@InProceedings{PaloschiMuleBorm:2017:VaAnDi,
               author = "Paloschi, Rennan Andres and Muler, Ranieli dos Anjos de Souza and 
                         Borma, Laura de Simone",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Vari{\'a}veis para an{\'a}lises de din{\^a}micas sazonais da 
                         Floresta Amaz{\^o}nica",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2740--2745",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Large tropical forests like the Amazon, important in carbon and 
                         water cycling, constantly are targets for climate change research 
                         and studies on the seasonality of the vegetation that seek to 
                         correlate the various types of data in order to develop 
                         theoretical models, obtain projections or thresholds for different 
                         phenomena, vegetation mechanisms, climate feedback from changes in 
                         forest behavior and possible relationships with global climate 
                         change, however, all currently used techniques have limitations 
                         that may hinder complex analysis. Data obtained locally are 
                         generally known as field truth, but imply high costs and therefore 
                         are not performed on a large scale. As far as the data obtained by 
                         remote orbital sensors are concerned, the limitations generally 
                         lie in the temporal and spatial scales covered by the sensors, in 
                         the interferences and noise of the signal received by the sensor 
                         and also in its ability to indicate, with relative fidelity, 
                         processes of operation of the terrestrial system occurring in 
                         situ. This study aimed to identify and assess the main variables 
                         used in the study of seasonal dynamics of the Amazon rainforest. 
                         The variables identified were the vegetation indices NDVI and EVI, 
                         the Gross Primary Productivity (GPP), the Solar-Induced 
                         Fluorescence (SIF) and the Evapotranspiration.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60122",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLR6P",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSLR6P",
           targetfile = "60122.pdf",
                 type = "Monitoramento e modelagem ambiental",
        urlaccessdate = "27 abr. 2024"
}