@InProceedings{OliveiraSouzVolpAlve:2023:CaAmÁr,
               author = "Oliveira, Jean Carlos de and Souza, Vanessa C. O. and Volpato, 
                         Margarete M. L. and Alves, Helena M. R.",
          affiliation = "{Universidade Federal de Itajub{\'a} (UNIFEI)} and {Universidade 
                         Federal de Itajub{\'a} (UNIFEI)} and {Empresa de Pesquisa 
                         Agropecu{\'a}ria de Minas Gerais (EPAMIG)} and {Empresa 
                         Brasileira de Pesquisa Agropecu{\'a}ria (EMBRAPA)}",
                title = "Caracteriza{\c{c}}{\~a}o ambiental de {\'a}reas cafeeira 
                         utilizando o Google Earth Engine",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e156334",
         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 = "GEE, cafeicultura, caracteriza{\c{c}}{\~a}o ambiental, coffee 
                         growing, environmental characterization.",
             abstract = "O objetivo deste trabalho foi avaliar a viabilidade do uso da 
                         plataforma em nuvem Google Earth Engine para 
                         caracteriza{\c{c}}{\~a}o ambiental de ambientes 
                         agr{\'{\i}}colas e, consequentemente, no subs{\'{\i}}dio 
                         {\`a} delimita{\c{c}}{\~a}o de regi{\~o}es {\`a} 
                         denomina{\c{c}}{\~a}o de origem por meio de geotecnologias. O 
                         estudo de caso foi no munic{\'{\i}}pio de Santo Ant{\^o}nio do 
                         Amparo/MG e foi realizado o diagn{\'o}stico ambiental em 
                         rela{\c{c}}{\~a}o ao relevo (altitude, declividade, vertente e 
                         sombreamento), solos e {\`a}s vari{\'a}veis clim{\'a}ticas 
                         temperatura e precipita{\c{c}}{\~a}o. Todo processamento foi 
                         realizado no ambiente de programa{\c{c}}{\~a}o Code Editor do 
                         GEE, que mostrou-se eficaz para estudos de 
                         caracteriza{\c{c}}{\~a}o ambiental. Foi poss{\'{\i}}vel gerar 
                         mapas e obter informa{\c{c}}{\~o}es quantitativas sobre a 
                         ocupa{\c{c}}{\~a}o da cafeicultura no munic{\'{\i}}pio. 
                         Al{\'e}m disso, foi poss{\'{\i}}vel realizar 
                         simula{\c{c}}{\~o}es de {\'a}reas para denomina{\c{c}}{\~a}o 
                         de origem utilizando vari{\'a}veis estritamente ambientais. 
                         ABSTRACT: The main of this work was to evaluate the feasibility of 
                         using the Google Earth Engine cloud platform for environmental 
                         characterization of agricultural environments and, consequently, 
                         to support the delimitation of protected denomination of origin 
                         (DO) through geotechnologies. The case study occurred in the 
                         municipality of Santo Ant{\^o}nio do Amparo/MG where an 
                         environmental diagnosis executed about the relief (elevation, 
                         declivity, slope orientation, and hillshade), soils, and the 
                         climatic variables temperature and precipitation. All processing 
                         was performed in the GEE Code Editor programming environment, 
                         which proved effective for environmental characterization studies. 
                         It was possible to generate maps and obtain quantitative 
                         information about the occupation of coffee growing in the 
                         municipality. In addition, it was possible to carry out 
                         simulations for delimitation DO using strictly environmental 
                         variables.",
  conference-location = "Florian{\'o}polis",
      conference-year = "02-05 abril 2023",
                 isbn = "978-65-89159-04-9",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/494UQNH",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/494UQNH",
           targetfile = "156334.pdf",
                 type = "Mudan{\c{c}}a de uso e cobertura da Terra",
        urlaccessdate = "03 jun. 2024"
}