@InProceedings{ViannaCarvSilvLemo:2017:VaSaND,
               author = "Vianna, Luana Menezes and Carvalho, Rita de C{\'a}ssia Freire and 
                         Silva, Mateus Tin{\^o}co and Lemos, Odair Lacerda",
                title = "Varia{\c{c}}{\~a}o sazonal do NDVI das tr{\^e}s fitofisionomias 
                         do munic{\'{\i}}pio de Boa Nova ? Ba",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6075--6080",
         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 = "The main objective of this study was to assess the NDVIs seasonal 
                         variation that took place among the vegetation groups in the 
                         municipality of Boa Nova BA, located in the southwest part of 
                         Bahia. Remote sensing is the practice of attaining land surfaces 
                         images with no contact between the detector and the object. NDVI 
                         is a remote sensing technique widely used in vegetation 
                         assessments, because its an index that emphasizes variations in 
                         land covers density. In this study the Normalized Difference 
                         Vegetation Index (NDVI) was calculated with Landsat 8 images in 
                         the dry season (06/16/2016) and the wet season (02/10/2016). The 
                         studied area is a transition zone between two biomes, Atlantic 
                         Forest and Caatinga and present three types of vegetation: 
                         caatinga, seasonal deciduous forest and ombrophilous dense forest. 
                         The images were processed in a GIS software (ArcGis 10.3). The 
                         results show that in the wet season, its not possible to 
                         distinguish the formations, and higher index were more common. In 
                         the dry season, it is possible to distinguish the different 
                         formations. In the ombrophilous dense forest, there were not big 
                         differences in the seasons, showing low correlation between NDVI 
                         and precipitation rates. In caatinga and seasonal deciduous forest 
                         seasonal, the low NDVI during the dry season was common in most 
                         areas this can be explained by the presence of deciduous 
                         vegetation and/or dry pasture.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59774",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMC96",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMC96",
           targetfile = "59774.pdf",
                 type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
        urlaccessdate = "27 abr. 2024"
}