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| 15. |  | TEIXEIRA, A. H. DE C.; LEIVAS, J. F.; TAKEMURA, C. M.; GARCON, E. A. M. Aplicação do algoritmo SAFER para monitoramento da evapotranspiração nos Biomas brasileiros. In: SILVA, C. D. D. da; ROLIM, E. C. de A. (Org.). Aspectos e impactos ambientais: o que geram as atividades do homem? Ponta Grossa, PR: Atena, 2021. Publicado também em: TEIXEIRA, A. H. DE C.; LEIVAS, J. F.; TAKEMURA, C. M.; GARCON, E. A. M. Aplicação do algoritmo SAFER para monitoramento da evapotranspiração nos Biomas brasileiros. In: ENCONTRO DE RECURSOS HÍDRICOS EM SERGIPE,...| Biblioteca(s): Embrapa Territorial. |
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| 20. | | PINTO, D. M.; CORDEIRO, F. L.; TAKEMURA, C. M.; SOLANO, V. de O. Cartografia temática da pesquisa técnico-científica da Embrapa destinada à agricultura familiar: uma contribuição para a segurança alimentar. In: CONGRESSO BRASILEIRO DE BIBLIOTECONOMIA, DOCUMENTAÇÃO E CIÊNCIA DA INFORMAÇÃO, 26., 2017, Fortaleza. Anais... Fortaleza: FEBAB, 2017. 392-410. Publicado também em: Revista Brasileira de Biblioteconomia e Documentação, v. 13, p. 392-410, n. esp. CBBD 2017.| Biblioteca(s): Embrapa Pantanal. |
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| Registros recuperados : 78 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Meio Ambiente; Embrapa Territorial. |
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Data corrente: |
24/07/2023 |
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Data da última atualização: |
24/07/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 3 |
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Autoria: |
TEIXEIRA, A. H. DE C.; LEIVAS, J. F.; TAKEMURA, C. M.; SILVA, G. B. S. da; GARCON, E. A. M.; SOUSA, I.; CESAR SILVA. |
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Afiliação: |
ANTONIO HERIBERTO DE CASTRO TEIXEIRA, UNIVERSIDADE FEDERAL DE SERGIPE; JANICE FREITAS LEIVAS, CNPM; CELINA MAKI TAKEMURA, CNPM; GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPMA; EDLENE APARECIDA MONTEIRO GARCON, CNPM; INAJÁ SOUSA, UNIVERSIDADE FEDERAL DE SERGIPE; SILVA, C., UNIVERSIDADE ESTADUAL DE CAMPINAS. |
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Título: |
Remote sensing environmental indicators for monitoring spatial and temporal dynamics of weather and vegetation conditions: applications for Brazilian biomes. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Environmental Monitoring and Assessment, v. 195, n. 944, 2023. |
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ISSN: |
1573-2959 |
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DOI: |
doi.org/10.1007/s10661-023-11560-8 |
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Idioma: |
Português |
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Conteúdo: |
Abstract: The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P−ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling showed suitability for monitoring the water and vegetation conditions, making way to detect anomalies for specific periods along the year by using historical images and weather data, with strong potential to support public policies for management and conservation of natural resources and with possibilities for replication of the methods in other countries. MenosAbstract: The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P−ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling sho... Mostrar Tudo |
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Palavras-Chave: |
Precipitation; Water productivity. |
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Thesagro: |
Evapotranspiração; Sensoriamento Remoto. |
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Thesaurus NAL: |
Biomass production; Evapotranspiration; Water balance. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1155228/1/6143.pdf
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Marc: |
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001 2155228
005 2023-07-24
008 2023 bl uuuu u00u1 u #d
022 $a1573-2959
024 7 $adoi.org/10.1007/s10661-023-11560-8$2DOI
100 1 $aTEIXEIRA, A. H. DE C.
245 $aRemote sensing environmental indicators for monitoring spatial and temporal dynamics of weather and vegetation conditions$bapplications for Brazilian biomes.$h[electronic resource]
260 $c2023
520 $aAbstract: The SAFER (Simple Algorithm for Evapotranspiration Retrieving) algorithm and the radiation use efficiency (RUE) model were coupled to test large-scale remote sensing environmental indicators in Brazilian biomes. MODIS MOD13Q1 reflectance product and gridded weather data for the year 2016 were used to demonstrate the suitability of the algorithm to monitor the dynamics of environmental remote sensing indicators along a year in the Brazilian biomes, Amazon, Caatinga, Cerrado, Pantanal, Atlantic Forest, and Pampa. Significant spatial and temporal variations in precipitation (P), actual evapotranspiration (ET), and biomass production (BIO) yielded differences on water balance (WB = P−ET) and water productivity (WP = ET/BIO). The highest WB and WP differences were detected in the wettest biomes, Amazon, Atlantic Forest, and Pampa, when compared with the driest biome, Caatinga. Rainfall distribution along the year affected the magnitude of the evaporative fraction (ETf), i.e., the ET to reference evapotranspiration (ET0) ratio. However, there was a gap between ETf and WB, which may be related to the time needed for recovering good soil moisture conditions after rainfalls. For some biomes, BIO related most to the levels of absorbed photosynthetically active radiation (Amazon and Atlantic Forest), while for others, BIO followed most the soil moisture levels, depicted by ETf (Caatinga, Cerrado, Pantanal, and Pampa). The large-scale modeling showed suitability for monitoring the water and vegetation conditions, making way to detect anomalies for specific periods along the year by using historical images and weather data, with strong potential to support public policies for management and conservation of natural resources and with possibilities for replication of the methods in other countries.
650 $aBiomass production
650 $aEvapotranspiration
650 $aWater balance
650 $aEvapotranspiração
650 $aSensoriamento Remoto
653 $aPrecipitation
653 $aWater productivity
700 1 $aLEIVAS, J. F.
700 1 $aTAKEMURA, C. M.
700 1 $aSILVA, G. B. S. da
700 1 $aGARCON, E. A. M.
700 1 $aSOUSA, I.
700 1 $aCESAR SILVA
773 $tEnvironmental Monitoring and Assessment$gv. 195, n. 944, 2023.
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Embrapa Territorial (CNPM) |
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