@InProceedings{SatoShimKupl:2011:UsAnCo,
               author = "Sato, Luciane Yumie and Shimabukuro, Yosio Edemir and Kuplich, 
                         Tatiana Mora",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais - INPE} and {Instituto 
                         Nacional de Pesquisas Espaciais - INPE} and {Centro Regional Sul 
                         de Pesquisas Espaciais - CRS/ INPE}",
                title = "Uso da an{\'a}lise por componentes principais na 
                         avalia{\c{c}}{\~a}o da mudan{\c{c}}a da cobertura florestal da 
                         Floresta Nacional do Tapaj{\'o}s",
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "6696--6702",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 15. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "linear spectral mixing model, vegetation fraction image, image 
                         processing, modelo linear de mistura espectral, 
                         imagem-fra{\c{c}}{\~a}o vegeta{\c{c}}{\~a}o, processamento de 
                         imagens.",
             abstract = "Remote Sensing has been an efficient way to mapping and monitoring 
                         large extensions of land surface. Among different remote sensing 
                         techniques, the Principal Component Analysis (PCA) allows tracking 
                         land use and land cover changes with multispectral and 
                         multitemporal data. This study aims to evaluate, through the PCA, 
                         the changes occurred between the years 2005 and 2010 in the land 
                         cover of the area that encompasses the northern part of 
                         Tapaj{\'o}s National Forest (Par{\'a} state). The input data for 
                         the PCA is the vegetation fraction images resulting from the 
                         application of Linear Spectral Mixing Model using Landsat Thematic 
                         Mapper (TM) data. As a result, this work shows a map of land cover 
                         changes that allows to observe the regions with higher or lower 
                         temporal variation on the forest cover. Water surfaces and dense 
                         forest were the classes that remained more stable over the years, 
                         with low variation. Regions that have undergone anthropic process 
                         showed higher variation. Despite the high variability, these 
                         regions represent only 5% of the scene, regions with median 
                         variation represent 10% and with low variation are 85%. It was 
                         found that using the PCA is possible to analyze the spatial 
                         distribution of temporal variation in forest cover in the scene 
                         under study. However, due to the presence of clouds in some areas, 
                         the map shows variations that do not correspond to real changes in 
                         vegetation cover, indicating the need to use images without cloud 
                         cover.",
  conference-location = "Curitiba",
      conference-year = "30 abr. - 5 maio 2011",
                 isbn = "{978-85-17-00056-0 (Internet)} and {978-85-17-00057-7 (DVD)}",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW/3A6HNN8",
                  url = "http://urlib.net/ibi/3ERPFQRTRW/3A6HNN8",
           targetfile = "p0565.pdf",
                 type = "Uso e Cobertura da Terra",
        urlaccessdate = "16 jun. 2024"
}