author = "Kuplich, Tatiana Mora and Costa, Luis Fernando Flenik and Capoane, 
                         Viviane and Barbieri, Andreus",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Primeira aproxima{\c{c}}{\~a}o dos Tipos Funcionais de 
                         Vegeta{\c{c}}{\~a}o do Rio Grande do Sul",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2168--2175",
         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 = "Time series of vegetation indices describe the temporal and 
                         spatial path of primary productivity or biomass, allowing its 
                         characterization and mapping according to functional types of 
                         vegetation, which might be monitored in face of climate change. 
                         This work aims to generate products from an annual series of 
                         EVI/MODIS on a first approximation of Functional Types of 
                         vegetation (TFV) for the state of Rio Grande do Sul. The Google 
                         Earth Engine (GEE) platform facilitated obtaining and processing a 
                         large volume of remote sensing data, motivating the accomplishment 
                         of this work. The products generated from a 2014 EVI series were: 
                         the Integral (representing the annual primary productivity), the 
                         Range (range of EVI, representing the seasonality in the year 
                         considered) and date of Maximum EVI or maximum vegetative vigor. 
                         These products were classified by density slicing (based on the 
                         histogram) and integrated via map algebra (with decreasing weights 
                         to integral, range and maximum), resulting in 42 classes. Those 
                         were subsequently grouped into 11 TFV, with 4 predominant classes 
                         in terms of spatial coverage. The different TFV found, expressing 
                         the dynamics of productivity, are dependent on several factors 
                         besides the phenology characteristic of each individual or group. 
                         The climate is an important abiotic factor for the TFV, but also 
                         topography, soils and their degradation, and land use dynamics. 
                         The ability to identify phenological patterns and the reasons for 
                         changes in these patterns will make possible the assessment and 
                         prediction of effects of global climatic changes in ecosystems.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59872",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSLQ56",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3PSLQ56",
           targetfile = "59872.pdf",
                 type = "Paisagens naturais",
        urlaccessdate = "30 nov. 2020"