author = "Kuck, Tahisa Neitzel and Keizer, Edwin Willem Hermanus and 
                         Pacheco, Pablo and Lira, Roni Von Cascais de and Vasconcelos, 
                         S{\^a}mia Amorim de and Arruda, Andr{\'e} N{\'o}brega de",
          affiliation = "{Greenpeace  Campanha Amaz{\^o}nia} and {Greenpeace  Campanha 
                         Amaz{\^o}nia} and {Greenpeace  Campanha Amaz{\^o}nia} and 
                         {Greenpeace  Campanha Amaz{\^o}nia} and {Greenpeace  Campanha 
                         Amaz{\^o}nia} and {Greenpeace  Campanha Amaz{\^o}nia}",
                title = "Mapeamento multitemporal (2001-2009) do uso da terra no bioma 
                         Amaz{\^o}nia do estado do Mato Grosso atrav{\'e}s de imagens 
            booktitle = "Anais...",
                 year = "2011",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                pages = "7776--7783",
         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 = "remote sensing, LUCC, EVI, decision tree, sensoriamento remoto, 
                         mudan{\c{c}}a de uso/cobertura da terra, EVI, {\'a}rvore de 
             abstract = "Large scale agriculture and extensive cattle ranging are the main 
                         drivers of deforestation within the Amazon are responsible for 
                         158.310 km2 of forest cover loss since 2001. Although these two 
                         activities represent significant importance within the context of 
                         land use and land cover change and their impacts on greenhouse gas 
                         emissions, there is still no adequate operational monitoring 
                         system which provides high quality data and information on land 
                         use change considering the spatial-temporal dynamics. This 
                         information is crucial for territorial planning, zonation for use 
                         and conservation, environmental monitoring, agricultural planning 
                         and agro-business among others. The objective of this study by 
                         Greenpeace was the development of a land use classification 
                         methodology for the annual land use mapping within the Amazon 
                         Biome covering the state of Mato Grosso, based on multitemporal 
                         analysis of EVI (Enhanced Vegetation Index) values derived from 
                         the MOD12Q1 product of the MODIS sensor. The classification was 
                         implemented through the construction of a decision tree based on 
                         knowledge differentiating the temporal behavior of EVI of the 
                         different land use types. Field data collection, literature 
                         analysis and medium to high resolution image interpretation were 
                         the basis for land use differentiation. The obtained results were 
                         validated and demonstrated excellent accuracies according to 
                         literature. The methodology showed to be applicable for the 
                         mapping of the principal land use types present within the study 
                         area and permits to analyze interannual transitions to increase 
                         our understanding of the land use dynamics within the Amazon 
  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/39UFBGL",
                  url = "http://urlib.net/rep/3ERPFQRTRW/39UFBGL",
           targetfile = "p0541.pdf",
                 type = "Mudan{\c{c}}a de Uso e Cobertura da Terra",
        urlaccessdate = "25 jan. 2021"