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| 3. |  | TRABAQUINI, K.; SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; GALVÃO, L. S. Dynamics and distribution of anthropic occupation in the Cerrado of Mato Grosso in the period from 1990 to 2008. Geografia, Rio Claro, v. 38, n. 2, p. 209-224, maio/ago. 2013. p. 209-224| Biblioteca(s): Embrapa Territorial. |
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| 8. | | BALBINOT, R.; LAMBRECHT, F. R.; BREUNIG, F. M.; TRAUTENMÜLLER, J. W.; GALVÃO, L. S.; DENARDI, L.; VENDRUSCOLO, R. Análise fitossociológica de um fragmento de Floresta Estacional Decidual: Parque Estadual do Turvo, RS. Pesquisa Florestal Brasileira, Colombo, v. 36, n. 86, p. 103-113, abr./jun. 2016.| Biblioteca(s): Embrapa Florestas. |
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| 13. | | GALVAO, L. S.; PEREIRA FILHO, W.; ABDON, M. de M.; NOVO, E. M. L. de M.; SILVA, J. dos S. V. da. Sensoriamento remoto hiperespectral no estudo de baias e salinas no Pantanal brasileiro. In: CONGRESSO BRASILEIRO DE SENSORIAMENTO REMOTO, 11., Belo Horizonte, 2003. Anais... Belo Horizonte: SBSR / INPE, p.2493-2500, 2003.| Biblioteca(s): Embrapa Pantanal. |
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| 14. | | GALVÃO, L. S.; PEREIRA FILHO, W.; ABDON, M. de M.; NOVO, E. M. M. L.; SILVA, J. dos S. V. da; PONZONI, F. J. Hyperspectral remote sensing of the brazilian pantanal lakes. In: JPL AIRBORNE EARTH SCIENCE WORKSHOP, 11., 2002, Pasadena. Proceedings... Pasadena: NASA, 2002. p. 355-362. Na publicação: João S. V. da Silva.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 15. | | PAVANELLI, J. A. P.; MALDONADO, F. D.; SANTOS, J. R. dos; GALVÃO, L. S.; XAUD, M. R.; XAUD, H. A. M. Rotação radiométrica para detecção de mudanças na paisagem de tensão ecológica em Roraima. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015.| Biblioteca(s): Embrapa Roraima. |
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| 16. | | MOURA, Y. M. de; BALZTER, H.; GALVÃO, L. S.; DALAGNOL, R.; ESPÍRITO-SANTO, F.; SANTOS, E. G.; GARCIA, M.; BISPO, P. da C.; OLIVEIRA JUNIOR, R. C. de; SHIMABUKURO, Y. E. Carbon dynamics in a human-modified tropical forest: a case study using multi-temporal LiDAR Data. Remote Sensing, v. 12, n. 3, Article 430, 2020.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 17. | | MOURA, Y. M. de; GALVÃO, L. S.; HILKER, T.; WU, J.; SALESKA, S.; AMARAL, C. H. do; NELSON, B. W.; LOPES, A. P.; WIEDEMAN, K. K.; PROHASKA, N.; OLIVEIRA JUNIOR, R. C. de; MACHADO, C. B.; ARAGÃO, L. E. O. C. Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations. ISPRS Journal of Photogrammetry and Remote Sensing, v. 131, p. 52-64, Sept. 2017.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 18. | | HILKER, T.; GALVÃO, L. S.; ARAGÃO, L. E. O. C.; MOURA, Y. M. de; AMARAL, C. H. do; LYAPUSTIN, A. I.; WU, J.; ALBERT, L. P.; FERREIRA, M. J.; ANDERSON, L. O.; SANTOS, V. A. H. F. dos; PROHASKA, N.; TRIBUZY, E.; CERON, J. V. B.; SALESKA, S. R.; WANG, Y.; GONÇALVES, J. F. de C.; OLIVEIRA JUNIOR, R. C. de; RODRIGUES, J. V. F. C.; GARCIA, M. N. Vegetation chlorophyll estimates in the Amazon from multi-angle MODIS observations and canopy reflectance model. International Journal of Applied Earth Observation and Geoinformation, v. 58, p. 278-287, June 2017.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 19. | | BISPO, P. da C.; PICOLI, M. C. A.; MARIMON, B. S.; MARIMON JUNIOR, B. H.; PERES, C. A.; MENOR, I. O.; SILVA, D. E.; MACHADO, F. de F.; ALENCAR, A. A. C.; ALMEIDA, C. A. de; ANDERSON, L. O.; ARAGÃO, L. E. O. C.; BREUNIG, F. M.; BUSTAMANTE, M.; DALAGNOL, R.; DINIZ-FILHO, J. A. F.; FERREIRA, L. G.; FISCH, G.; GALVÃO, L. S.; GIAROLLA, A.; GOMES, A. R.; MARCO JUNIOR, P. de; KUCK, T. N.; LEHMANN, C. E. R.; LEMES, M. R.; TRIVISAN, D. P.; ZIMBRES, B.; WIEDERKEHR, N. C.; SILVA-JUNIOR, C. H. L. Overlooking vegetation loss outside forests imperils the Brazilian Cerrado and other non-forest biomes. Nature Ecology & Evolution, v. 8, p. 12-13 Jan. 2024.| Biblioteca(s): Embrapa Cerrados. |
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| Registros recuperados : 19 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
13/10/2017 |
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Data da última atualização: |
22/12/2021 |
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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: |
MOURA, Y. M. de; GALVÃO, L. S.; HILKER, T.; WU, J.; SALESKA, S.; AMARAL, C. H. do; NELSON, B. W.; LOPES, A. P.; WIEDEMAN, K. K.; PROHASKA, N.; OLIVEIRA JUNIOR, R. C. de; MACHADO, C. B.; ARAGÃO, L. E. O. C. |
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Afiliação: |
Yhasmin Mendes de Moura, INPE; Lênio Soares Galvão, INPE; Thomas Hilker, University of Southampton; Jin Wu, University of Arizona / Brookhaven National Laboratory; Scott Saleska, University of Arizona; Cibele Hummel do Amaral, UFV; Bruce Walker Nelson, INPA; Aline Pontes Lopes, INPE; Kenia K. Wiedeman, University of Arizona / Harvard University; Neill Prohaska, University of Arizona; RAIMUNDO COSME DE OLIVEIRA JUNIOR, CPATU; Carolyne Bueno Machado, INPE; Luiz E. O. C. Aragão, INPE / University of Exeter. |
