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| Registros recuperados : 22 | |
| 4. |  | ACCIOLY, L. J. de O.; HUETE, A. R. Resposta espectral de solos em razão do ângulo de visada, da umidade e da rugosidade superficial. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 35, n. 12, p. 2473-84, dez. 2000. Título em inglês: Soil spectral response in relation to viewing angle, soil moisture and surface roughness.| Biblioteca(s): Embrapa Solos; Embrapa Unidades Centrais. |
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| 6. | | HAREN, J. van; SALESKA, S.; HUETE, A.; KELLER, M.; OLIVEIRA, R. C. Amazon forest tree species composition influences soil fluxes of CO2 and N2O. In: SCIENCE TEAM MEETING, 10., 2006, Brasília, DF. Book of Abstracts... Manaus: LBA-ECO, 2006. p. 19.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 7. | | MIURA, T.; HUETE, A. R.; FERREIRA, L. G.; SANO, E. E. An assessment of land cover dependencies of VI-biophysical relationships for regional extrapolations of ground LBA ecology measurements in Brazilian Cerrado In: CONFERÊNCIA CIENTÍFICA DO LBA, 3., 2004, Brasília, DF. Anais de trabalhos completos. Brasília, DF: LBA, 2004. 1 p.| Biblioteca(s): Embrapa Cerrados. |
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| 10. | | POTTER, C.; BUSTAMANTE, M.; FERREIRA, L.; HUETE, A.; KLOOSTER, S.; KRAMER, M.; COSME, R. Synthesis studies of secondary forest productivity in the Amazon: field data, remote sensing, modeling approaches. In: SCIENCE TEAM MEETING, 10., 2006, Brasília, DF. Book of Abstracts... Manaus: LBA-ECO, 2006. p. 32.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 14. | | SHIMABUKURO, Y. E.; VERONA, J. D.; LACRUZ, S. P.; HUETE, A.; FERREIRA, L.; YOSHIOKA, H. SANO, E. Avaliacao dos dados MODIS para o estudo da cobertura vegetal da Floresta Nacional Tapajos no estado do Para. In: SIMPOSIO BRASILEIRO DE SENSORIAMENTO REMOTO- SBSR, 10., 2001, Foz do Iguacu. [Anais...]. [S.l.]: SELPER: INPE, 2001? 4 p.| Biblioteca(s): Embrapa Cerrados. |
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| 17. | | POTTER, C.; KLOOSTER, S.; HUETE, A.; GENOVESE, V.; BUSTAMANTE, M.; FERREIRA, L. G.; OLIVEIRA JUNIOR, R. C. de; ZEPP, R. Terrestrial carbon sinks in the Brazilian Amazon and Cerrado region predicted from MODIS satellite data and ecosystem modeling. Biogeosciences discussions, v. 6, n. 1, p. 947-969, Jan./Feb. 2009.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 18. | | NELSON, B.; TAVARES, J.; WU, J.; VALERIANO, D.; LOPES, A.; MAROSTICA, S.; MARTINS, G.; PROHASKA, N.; ALBERT, L.; ARAUJO, A. de; MANZI, A.; SALESKA, S.; HUETE, A. Seasonality of Central Amazon Forest Leaf Flush Using Tower-Mounted RGB Camera. In: AGU FALL MEETING, 2014, San Francisco. [Proceedings]. [San Francisco]: AGU, 2014.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 19. | | WU, J.; KOBAYASHI, H.; STARK, S. C.; MENG, R.; GUAN, K.; TRAN, N. N.; GAO, S.; YANG, W.; RESTREPO-COUPE, N.; MIURA, T.; OLIVEIRA JUNIOR, R. C. de; ROGERS, A.; DYE, D. G.; NELSON, B. W.; SERBIN, S. P.; HUETE, A. R.; SALESKA, S. R. Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. New Phytologist, v. 217, n. 4, p. 1507-1520, Mar. 2018.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 20. | | WU, J.; GUAN, K.; HAYEK, M.; RESTREPO-COUPE, N.; WIEDEMANN, K. T.; XU, X.; WEHR, R.; CHRISTOFFERSEN, B. O.; MIAO, G.; SILVA, R. da; ARAUJO, A. C. de; OLIVEIRA JUNIOR, R. C. de; CAMARGO, P. B.; MONSON, R. K.; HUETE, A. R.; SALESKA, S. R. Partitioning controls on Amazon forest photosynthesis between environmental and biotic factors at hourly to interannual timescales. Global Change Biology, v. 23, n. 3, p. 1240-1257, Mar. 2017.| Biblioteca(s): Embrapa Amazônia Oriental. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
06/02/2018 |
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Data da última atualização: |
02/05/2018 |
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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: |
WU, J.; KOBAYASHI, H.; STARK, S. C.; MENG, R.; GUAN, K.; TRAN, N. N.; GAO, S.; YANG, W.; RESTREPO-COUPE, N.; MIURA, T.; OLIVEIRA JUNIOR, R. C. de; ROGERS, A.; DYE, D. G.; NELSON, B. W.; SERBIN, S. P.; HUETE, A. R.; SALESKA, S. R. |
