z 2018-11-26T15:45:51Z |
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 |
http://dx.doi.org/10.1117/12.2277588 Remote Sensing For Agriculture, Ecosystems, And Hydrology Xix. Bellingham: Spie-int Soc Optical Engineering, v. 10421, 9 p., 2017. 0277-786X http://hdl.handle.net/11449/159948 10.1117/12.2277588 WOS:000417373000011 |
url |
http://dx.doi.org/10.1117/12.2277588 http://hdl.handle.net/11449/159948 |
identifier_str_mv |
Remote Sensing For Agriculture, Ecosystems, And Hydrology Xix. Bellingham: Spie-int Soc Optical Engineering, v. 10421, 9 p., 2017. 0277-786X 10.1117/12.2277588 WOS:000417373000011 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Remote Sensing For Agriculture, Ecosystems, And Hydrology Xix |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
9 application/pdf |
dc.publisher.none.fl_str_mv |
Spie-int Soc Optical Engineering |
publisher.none.fl_str_mv |
Spie-int Soc Optical Engineering |
dc.source.none.fl_str_mv |
Web of Science 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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1799964535026614272 |