@Article{SilvaForShiAdaSan:2010:DiCoVe,
               author = "Silva, Gustavo Bayma Siqueira da and Formaggio, Antonio Roberto 
                         and Shimabukuro, Yosio Edemir and Adami, Marcos and Sano, Edson",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and Embrapa Cerrados, BR-73310970 Planaltina, DF 
                         Brazil",
                title = "Discrimina{\c{c}}{\~a}o da cobertura vegetal do Cerrado 
                         matogrossense por meio de imagens MODIS/Discrimination of Cerrado 
                         vegetation cover in the state of Mato Grosso using MODIS images",
              journal = "Pesquisa Agropecuaria",
                 year = "2010",
               volume = "45",
               number = "2",
                pages = "186--194",
                month = "Feb.",
             keywords = "Agriculture, Sensoriamento Remoto, Modelo linear de mistura 
                         espectral, An{\'a}lise multi-temporal, linear spectral mixture 
                         model, temporal analysis, brazilian cerrado, tropical savanna, 
                         mixing models, classification, dynamics, areas, biome.",
             abstract = "The objective of the present work was to evaluate the potential of 
                         the spectral linear mixture model (SLMM), applied to Moderate 
                         Resolution Imaging Spectroradiometer (MODIS) images, to 
                         discriminate natural and anthropic classes of vegetation in the 
                         portion of Mato Grosso state covered by Cerrado vegetation. The 
                         monitoring of the Cerrado biome is becoming very important due to 
                         its strong human disturbance, especially in the last four decades. 
                         In this context, the MODIS sensor appears as an option due to its 
                         high temporal resolution. However, considering its moderate 
                         spatial resolution, the decomposition of its spectral response is 
                         indicated. The SLMM appears to be a viable technique, since it 
                         permits estimating the percentage of components within the pixel. 
                         The data used in the temporal class profiles corresponded to the 
                         following fraction images derived from SLMM: vegetation, soil, and 
                         shade. Discrimination of natural and anthropogenic classes was 
                         determined through the Mahalanobis distance, presented by 
                         dendrograms. The fraction images allow time series analyses for 
                         spatial and temporal characterization of the classes. Soil and 
                         shade fraction images, in the dry season, present better results 
                         in the discrimination of selected classes. For the discrimination 
                         of classes with similar floristic composition, fraction images 
                         from the rainy season are indicated.",
                  doi = "10.1590/S0100-204X2010000200010",
                  url = "http://dx.doi.org/10.1590/S0100-204X2010000200010",
                label = "lattes: 7484071887086439 4 SilvaForShiAdaSan:2010:DICLCO",
             language = "pt",
           targetfile = "v45n2a10.pdf",
                  url = "http://webnotes.sct.embrapa.br/pdf/pab2010/02/45n02a10.pdf",
        urlaccessdate = "12 maio 2024"
}