@InProceedings{BeuchleShiCarJanLim:2019:LaMoFo,
               author = "Beuchle, Ren{\'e} and Shimabukuro, Yosio Edemir and Carboni, 
                         Silvia and Janouskova, Klara and Lima, Thais Almeida",
          affiliation = "European Commission, Joint Research Centre (JRC) and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {GFT ITALIA} and {ARHS 
                         Developments S.A.} and {University of British Columbia}",
                title = "Large-scale monitoring of forest disturbances in northern Mato 
                         Grosso from 2000-2011 based on the cloud computed \ΔrNBR 
                         index",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "143--146",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "forest disturbance, remote sensing, REDD+, Brazilian Amazon, 
                         selective logging, forest fires, \Δ,,rNBR.",
             abstract = "This paper describes a novel approach of large-scale remote 
                         sensing - based monitoring of human-induced forest disturbances by 
                         selective logging and forest fires for the years 20002011 in 
                         Northern Mato Grosso State in the Brazilian Amazon, comprising 
                         more than 414,000 km2. A pixel-based yearly change detection 
                         approach is applied on multiple Landsat imagery, using a 
                         self-referenced Normalized Burn Ratio (\ΔrNBR) index through 
                         cloud computing with Google Earth Engine. Assessed within grid 
                         cells of 300 m ×300 m spatial resolution, the overall area of 
                         disturbed forest over 12 years covers 53,302 km2 (24,1%), thereof 
                         38,255 km2 by selective logging (17,3%) and 18,711 km2 (8,4%) by 
                         forest fires, including 3,664 km2 (1.7%) in both categories. The 
                         yearly areas under selective logging and affected by forest fire 
                         range from 1,819 km2 (2009) to 6,984 km2 (2005) and from 68,0 km2 
                         (2001) and 10,258 km2 (2007), respectively.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3TUTN72",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3TUTN72",
           targetfile = "97295.pdf",
                 type = "Degrada{\c{c}}{\~a}o de florestas",
        urlaccessdate = "28 abr. 2024"
}