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 
              journal = "Geophysical Research Letters",
                 year = "2014",
               volume = "41",
               number = "20",
                pages = "71767183",
             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 = "26 nov. 2020"