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Afiliação: |
Jin Wu, University of Arizona / Brookhaven National Laboratory; Hideki Kobayashi, Japan Agency for Marine-Earth Science and Technology; Scott C. Stark, Michigan State University; Ran Meng, Brookhaven National Laboratory; Kaiyu Guan, University of Illinois at Urbana Champaign; Ngoc Nguyen Tran, University of Technology Sydney; Sicong Gao, University of Technology Sydney; Wei Yang, Chiba University; Natalia Restrepo-Coupe, University of Arizona; Tomoaki Miura, University of Havaii; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; Alistair Rogers, Brookhaven National Laboratory; Dennis G. Dye, Northern Arizona University; Bruce W. Nelson, INPA; Shawn P. Serbin, Brookhaven National Laboratory; Alfredo R. Huete, University of Technology Sydney; Scott R. Saleska, University of Arizona. |
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Título: |
Biological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
New Phytologist, v. 217, n. 4, p. 1507-1520, Mar. 2018. |
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DOI: |
10.1111/nph.14939 |
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Idioma: |
Inglês |
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Conteúdo: |
Satellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate?phenology relationships in the tropics. MenosSatellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite... Mostrar Tudo |
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Palavras-Chave: |
Sazonalidade. |
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Thesagro: |
Fenologia; Floresta tropical. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
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001 2087194
005 2018-05-02
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1111/nph.14939$2DOI
100 1 $aWU, J.
245 $aBiological processes dominate seasonality of remotely sensed canopy greenness in an Amazon evergreen forest.$h[electronic resource]
260 $c2018
520 $aSatellite observations of Amazon forests show seasonal and interannual variations, but the underlying biological processes remain debated. Here we combined radiative transfer models (RTMs) with field observations of Amazon forest leaf and canopy characteristics to test three hypotheses for satellite-observed canopy reflectance seasonality: seasonal changes in leaf area index, in canopy-surface leafless crown fraction and/or in leaf demography. Canopy RTMs (PROSAIL and FLiES), driven by these three factors combined, simulated satellite-observed seasonal patterns well, explaining c. 70% of the variability in a key reflectance-based vegetation index (MAIAC EVI, which removes artifacts that would otherwise arise from clouds/aerosols and sun?sensor geometry). Leaf area index, leafless crown fraction and leaf demography independently accounted for 1, 33 and 66% of FLiES-simulated EVI seasonality, respectively. These factors also strongly influenced modeled near-infrared (NIR) reflectance, explaining why both modeled and observed EVI, which is especially sensitive to NIR, captures canopy seasonal dynamics well. Our improved analysis of canopy-scale biophysics rules out satellite artifacts as significant causes of satellite-observed seasonal patterns at this site, implying that aggregated phenology explains the larger scale remotely observed patterns. This work significantly reconciles current controversies about satellite-detected Amazon phenology, and improves our use of satellite observations to study climate?phenology relationships in the tropics.
650 $aFenologia
650 $aFloresta tropical
653 $aSazonalidade
700 1 $aKOBAYASHI, H.
700 1 $aSTARK, S. C.
700 1 $aMENG, R.
700 1 $aGUAN, K.
700 1 $aTRAN, N. N.
700 1 $aGAO, S.
700 1 $aYANG, W.
700 1 $aRESTREPO-COUPE, N.
700 1 $aMIURA, T.
700 1 $aOLIVEIRA JUNIOR, R. C. de
700 1 $aROGERS, A.
700 1 $aDYE, D. G.
700 1 $aNELSON, B. W.
700 1 $aSERBIN, S. P.
700 1 $aHUETE, A. R.
700 1 $aSALESKA, S. R.
773 $tNew Phytologist$gv. 217, n. 4, p. 1507-1520, Mar. 2018.
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