@InProceedings{PelissariLLTSTONRS:2023:AdSoCo,
               author = "Pelissari, Tatiane Deoti and Louren{\c{c}}oni, Thais and Lima, 
                         Mandelson and Teodoro, Paulo Eduardo and Santos, Regimar Garcia 
                         dos and Teodoro, Larissa Pereira Ribeiro and Oliveira, Betrielly 
                         Zanrosso de and Nanni, Marcos Rafael and Rossi, Fernando Saragosa 
                         and Silva J{\'u}nior, Carlos Antonio",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and {Universidade do 
                         Estado de Mato Grosso (UNEMAT)} and {Universidade do Estado de 
                         Mato Grosso (UNEMAT)} and {} and {Universidade Estadual Paulista 
                         (UNESP)} and {Universidade Federal de Mato Grosso do Sul (UFMS)} 
                         and {Universidade do Estado de Mato Grosso (UNEMAT)} and 
                         {Universidade Estadual de Maring{\'a} (UEM)} and {Universidade 
                         Estadual Paulista (UNESP)} and {Universidade do Estado de Mato 
                         Grosso (UNEMAT)}",
                title = "Advance of soy commodity in the Amazonia under deforestation data 
                         via PRODES and Imazongeo",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155539",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 20. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Amazon, remote sensing, agricultural culture, public policies, 
                         sustainability.",
             abstract = "Decision making on deforestation in the Amazon has been efficient 
                         due to monitoring programs using remote sensing. Thus, our 
                         objective was to identify the expansion of soy farming in 
                         disagreement with the Soy Moratorium in the Amazon of Mato Grosso 
                         from 2008 to 2019. Deforestation data from PRODES and ImazonGeo 
                         programs were used. The PCEI was calculated using a cloud platform 
                         for soybean areas identification. The Mann-Kendall and Pettitt 
                         tests were used to identify trends across the time series. Our 
                         results revealed a difference between these programs on 
                         deforestation and forest-to-soy conversion areas. According to 
                         PRODES data, 1,387,288 ha were deforested from August 2008 to 
                         October 2019, of which 108,411 ha were converted to soybeans. 
                         ImazonGeo data showed 729,204 hectares deforested and 46,182 
                         hectares converted to soybean areas. These results indicate that 
                         the PRODES system has greater data variability and higher averages 
                         than ImazonGeo.",
  conference-location = "Florian{\'o}polis",
      conference-year = "02-05 abril 2023",
                 isbn = "978-65-89159-04-9",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/494HRA5",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/494HRA5",
           targetfile = "155539.pdf",
                 type = "Mudan{\c{c}}a de uso e cobertura da Terra",
        urlaccessdate = "04 jun. 2024"
}