@Article{MaedaHeisAragRinn:2014:CaMOEV,
author = "Maeda, Eduardo Eiji and Heiskanen, Janne and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de and Rinne, Janne",
affiliation = "{} and {} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Can MODIS EVI monitor ecosystem productivity in the Amazon
rainforest?",
journal = "Geophysical Research Letters",
year = "2014",
volume = "41",
number = "20",
pages = "7176–7183",
keywords = "EVI, MODIS, Amazon, phenology, anomalies.",
abstract = "The enhanced vegetation index (EVI) obtained from satellite
imagery has often been used as a proxy of vegetation functioning
and productivity in the Amazon rainforest. However, recent studies
indicate that EVI patterns are strongly affected by satellite data
artifacts. Hence, it is unclear if EVI is sensitive to subtle
seasonal variations in evergreen Amazon forest productivity. This
study analyzes 12\ years of Moderate Resolution Imaging
Spectroradiometer (MODIS) EVI in order to evaluate its response to
factors driving productivity in the Amazon. We show that, after
removing cloud and aerosol contamination, and correcting
bidirectional reflectance distribution function effects, radiation
and rainfall extremes show no influence on EVI anomalies. However,
EVI seasonal patterns are still evident after accounting for
Sun-sensor geometry effects. This remaining pattern cannot be
explained by solar radiation or rainfall, but it is significantly
correlated to gross primary production (GPP). Nevertheless, we
argue that the causality between GPP and EVI should be interpreted
with caution.",
doi = "10.1002/2014GL061535",
url = "http://dx.doi.org/10.1002/2014GL061535",
issn = "0094-8276",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "Maeda2014_MODIS_Productivity_Amazon_GRL.pdf",
urlaccessdate = "04 maio 2024"
}