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| Registros recuperados : 95 | |
| 19. |  | CORRÊA, C. L. O.; LUNA, A. S.; PENHA, E. das M.; GOTTSCHALK, L. M. F. Determinação de acrilamida por espectrofluorêscencia em amostras de café. In: CONGRESSO BRASILEIRO DE PESQUISA S CAFEEIRAS, 44., 2018, Franca, SP. O Nosso café, melhorados desde o pé: Trabalhos apresentados. Varginha: Fundação Procafé, 2018. p. 182-183 23 a 26 out. 2018. Seção 4.5. Colheita, preparo, qualidade do café, consumo e saúde.| Biblioteca(s): Embrapa Agroindústria de Alimentos. |
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| Registros recuperados : 95 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
14/06/2021 |
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Data da última atualização: |
16/08/2021 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
B - 1 |
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Autoria: |
SILVA, L. A. P. da; BOLFE, E. L.; SOUZA, C. M. P. de; FILGUEIRAS, R. |
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Afiliação: |
LUCAS AUGUSTO PEREIRA DA SILVA, UFU; EDSON LUIS BOLFE, CNPTIA; CRISTIANO MARCELO PEREIRA DE SOUZA, UNIMONTES; ROBERTO FILGUEIRAS, UFV. |
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Título: |
The sensitivity of evapotranspiration for land uses and topography in area of Cerrado Biome - Brazil. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Espaço & Geografia, v. 24, n. 1, p. 132-148, 2021. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract: Evapotranspiration (ET) is a crucial element in the spatiotemporal dynamics of moisture, energy, and heat, and is related to climatic, pedogeomorphological, and phytophysiognomic aspects of the landscape. Therefore, estimating ET requires dynamic and integrated temporal analysis with biophysical landscape factors. The study aimed to analyze the behavior of ET through the analysis of land use and land cover and topographic in time series. The Simple Algorithm for Evapotranspiration Recovery (SAFER) model was used to obtain the variable ET in the periods of 01/21, 02/22, 05/13 and 06/30/2019 (variables). A database of explanatory covariates was constructed, including land use and land cover, satellite image data (Landsat-8) and digital elevation model (SRTM). The values of variables and covariates were extracted into a grid of points and separated for three altimetric conditions, and the linear Gaussian Models (GLM) were applied to the point data. The most explanatory spectral covariates for the ET variation were Albedo and Surface Temperature. And the covariates related to topography were Digital Elevation Model and Topographic Moisture Index. In general, the wet period presents a higher ET rate (2.06 mm d-¹). Forests generated the highest ET regardless of period (1.62 mm d-¹ to 4.03 mm d-¹). Elevated topography also influences the increase in ET in relation to the same lower altimetry classes (A2 and A3). This influence is associated with the altitude dynamics and intrinsic elements of the region, such as the marshy environment in the A3 region, where the highest ET values occurred. This work stands out from its peers for addressing the influence of landscape aspects on the knowledge of evapotranspiration variation, a vanguard theme in the scope of spatial analysis. MenosAbstract: Evapotranspiration (ET) is a crucial element in the spatiotemporal dynamics of moisture, energy, and heat, and is related to climatic, pedogeomorphological, and phytophysiognomic aspects of the landscape. Therefore, estimating ET requires dynamic and integrated temporal analysis with biophysical landscape factors. The study aimed to analyze the behavior of ET through the analysis of land use and land cover and topographic in time series. The Simple Algorithm for Evapotranspiration Recovery (SAFER) model was used to obtain the variable ET in the periods of 01/21, 02/22, 05/13 and 06/30/2019 (variables). A database of explanatory covariates was constructed, including land use and land cover, satellite image data (Landsat-8) and digital elevation model (SRTM). The values of variables and covariates were extracted into a grid of points and separated for three altimetric conditions, and the linear Gaussian Models (GLM) were applied to the point data. The most explanatory spectral covariates for the ET variation were Albedo and Surface Temperature. And the covariates related to topography were Digital Elevation Model and Topographic Moisture Index. In general, the wet period presents a higher ET rate (2.06 mm d-¹). Forests generated the highest ET regardless of period (1.62 mm d-¹ to 4.03 mm d-¹). Elevated topography also influences the increase in ET in relation to the same lower altimetry classes (A2 and A3). This influence is associated with the altitude dynamics and ... Mostrar Tudo |
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Palavras-Chave: |
GLM; Hypsometric regions; Modelo Algoritmo Simples para Recuperação da Evapotranspiração; Modelo SAFER; Modelos Lineares Gaussianos; Regiões Altimétricas; Série temporal; Uso do solo. |
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Thesagro: |
Cerrado; Cobertura do Solo; Evapotranspiração; Sensoriamento Remoto. |
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Thesaurus NAL: |
Evapotranspiration; Land cover; Land use; Remote sensing. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/223736/1/AP-Sensitivity-evapotranspiration-2021.pdf
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Marc: |
LEADER 02868naa a2200349 a 4500
001 2132273
005 2021-08-16
008 2021 bl uuuu u00u1 u #d
100 1 $aSILVA, L. A. P. da
245 $aThe sensitivity of evapotranspiration for land uses and topography in area of Cerrado Biome - Brazil.$h[electronic resource]
260 $c2021
520 $aAbstract: Evapotranspiration (ET) is a crucial element in the spatiotemporal dynamics of moisture, energy, and heat, and is related to climatic, pedogeomorphological, and phytophysiognomic aspects of the landscape. Therefore, estimating ET requires dynamic and integrated temporal analysis with biophysical landscape factors. The study aimed to analyze the behavior of ET through the analysis of land use and land cover and topographic in time series. The Simple Algorithm for Evapotranspiration Recovery (SAFER) model was used to obtain the variable ET in the periods of 01/21, 02/22, 05/13 and 06/30/2019 (variables). A database of explanatory covariates was constructed, including land use and land cover, satellite image data (Landsat-8) and digital elevation model (SRTM). The values of variables and covariates were extracted into a grid of points and separated for three altimetric conditions, and the linear Gaussian Models (GLM) were applied to the point data. The most explanatory spectral covariates for the ET variation were Albedo and Surface Temperature. And the covariates related to topography were Digital Elevation Model and Topographic Moisture Index. In general, the wet period presents a higher ET rate (2.06 mm d-¹). Forests generated the highest ET regardless of period (1.62 mm d-¹ to 4.03 mm d-¹). Elevated topography also influences the increase in ET in relation to the same lower altimetry classes (A2 and A3). This influence is associated with the altitude dynamics and intrinsic elements of the region, such as the marshy environment in the A3 region, where the highest ET values occurred. This work stands out from its peers for addressing the influence of landscape aspects on the knowledge of evapotranspiration variation, a vanguard theme in the scope of spatial analysis.
650 $aEvapotranspiration
650 $aLand cover
650 $aLand use
650 $aRemote sensing
650 $aCerrado
650 $aCobertura do Solo
650 $aEvapotranspiração
650 $aSensoriamento Remoto
653 $aGLM
653 $aHypsometric regions
653 $aModelo Algoritmo Simples para Recuperação da Evapotranspiração
653 $aModelo SAFER
653 $aModelos Lineares Gaussianos
653 $aRegiões Altimétricas
653 $aSérie temporal
653 $aUso do solo
700 1 $aBOLFE, E. L.
700 1 $aSOUZA, C. M. P. de
700 1 $aFILGUEIRAS, R.
773 $tEspaço & Geografia$gv. 24, n. 1, p. 132-148, 2021.
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Embrapa Agricultura Digital (CNPTIA) |
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