@InProceedings{CarvalhoJúniorSilv:2007:DeMuEs,
               author = "Carvalho J{\'u}nior, Osmar Ab{\'{\i}}lio de and Silva, Nilton 
                         Correia da",
          affiliation = "{Universidade de Bras{\'{\i}}lia (UnB). Departamento de 
                         Geografia.} and {Centro Universit{\'a}rio de An{\'a}polis 
                         (Unievang{\'e}lica). Departamento de Sistemas de 
                         Informa{\c{c}}{\~a}o.}",
                title = "Detec{\c{c}}{\~a}o de mudan{\c{c}}a espectral uma nova 
                         metodologia para an{\'a}lise de s{\'e}ries temporais",
            booktitle = "Anais...",
                 year = "2007",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares and Fonseca, Leila Maria Garcia",
                pages = "5635--5641",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 13. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "change detection, spectral classification, digital image 
                         processing, detec{\c{c}}{\~a}o de mudan{\c{c}}a, 
                         classifica{\c{c}}{\~a}o espectral, processamento digital de 
                         imagem.",
             abstract = "Digital change detection is the computerized process of 
                         identifying changes in the state of an object, or other 
                         earthsurface features, between different dates. During the last 
                         years, a large number of change detection methods have evolved 
                         that differ widely in refinement, robustness and complexity. This 
                         study aims to develop one program to detect and delineate 
                         landscape changes automatically over multiple scales using a 
                         formulation of spectral classifiers. The procedure calculates for 
                         each pixel the SAM, SCM or Euclidian distance value between the 
                         spectra at time, t1 and t2. Considering a high threshold value is 
                         possible to define point with the same spectral behavior and 
                         probably without alteration during the period. In particular, this 
                         method approach allows the automatic identification of the 
                         invariants points to calibrate remote-sensing images, without 
                         visual interpretation data. Users program establish the spectral 
                         change detection (SCD) method (SAM-SCD, SCM- SCD and Euclidian 
                         Distance-SCD). Thus, the program allows working simultaneously 
                         with the collection of the temporal images. This realization is an 
                         important task in landscape analysis and remote sensing.",
  conference-location = "Florian{\'o}polis",
      conference-year = "21-26 abr. 2007",
                 isbn = "978-85-17-00031-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2006/11.24.14.04",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2006/11.24.14.04",
           targetfile = "5635-5641.pdf",
                 type = "Processamento de Dados e de Imagens",
        urlaccessdate = "15 jun. 2024"
}