@InProceedings{VellosoSaSoGlAmOl:2017:DiReFl,
               author = "Velloso, Sidney Geraldo Silveira and Santos, Jo{\~a}o Fl{\'a}vio 
                         Costa dos and Souza, Guilherme Silverio Aquino de and Gleriani, 
                         Jos{\'e} Marinaldo and Amaral, Cibele Hummel do and Oliveira, 
                         Julio Cesar de",
                title = "Din{\^a}mica da regenera{\c{c}}{\~a}o florestal em ambiente de 
                         floresta Atl{\^a}ntica e sua modelagem por redes neurais",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6535--6542",
         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 brazilian Atlantic rainforest is the third largest biome among 
                         those that cover the country. Given its characteristics of high 
                         anthropic pressure and high endemism of vegetal and animal 
                         species, the biome was classified as a mundial hotspot. Thus, 
                         actions for conservation and restauration of its forests have been 
                         proposed. Between these actions, there is the forest natural 
                         regeneration. Given the current socioeconomics aspects of the 
                         rural population, many pastures are being abandoned, which allows 
                         the natural regenerations establishment. The objectives of this 
                         work were to analyze the landscape dynamics through orbital images 
                         in an area of Atlantic forest and to predict the natural 
                         regeneration through neural network modeling. Images from the 
                         TM/Landsat-5 and OLI/Landsat-8 sensors were acquired and the 
                         visual interpretation allowed the thematic extraction of classes 
                         for the analysis of the dynamics of the forest natural 
                         regeneration. It was observed that the forest regeneration were 
                         mainly found in South facing aspects, because they have an more 
                         suitable envinronment for the establishment of the secondary 
                         succession. The results for the network modeling werent 
                         satisfactory, where only 32% of the regeneration were correctly 
                         predict.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59588",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMD4N",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMD4N",
           targetfile = "59588.pdf",
                 type = "Monitoramento e modelagem ambiental",
        urlaccessdate = "27 abr. 2024"
}