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dc.contributor.authorTavares, Matheus Henriquept_BR
dc.contributor.authorCunha, Augusto Hugo Farias dapt_BR
dc.contributor.authorMarques, David Manuel Lelinho da Mottapt_BR
dc.contributor.authorRuhoff, Anderson Luispt_BR
dc.contributor.authorCavalcanti, José Rafael de Albuquerquept_BR
dc.contributor.authorFragoso Júnior, Carlos Rubertopt_BR
dc.contributor.authorBravo, Juan Martínpt_BR
dc.contributor.authorMunar Samboní, Andrés Mauriciopt_BR
dc.contributor.authorFan, Fernando Mainardipt_BR
dc.contributor.authorRodrigues, Lúcia Helena Ribeiropt_BR
dc.date.accessioned2019-03-08T02:31:10Zpt_BR
dc.date.issued2019pt_BR
dc.identifier.issn2073-4441pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/189268pt_BR
dc.description.abstractWater 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.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofWater. Basel, Switzerland. Vol.11, n.1 (jan. 2019), 168, 21 f.pt_BR
dc.rightsOpen Accessen
dc.subjectWater-surface temperatureen
dc.subjectSensoriamento remotopt_BR
dc.subjectLakesen
dc.subjectLandsatpt_BR
dc.subjectRemote sensingen
dc.subjectLagospt_BR
dc.subjectModerate Resolution Imaging Spectroradiometer (MODIS)pt_BR
dc.subjectThermal infrareden
dc.subjectLandsaten
dc.subjectTemperatura da águapt_BR
dc.titleComparison 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 Brazilpt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001088847pt_BR
dc.type.originEstrangeiropt_BR


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