Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia

Anderson, LO; Aragão, LOC; Shimabukuro, YE; Almeida, S; Huete, A

Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia

Anderson, LO Aragão, LOC Shimabukuro, YE Almeida, S Huete, A

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Publication Type:: Journal Article
Citation:: International Journal of Remote Sensing, 2011, 32 (2), pp. 387 - 408
Issue Date:: 2011-01-01

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Field	Value	Language
dc.contributor.author	Anderson, LO	en_US
dc.contributor.author	Aragão, LOC	en_US
dc.contributor.author	Shimabukuro, YE	en_US
dc.contributor.author	Almeida, S	en_US
dc.contributor.author	Huete, A https://orcid.org/0000-0003-2809-2376	en_US
dc.date.issued	2011-01-01	en_US
dc.identifier.citation	International Journal of Remote Sensing, 2011, 32 (2), pp. 387 - 408	en_US
dc.identifier.issn	0143-1161	en_US
dc.identifier.uri	http://hdl.handle.net/10453/18174
dc.description.abstract	In this study we investigate the potential of fraction images derived from a linear spectral mixture model to detect vegetation phenology in Amazonia, and evaluate their relationships with the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices. Time series ofMODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land covermap and a forest inventory survey to support the interpretation of our findings. Each vegetation physiognomy was characterized by a particular intra-annual variability detected by a combination of the fraction images. Both vegetation and shade fractions were important to evaluate the seasonality of the open tropical forest (OTF). The association of these results with forest inventory data and the literature suggests that Enhanced Vegetation Index (EVI) and vegetation fraction images are sensitive to structural changes in the canopy of OTF. In cerrado grassland (CG) the phenology was better characterized by combined soil and vegetation fractions. Soybean (SB) areas were characterized by the highest ranges in the vegetation and soil fraction images. Vegetation fraction and vegetation indices for the OTF showed a significant positive relationship with EVI but not with Normalized Difference Vegetation Index (NDVI). Significant relationships for vegetation fraction and vegetation indices were also found for the CG and soybean areas. In contrast to vegetation index approaches to monitoring phenology, fraction images provide additional information that allows amore comprehensive exploration of the spectral and structural changes in vegetation formations. © 2011 Taylor & Francis.	en_US
dc.relation.ispartof	International Journal of Remote Sensing	en_US
dc.relation.isbasedon	10.1080/01431160903474921	en_US
dc.subject.classification	Geological & Geomatics Engineering	en_US
dc.title	Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	32	en_US
utslib.for	0607 Plant Biology	en_US
utslib.for	0406 Physical Geography and Environmental Geoscience	en_US
utslib.for	0909 Geomatic Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Life Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - CAMGIS - Centre for Advanced Modelling and Geospatial lnformation Systems
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	32	en_US

Abstract:

In this study we investigate the potential of fraction images derived from a linear spectral mixture model to detect vegetation phenology in Amazonia, and evaluate their relationships with the Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indices. Time series ofMODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land covermap and a forest inventory survey to support the interpretation of our findings. Each vegetation physiognomy was characterized by a particular intra-annual variability detected by a combination of the fraction images. Both vegetation and shade fractions were important to evaluate the seasonality of the open tropical forest (OTF). The association of these results with forest inventory data and the literature suggests that Enhanced Vegetation Index (EVI) and vegetation fraction images are sensitive to structural changes in the canopy of OTF. In cerrado grassland (CG) the phenology was better characterized by combined soil and vegetation fractions. Soybean (SB) areas were characterized by the highest ranges in the vegetation and soil fraction images. Vegetation fraction and vegetation indices for the OTF showed a significant positive relationship with EVI but not with Normalized Difference Vegetation Index (NDVI). Significant relationships for vegetation fraction and vegetation indices were also found for the CG and soybean areas. In contrast to vegetation index approaches to monitoring phenology, fraction images provide additional information that allows amore comprehensive exploration of the spectral and structural changes in vegetation formations. © 2011 Taylor & Francis.

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http://hdl.handle.net/10453/18174