Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil

Detalhes bibliográficos
Autor(a) principal: Tavares, Matheus Henrique
Data de Publicação: 2019
Outros Autores: Cunha, Augusto Hugo Farias da, Marques, David Manuel Lelinho da Motta, Ruhoff, Anderson Luis, Cavalcanti, José Rafael de Albuquerque, Fragoso Júnior, Carlos Ruberto, Bravo, Juan Martín, Munar Samboní, Andrés Mauricio, Fan, Fernando Mainardi, Rodrigues, Lúcia Helena Ribeiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/189268
Resumo: Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.
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spelling Tavares, Matheus HenriqueCunha, Augusto Hugo Farias daMarques, David Manuel Lelinho da MottaRuhoff, Anderson LuisCavalcanti, José Rafael de AlbuquerqueFragoso Júnior, Carlos RubertoBravo, Juan MartínMunar Samboní, Andrés MauricioFan, Fernando MainardiRodrigues, Lúcia Helena Ribeiro2019-03-08T02:31:10Z20192073-4441http://hdl.handle.net/10183/189268001088847Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.application/pdfengWater. Basel, Switzerland. Vol.11, n.1 (jan. 2019), 168, 21 f.Sensoriamento remotoLandsatLagosModerate Resolution Imaging Spectroradiometer (MODIS)Temperatura da águaWater-surface temperatureLakesRemote sensingThermal infraredLandsatComparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern BrazilEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001088847.pdf.txt001088847.pdf.txtExtracted Texttext/plain69527http://www.lume.ufrgs.br/bitstream/10183/189268/2/001088847.pdf.txtcbb513f164ea4e87a37dced1f200bd94MD52ORIGINAL001088847.pdfTexto completo (inglês)application/pdf748483http://www.lume.ufrgs.br/bitstream/10183/189268/1/001088847.pdf2fb6421ec7025a3a7dcc95a65d70a77eMD5110183/1892682019-06-21 02:34:24.749772oai:www.lume.ufrgs.br:10183/189268Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2019-06-21T05:34:24Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
title Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
spellingShingle Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
Tavares, Matheus Henrique
Sensoriamento remoto
Landsat
Lagos
Moderate Resolution Imaging Spectroradiometer (MODIS)
Temperatura da água
Water-surface temperature
Lakes
Remote sensing
Thermal infrared
Landsat
title_short Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
title_full Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
title_fullStr Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
title_full_unstemmed Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
title_sort Comparison of methods to estimate lake-surface-water temperature using Landsat 7 ETM+ and MODIS imagery : case study of a large shallow subtropical lake in southern Brazil
author Tavares, Matheus Henrique
author_facet Tavares, Matheus Henrique
Cunha, Augusto Hugo Farias da
Marques, David Manuel Lelinho da Motta
Ruhoff, Anderson Luis
Cavalcanti, José Rafael de Albuquerque
Fragoso Júnior, Carlos Ruberto
Bravo, Juan Martín
Munar Samboní, Andrés Mauricio
Fan, Fernando Mainardi
Rodrigues, Lúcia Helena Ribeiro
author_role author
author2 Cunha, Augusto Hugo Farias da
Marques, David Manuel Lelinho da Motta
Ruhoff, Anderson Luis
Cavalcanti, José Rafael de Albuquerque
Fragoso Júnior, Carlos Ruberto
Bravo, Juan Martín
Munar Samboní, Andrés Mauricio
Fan, Fernando Mainardi
Rodrigues, Lúcia Helena Ribeiro
author2_role author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Tavares, Matheus Henrique
Cunha, Augusto Hugo Farias da
Marques, David Manuel Lelinho da Motta
Ruhoff, Anderson Luis
Cavalcanti, José Rafael de Albuquerque
Fragoso Júnior, Carlos Ruberto
Bravo, Juan Martín
Munar Samboní, Andrés Mauricio
Fan, Fernando Mainardi
Rodrigues, Lúcia Helena Ribeiro
dc.subject.por.fl_str_mv Sensoriamento remoto
Landsat
Lagos
Moderate Resolution Imaging Spectroradiometer (MODIS)
Temperatura da água
topic Sensoriamento remoto
Landsat
Lagos
Moderate Resolution Imaging Spectroradiometer (MODIS)
Temperatura da água
Water-surface temperature
Lakes
Remote sensing
Thermal infrared
Landsat
dc.subject.eng.fl_str_mv Water-surface temperature
Lakes
Remote sensing
Thermal infrared
Landsat
description Water temperature regulates many processes in lakes; therefore, evaluating it is essential to understand its ecological status and functioning, and to comprehend the impact of climate change. Although few studies assessed the accuracy of individual sensors in estimating lake-surface-water temperature (LSWT), comparative analysis considering different sensors is still needed. This study evaluated the performance of two thermal sensors, MODIS and Landsat 7 ETM+, and used Landsat methods to estimate the SWT of a large subtropical lake. MODIS products MOD11 LST and MOD28 SST were used for comparison. For the Landsat images, the radiative transfer equation (RTE), using NASA’s Atmospheric Correction Parameter Calculator (AtmCorr) parameters, was compared with the single-channel algorithm in different approaches. Our results showed that MOD11 obtained the highest accuracy (RMSE of 1.05 C), and is the recommended product for LSWT studies. For Landsat-derived SWT, AtmCorr obtained the highest accuracy (RMSE of 1.07 C) and is the recommended method for small lakes. Sensitivity analysis showed that Landsat-derived LSWT using the RTE is very sensitive to atmospheric parameters and emissivity. A discussion of the main error sources was conducted. We recommend that similar tests be applied for Landsat imagery on different lakes, further studies on algorithms to correct the cool-skin effect in inland waters, and tests of different emissivity values to verify if it can compensate for this effect, in an effort to improve the accuracy of these estimates.
publishDate 2019
dc.date.accessioned.fl_str_mv 2019-03-08T02:31:10Z
dc.date.issued.fl_str_mv 2019
dc.type.driver.fl_str_mv Estrangeiro
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10183/189268
dc.identifier.issn.pt_BR.fl_str_mv 2073-4441
dc.identifier.nrb.pt_BR.fl_str_mv 001088847
identifier_str_mv 2073-4441
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url http://hdl.handle.net/10183/189268
dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Water. Basel, Switzerland. Vol.11, n.1 (jan. 2019), 168, 21 f.
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