@InProceedings{VitelBaMoCaGrFeLe:2013:LaChAn,
               author = "Vitel, Claudia Suzanne Marie Nathalie and Barros, Heberton and 
                         Moreira, Noeli and Carrero, Gabriel Cardoso and Gra{\c{c}}a, 
                         Paulo Maur{\'{\i}}cio Lima de Alencastro and Fearnside, Philip 
                         Martin and Leroy, Maya",
                title = "Land-use change analysis in the Sete de Setembro Indigenous Land 
                         (Rond{\^o}nia \& Mato Grosso, Brazil) using multi-temporal 
                         Landsat images classification between 2000 and 2009",
            booktitle = "Anais...",
                 year = "2013",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares",
                pages = "7164--7171",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 16. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Indigenous Lands that are under high risk of deforestation are 
                         good candidates for REDD (Reduction of Emissions from 
                         Deforestation and Forest Degradation). REDD proposes to reduce 
                         deforestation and forest degradation through remuneration of 
                         carbon benefits. To estimate avoided greenhouse gas (GHG) 
                         emissions, the calculation is usually based on the most plausible 
                         expected amount of deforestation/degradation based on a Land-Use 
                         and Land-Cover Change (LULCC) reference scenario. One of the core 
                         methodological steps of a LULCC reference (or baseline) scenario 
                         is to evaluate the quantity of LULCC that occurred in a historical 
                         period, and to identify the drivers of these changes in order to 
                         understand how LULCC would evolve in a future period. The 
                         objective of this study was to map annual land-cover/use classes 
                         in the Sete de Setembro Indigenous Land (in Rond{\^o}nia and Mato 
                         Grosso) between 2000 and 2009, and to extract LULCC rates to serve 
                         as the basis for the Suru{\'{\i}} Forest Carbon Project LULCC 
                         reference scenario. We applied a Maximum-Likelihood supervised 
                         classification of multi-temporal Landsat-TM images to distinguish 
                         five land-cover subclasses: 1-burned areas, 2-bare soil, 
                         3-secondary vegetation, 4- forest and 5-water, and we then grouped 
                         these subclasses to obtain three land-cover/use classes. In 2009, 
                         3416.5 ha were vegetation in equilibrium, 240.033 ha were forest 
                         and 230 ha were secondary vegetation. Applying a subtraction 
                         calculation between consecutive land-cover/use maps, we obtained 
                         an annual average of 154.7 ha of deforestation and 88 ha of 
                         secondary vegetation clearing. Forest-cutting represents, on 
                         average, 72% of LULCC, whereas secondary-vegetation clearing 
                         represents 28%.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "13-18 abr. 2013",
                 isbn = "{978-85-17-00066-9 (Internet)} and {978-85-17-00065-2 (DVD)}",
                label = "1209",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "3ERPFQRTRW34M/3E7GJR3",
                  url = "http://urlib.net/ibi/3ERPFQRTRW34M/3E7GJR3",
           targetfile = "p1209.pdf",
                 type = "Mudan{\c{c}}a de Uso e Cobertura da Terra",
        urlaccessdate = "08 maio 2024"
}