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Original Articles

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

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Pages 387-408 | Received 07 Feb 2008, Accepted 04 Nov 2009, Published online: 06 Feb 2011
 

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 of MODIS 250-m data over three contrasting land cover types in the Amazon were used in conjunction with rainfall data, a land cover map 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 a more comprehensive exploration of the spectral and structural changes in vegetation formations.

Acknowledgments

The first author would like to thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for the PhD studentship (BEX4018052) and BECA/IEB (BECA-B/2006/01/BDE/04) for financial support. We thank Dr Dalton M. Valeriano and Dr Sassan Saatchi for thoughtful discussions. Data for this study were provided by the Land Processes Distributed Active Archive Center (LP-DAAC) and Agência Nacional de Águas (ANA), information freely available in the World Wide Web at http://edcdaac.usgs.gov and http://ana.gov.br, respectively. The authors would like to thanks the two anonymous reviewers for their comments and suggestions that immensely contributed to improving the manuscript.

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