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Título: |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
ISPRS Journal of Photogrammetry and Remote Sensing, v. 131, p. 52-64, Sept. 2017. |
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DOI: |
https://doi.org/10.1016/j.isprsjprs.2017.07.006 |
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Idioma: |
Inglês |
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Conteúdo: |
The association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index.Weinspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced theSMAshade fraction over time.WhenMODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3?5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. While the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing. MenosThe association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index.Weinspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Ma... Mostrar Tudo |
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Palavras-Chave: |
Espécie florestal; Sazonalidade. |
|
Thesagro: |
Fenologia; Folha; Seca. |
|
Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
LEADER 03841naa a2200337 a 4500
001 2077368
005 2021-12-22
008 2017 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.isprsjprs.2017.07.006$2DOI
100 1 $aMOURA, Y. M. de
245 $aSpectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations.$h[electronic resource]
260 $c2017
520 $aThe association between spectral reflectance and canopy processes remains challenging for quantifying large-scale canopy phenological cycles in tropical forests. In this study, we used a tower-mounted hyperspectral camera in an eastern Amazon forest to assess how canopy spectral signals of three species are linked with phenological processes in the 2012 dry season. We explored different approaches to disentangle the spectral components of canopy phenology processes and analyze their variations over time using 17 images acquired by the camera. The methods included linear spectral mixture analysis (SMA); principal component analysis (PCA); continuum removal (CR); and first-order derivative analysis. In addition, three vegetation indices potentially sensitive to leaf flushing, leaf loss and leaf area index (LAI) were calculated: the Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and the entitled Green-Red Normalized Difference (GRND) index.Weinspected also the consistency of the camera observations using Moderate Resolution Imaging Spectroradiometer (MODIS) and available phenological data on new leaf production and LAI of young, mature and old leaves simulated by a leaf demography-ontogeny model. The results showed a diversity of phenological responses during the 2012 dry season with related changes in canopy structure and greenness values. Because of the differences in timing and intensity of leaf flushing and leaf shedding, Erisma uncinatum, Manilkara huberi and Chamaecrista xinguensis presented different green vegetation (GV) and non-photosynthetic vegetation (NPV) SMA fractions; distinct PCA scores; changes in depth, width and area of the 681-nm chlorophyll absorption band; and variations over time in the EVI, GRND and NDVI. At the end of dry season, GV increased for Erisma uncinatum, while NPV increased for Chamaecrista xinguensis. For Manilkara huberi, the NPV first increased in the beginning of August and then decreased toward September with new foliage. Variations in red-edge position were not statistically significant between the species and across dates at the 95% confidence level. The camera data were affected by view-illumination effects, which reduced theSMAshade fraction over time.WhenMODIS data were corrected for these effects using the Multi-Angle Implementation of Atmospheric Correction Algorithm (MAIAC), we observed an EVI increase toward September that closely tracked the modeled LAI of mature leaves (3?5 months). Compared to the EVI, the GRND was a better indicator of leaf flushing because the modeled production of new leaves peaked in August and then declined in September following the GRND closely. While the EVI was more related to changes in mature leaf area, the GRND was more associated with new leaf flushing.
650 $aFenologia
650 $aFolha
650 $aSeca
653 $aEspécie florestal
653 $aSazonalidade
700 1 $aGALVÃO, L. S.
700 1 $aHILKER, T.
700 1 $aWU, J.
700 1 $aSALESKA, S.
700 1 $aAMARAL, C. H. do
700 1 $aNELSON, B. W.
700 1 $aLOPES, A. P.
700 1 $aWIEDEMAN, K. K.
700 1 $aPROHASKA, N.
700 1 $aOLIVEIRA JUNIOR, R. C. de
700 1 $aMACHADO, C. B.
700 1 $aARAGÃO, L. E. O. C.
773 $tISPRS Journal of Photogrammetry and Remote Sensing$gv. 131, p. 52-64, Sept. 2017.
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