Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.1016/j.isprsjprs.2017.07.006 http://www.locus.ufv.br/handle/123456789/22065 |
Resumo: | 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. We inspected 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 the SMA shade fraction over time. When MODIS 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. |
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Amaral, Cibele Hummel doMoura, Yhasmin Mendes deGalvão, Lênio SoaresHilker, ThomasWu, JinSaleska, ScottNelson, Bruce WalkerLopes, Aline PontesWiedeman, Kenia K.Prohaska, NeillOliveira, Raimundo Cosme deMachado, Carolyne BuenoAragão, Luiz E. O. C.2018-09-28T12:02:24Z2018-09-28T12:02:24Z2017-09-010924-2716https://doi.org/10.1016/j.isprsjprs.2017.07.006http://www.locus.ufv.br/handle/123456789/22065The 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. We inspected 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 the SMA shade fraction over time. When MODIS 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.engISPRS Journal of Photogrammetry and Remote SensingVolume 131, Pages 52-64, September 2017Elsevier B. V.info:eu-repo/semantics/openAccessPhenologyHyperspectral remote sensingTropical speciesLeaf flushAmazonSeasonalityDry seasonSpectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observationsinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf4714239https://locus.ufv.br//bitstream/123456789/22065/1/artigo.pdfebc4c6b38517c8d87cac8622610935b8MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/22065/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg5060https://locus.ufv.br//bitstream/123456789/22065/3/artigo.pdf.jpgff94694ea51ab9b419ed25e37a4786c9MD53123456789/220652018-09-28 23:00:33.93oai:locus.ufv.br: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Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-09-29T02:00:33LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
title |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
spellingShingle |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations Amaral, Cibele Hummel do Phenology Hyperspectral remote sensing Tropical species Leaf flush Amazon Seasonality Dry season |
title_short |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
title_full |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
title_fullStr |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
title_full_unstemmed |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
title_sort |
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations |
author |
Amaral, Cibele Hummel do |
author_facet |
Amaral, Cibele Hummel do Moura, Yhasmin Mendes de Galvão, Lênio Soares Hilker, Thomas Wu, Jin Saleska, Scott Nelson, Bruce Walker Lopes, Aline Pontes Wiedeman, Kenia K. Prohaska, Neill Oliveira, Raimundo Cosme de Machado, Carolyne Bueno Aragão, Luiz E. O. C. |
author_role |
author |
author2 |
Moura, Yhasmin Mendes de Galvão, Lênio Soares Hilker, Thomas Wu, Jin Saleska, Scott Nelson, Bruce Walker Lopes, Aline Pontes Wiedeman, Kenia K. Prohaska, Neill Oliveira, Raimundo Cosme de Machado, Carolyne Bueno Aragão, Luiz E. O. C. |
author2_role |
author author author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Amaral, Cibele Hummel do Moura, Yhasmin Mendes de Galvão, Lênio Soares Hilker, Thomas Wu, Jin Saleska, Scott Nelson, Bruce Walker Lopes, Aline Pontes Wiedeman, Kenia K. Prohaska, Neill Oliveira, Raimundo Cosme de Machado, Carolyne Bueno Aragão, Luiz E. O. C. |
dc.subject.pt-BR.fl_str_mv |
Phenology Hyperspectral remote sensing Tropical species Leaf flush Amazon Seasonality Dry season |
topic |
Phenology Hyperspectral remote sensing Tropical species Leaf flush Amazon Seasonality Dry season |
description |
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. We inspected 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 the SMA shade fraction over time. When MODIS 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. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017-09-01 |
dc.date.accessioned.fl_str_mv |
2018-09-28T12:02:24Z |
dc.date.available.fl_str_mv |
2018-09-28T12:02:24Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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dc.identifier.uri.fl_str_mv |
https://doi.org/10.1016/j.isprsjprs.2017.07.006 http://www.locus.ufv.br/handle/123456789/22065 |
dc.identifier.issn.none.fl_str_mv |
0924-2716 |
identifier_str_mv |
0924-2716 |
url |
https://doi.org/10.1016/j.isprsjprs.2017.07.006 http://www.locus.ufv.br/handle/123456789/22065 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 131, Pages 52-64, September 2017 |
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Elsevier B. V. info:eu-repo/semantics/openAccess |
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Elsevier B. V. |
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openAccess |
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ISPRS Journal of Photogrammetry and Remote Sensing |
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ISPRS Journal of Photogrammetry and Remote Sensing |
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