@InProceedings{MartinsNoguSetzMore:2019:ApCoDi,
               author = "Martins, Guilherme and Nogueira, Joana and Setzer, Alberto 
                         Waingort and Morelli, Fabiano",
          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)}",
                title = "Fire Patterns in the Brazilian Cerrado: an Approach Comparing 
                         Different Input Datasets in the Fire Risk Modelling",
            booktitle = "Anais...",
                 year = "2019",
         organization = "International Wildland Fire Ecology and Fire Management Congress, 
                         7.",
             keywords = "Fire modelling, fire season, savannas, Brazil, land use.",
             abstract = "Emissions from vegetation fires are relevant in the 
                         atmosphere-biosphere interaction. Nevertheless, fire is still 
                         intensely used as a tool in land management, modifying natural 
                         fire patterns in fire-prone ecosystems. The Brazilian Cerrado has 
                         shown increased anthropogenic fire ignitions, especially due to 
                         deforestation that removed ~50% of its original cover and unusual 
                         droughts. Fire risk (FR) models using meteorological and 
                         vegetation parameters have been used to estimate fire patterns at 
                         biome level. Theaim of this study was to evaluate the performance 
                         of INPEs FR model using different climate and land cover (LC) 
                         datasets (versions 0 and 1) to estimate FR patterns in the 
                         Cerrado. Meteorological datasets from CoSch and MCD12Q1-IGBP V006 
                         land cover data represent v0 while v1 is composed by IMERG and 
                         Mapbiomas v3.0 datasets. The analyses were performed in the wet 
                         (W: November-March) and dry (D: May-September) seasons from 2015 
                         to 2018 at 1km of spatial resolution. The versions were compared 
                         using the seasonal predominance of FR (PFR) and evaluated in five 
                         categories: minimum, FR<=0.15; low, 0.15<FR<=0.40; medium, 
                         0.40<FR<=0.70; high, 0.70<FR<=0.95 and critical, 0.95<FR<=1.0. The 
                         main fire pattern differences between v0 and v1 were observed in 
                         D, when the PFR remains high during all season according to v0, 
                         while v1classifies critical PFR from July to September. In W, 
                         differences were not observed, except for November, classified as 
                         low PFR by v0 and minimum PFR in v1. These differences can 
                         berelated to the higher LC spatial resolution and definition of 
                         vegetation types in v1 such as woody savannas; v1 is based on 
                         Landsat medium resolution spectral images (~30m) while v0 uses 
                         MODIS low resolution (~500m). Concerning precipitation, the 
                         information has a higher spatial consistency using 10 km of 
                         spatial resolution in v1 while v0 uses 25 km of spatial 
                         resolution. With new Mapbiomas editions and revisions released 
                         every year, INPEs FR will be updated accordingly, allowing a 
                         realistic temporal modeling of the vegetation; including terrain 
                         data in this condition will allow a new FR product at 30m 
                         resolution for protected areas our next goal.",
  conference-location = "Bras{\'{\i}}lia, DF",
      conference-year = "2019",
                  doi = "10.37002/biodiversidadebrasileira.v10i1.1563",
                  url = "http://dx.doi.org/10.37002/biodiversidadebrasileira.v10i1.1563",
             language = "en",
           targetfile = "1563-Texto do Artigo-6511-1-10-20200401.pdf",
        urlaccessdate = "03 maio 2024"
}