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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Consistency of vegetation index seasonality across the Amazon rainforest

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Autor(es):
Maeda, Eduardo Eiji ; Moura, Yhasmin Mendes ; Wagner, Fabien ; Hilker, Thomas ; Lyapustin, Alexei I. ; Wang, Yujie ; Chave, Jerome ; Mottus, Matti ; Aragao, Luiz E. O. C. ; Shimabukuro, Yosio
Número total de Autores: 10
Tipo de documento: Artigo Científico
Fonte: International Journal of Applied Earth Observation and Geoinformation; v. 52, p. 42-53, OCT 2016.
Citações Web of Science: 11
Resumo

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in Vis seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between Vls, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing. (C) 2016 Elsevier B.V. All rights reserved. (AU)

Processo FAPESP: 13/14520-6 - Quantificação e modelagem da sazonalidade da produção primária líquida florestal pantropical usando observações de campo e dados de sensoriamento remoto
Beneficiário:Fabien Hubert Wagner
Linha de fomento: Bolsas no Brasil - Pós-Doutorado