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@InProceedings{BecerraCarvOmet:2015:AbMu,
               author = "Becerra, Jorge Alberto Bustamante and Carvalho, Suzana de and 
                         Ometto, Jean Balbaud",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Rela{\c{c}}{\~a}o das sazonalidades da precipita{\c{c}}{\~a}o 
                         e da vegeta{\c{c}}{\~a}o no bioma Caatinga: abordagem 
                         multitemporal",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6668--6674",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Precipitation is one of the most important climatic variables in 
                         the Caatinga biome that influences the spatial and temporal 
                         distribution pattern of its vegetation types. These types in turn 
                         influence the regional climate from the feedback mechanism of 
                         energy flows, water and momentum. This climate-vegetation 
                         interaction in the Caatinga is differentiated depending on the 
                         type of climate pattern in the region. This study aims to find out 
                         how the annual precipitation pattern influence the vegetation 
                         seasonality by the identification of the main phenological 
                         features of the vegetation annual growth cycles and the annual 
                         rainfall features in a gradient of five climatic regions in the 
                         Caatinga biome. We use time series (2001-2008) of vegetation 
                         indices such as NDVI and LSWI, and precipitation that was derived 
                         of TRMM satellite data and surface station data. The results 
                         indicate that precipitation variability in the rainy season 
                         influences directly the variability of vegetation growing cycles. 
                         That influence is not linear, but adjusted to a logarithmic 
                         function being precipitation better fit with LSWI (r2 = 0.67) than 
                         NDVI (r2 = 0.54). The influence of precipitation on Caatinga 
                         vegetation, using phenological metrics such as start, end, peak 
                         and length of the vegetation growing cycles, showed greater lag in 
                         climatic regions with higher precipitation while in regions with 
                         lower precipitation this lag was slight.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "1454",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4J65",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM4J65",
           targetfile = "p1454.pdf",
                 type = "An{\'a}lise de s{\'e}ries de tempo de imagens de sat{\'e}lite",
        urlaccessdate = "29 nov. 2020"
}


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