@InProceedings{VedovatoJacPesLimAra:2015:DeBuFo,
               author = "Vedovato, Laura Barbosa and Jacon, Aline Daniele and Pess{\^o}a, 
                         Ana Carolina Moreira and Lima, Andr{\'e} and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Detection of burned forests in Amazonia using the Normalized Burn 
                         Ratio (NBR) and Linear Spectral Mixture Model from Landsat 8 
                         images",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2984--2991",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Wildfires represent a major disturbance factor leading to 
                         environmental changes with local or regional impacts. In the 
                         Amazon, although fire is associated with several land-practices, 
                         the long dry season in some regions, especially during extreme 
                         droughts, makes vegetation more susceptible to uncontrolled fires. 
                         Furthermore,the burn of biomass is a considerable source of 
                         atmospheric pollution, including carbon dioxide, a major 
                         greenhouse gas. Due to the large geographical extent of fires at 
                         regional and global scales, remote sensing approaches became 
                         relevant in the last decades. In this paper, we compare two 
                         different methodologies of fire detection for Amazon region and 
                         evaluate possible spectral confusions these two methods can 
                         generate on the analysis. We compared the Normalized Burn Ratio 
                         (NBR) and the Linear Spectral Mixture Model data extracted from 
                         high resolution satellite Landsat 8 image. Our results indicate 
                         that the detection of burned forests areas using the LSMM index 
                         performs better over fragmented landscapes, with a index Kappa 
                         of0.68 and 0.66 against a index Kappa for NBR of 0.52 and 0.52, in 
                         the study sites B and C respectively. Considering areas less 
                         fragmented as study site A in this study, both methodologies 
                         showed the same Kappa value (0.88). Thus, considering the 
                         complexity of Amazonian landscapes, which encompass both high and 
                         low fragmentation areas, the LSMM index is likely to perform 
                         better in the detection of burnt forests than the NBR index.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "594",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4AJN",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4AJN",
           targetfile = "p0594.pdf",
                 type = "Monitoramento e modelagem ambiental",
        urlaccessdate = "27 abr. 2024"
}