@InProceedings{PinheiroEsca:2013:DeClPa,
               author = "Pinheiro, Taise Farias and Escada, Maria Isabel Sobral",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Detec{\c{c}}{\~a}o e Classifica{\c{c}}{\~a}o de padr{\~o}es 
                         da Degrada{\c{c}}{\~a}o Florestal na Amaz{\^o}nia por meio de 
                         banco de dados celular",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "3397--3404",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Forest degradation is a threat looms over Amazon forest. Detection 
                         and Recognition of Forest Degradation patterns are important to 
                         address forest state. This study presents the asset of application 
                         of a novel free system for spatial data mining, called GeoDMA, for 
                         distinguishing patterns in forest degradation in Brazilian Amazon. 
                         Types were related to progressive events of decreasing forest 
                         canopy. An analysis of land cover dynamic, from satellite image 
                         time series, is also showed. Method was based on cell database 
                         construction, landscape metrics and data mining techniques. 
                         Cell-based classification, provided by GeoDMA, proved to be useful 
                         in distinguishing forest degradation patterns. Errors were mostly 
                         caused by spatial and spectral resolution constraints of Landsat 
                         images (30m) than to the rules used to perform classification. 
                         Cell data base construction with resolution of 1km2 was suitable 
                         to represent forest degradation typologies. However, we recommend 
                         future studies to test finer resolution. Time analyses interval of 
                         three years between series data was not appropriate to represent 
                         land cover dynamics. Fast transition between forest and clear-cut 
                         requires analysis at annual-basis to better determine and detect 
                         forest degradation and their trajectories. Patterns have found to 
                         S{\~a}o F{\'e}lix do Xingu may not be enough to represent all 
                         the patterns one can distinguish in Amazon region.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "1439",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GLBN",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GLBN",
           targetfile = "p1439.pdf",
                 type = "Floresta e Vegeta{\c{c}}{\~a}o",
        urlaccessdate = "03 maio 2024"
}