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| 1. |  | KUBASKI, A. L.; CORDOBA, L. do P.; RIBEIRO, L. S.; LAZZAROTTO, M.; SCHNITZLER, E. Análise térmica de diferentes amostras de amido de pinhão (Araucaria angustifolia) de diferentes regiões do sul do Brasil. Brazilian Journal of Thermal Analysis, v. 7, p. 164-167, 2015. Disponível na internet. Edição dos Anais do 7º Simpósio de Análise Térmica, 2015, Bauru.| Biblioteca(s): Embrapa Florestas. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agropecuária Oeste. Para informações adicionais entre em contato com cpao.biblioteca@embrapa.br. |
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Biblioteca(s): |
Embrapa Agropecuária Oeste. |
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Data corrente: |
16/02/2022 |
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Data da última atualização: |
16/02/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
WOLFF, W.; FRANCISCO, J. P.; FLUMIGNAN, D. L.; MARIN, F. R.; FOLEGATTI, M. V. |
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Afiliação: |
WAGNER WOLFF, PROFESSOR, ESCOLA SUPERIOR DE AGRICULTURA "LUIZ DE QUEIROZ", UNIVERSIDADE DE SÃO PAULO, PIRACICABA, SP; JOÃO PAULO FRANCISCO, UNIVERSIDADE ESTADUAL DE MARINGÁ, UMUARAMA, PR; DANILTON LUIZ FLUMIGNAN, CPAO; FÁBIO RICARDO MARIN, PROFESSOR, ESCOLA SUPERIOR DE AGRICULTURA "LUIZ DE QUEIROZ", UNIVERSIDADE DE SÃO PAULO, PIRACICABA, SP; MARCOS VINÍCIUS FOLEGATTI, PROFESSOR, ESCOLA SUPERIOR DE AGRICULTURA "LUIZ DE QUEIROZ", UNIVERSIDADE DE SÃO PAULO, PIRACICABA, SP. |
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Título: |
Optimized algorithm for evapotranspiration retrieval via remote sensing. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Agricultural Water Management, v. 262, 107390, 2022. |
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DOI: |
10.1016/j.agwat.2021.107390 |
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Idioma: |
Inglês |
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Conteúdo: |
Many algorithms for surface energy balance (SEB) based on remote sensing (RS) have been advanced to determine evapotranspiration (ET). These algorithms were developed for specific conditions (e.g., sensors, land use, and crop management) in which functions and empirical parameters within its algorithms concur with those conditions. Therefore, this study aims to develop a SEB-RS algorithm for retrieving ET adjusted to in situ ob- servations. The study was conducted in two experimental fields in Brazil with the crops Jatropha curcas, maize, soybean, and sugarcane. We used multispectral images from the orbital sensors, Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) coupled in Landsat 8 satellite and from the terrestrial sensor, Altum, on board of an unmanned aerial vehicle. The proposed algorithm termed as Ground-truthed Surface Energy Balance (GT-SEB) is based on physical formulation of SEB-RS algorithms, where two extra computational processes using in situ ET observations were proposed for originating the new algorithm. The first additional process for opti- mizing the automatic ?anchor? pixels selection and another for algorithm parameters optimization. Thus, both processes aim to reduce the difference between the observed ET and estimated by GT-SEB. Being assessed for both orbital (OLI/TIRS) and suborbital (Altum) sensors, the GT-SEB yielded excellent results (root-mean-square- error, RMSE, ≤ 0.48 mm and modified Kling-Gupta efficiency, KGE, ≥ 0.92). In addition to GT-SEB being an optimized algorithm, it uses a classic parameterization of SEB-RS algorithms, providing efficiency and scalability for other remote sensors, climates, and surfaces. MenosMany algorithms for surface energy balance (SEB) based on remote sensing (RS) have been advanced to determine evapotranspiration (ET). These algorithms were developed for specific conditions (e.g., sensors, land use, and crop management) in which functions and empirical parameters within its algorithms concur with those conditions. Therefore, this study aims to develop a SEB-RS algorithm for retrieving ET adjusted to in situ ob- servations. The study was conducted in two experimental fields in Brazil with the crops Jatropha curcas, maize, soybean, and sugarcane. We used multispectral images from the orbital sensors, Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) coupled in Landsat 8 satellite and from the terrestrial sensor, Altum, on board of an unmanned aerial vehicle. The proposed algorithm termed as Ground-truthed Surface Energy Balance (GT-SEB) is based on physical formulation of SEB-RS algorithms, where two extra computational processes using in situ ET observations were proposed for originating the new algorithm. The first additional process for opti- mizing the automatic ?anchor? pixels selection and another for algorithm parameters optimization. Thus, both processes aim to reduce the difference between the observed ET and estimated by GT-SEB. Being assessed for both orbital (OLI/TIRS) and suborbital (Altum) sensors, the GT-SEB yielded excellent results (root-mean-square- error, RMSE, ≤ 0.48 mm and modified Kling-Gupta efficiency, KGE, ≥... Mostrar Tudo |
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Palavras-Chave: |
Geoprocessamento. |
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Thesagro: |
Agricultura de Precisão; Irrigação. |
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Categoria do assunto: |
A Sistemas de Cultivo |
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Marc: |
LEADER 02348naa a2200217 a 4500
001 2140156
005 2022-02-16
008 2022 bl uuuu u00u1 u #d
024 7 $a10.1016/j.agwat.2021.107390$2DOI
100 1 $aWOLFF, W.
245 $aOptimized algorithm for evapotranspiration retrieval via remote sensing.$h[electronic resource]
260 $c2022
520 $aMany algorithms for surface energy balance (SEB) based on remote sensing (RS) have been advanced to determine evapotranspiration (ET). These algorithms were developed for specific conditions (e.g., sensors, land use, and crop management) in which functions and empirical parameters within its algorithms concur with those conditions. Therefore, this study aims to develop a SEB-RS algorithm for retrieving ET adjusted to in situ ob- servations. The study was conducted in two experimental fields in Brazil with the crops Jatropha curcas, maize, soybean, and sugarcane. We used multispectral images from the orbital sensors, Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) coupled in Landsat 8 satellite and from the terrestrial sensor, Altum, on board of an unmanned aerial vehicle. The proposed algorithm termed as Ground-truthed Surface Energy Balance (GT-SEB) is based on physical formulation of SEB-RS algorithms, where two extra computational processes using in situ ET observations were proposed for originating the new algorithm. The first additional process for opti- mizing the automatic ?anchor? pixels selection and another for algorithm parameters optimization. Thus, both processes aim to reduce the difference between the observed ET and estimated by GT-SEB. Being assessed for both orbital (OLI/TIRS) and suborbital (Altum) sensors, the GT-SEB yielded excellent results (root-mean-square- error, RMSE, ≤ 0.48 mm and modified Kling-Gupta efficiency, KGE, ≥ 0.92). In addition to GT-SEB being an optimized algorithm, it uses a classic parameterization of SEB-RS algorithms, providing efficiency and scalability for other remote sensors, climates, and surfaces.
650 $aAgricultura de Precisão
650 $aIrrigação
653 $aGeoprocessamento
700 1 $aFRANCISCO, J. P.
700 1 $aFLUMIGNAN, D. L.
700 1 $aMARIN, F. R.
700 1 $aFOLEGATTI, M. V.
773 $tAgricultural Water Management$gv. 262, 107390, 2022.
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