@InProceedings{SantosJoMoPaSoSi:2023:GoEaEn,
               author = "Santos, Marcelo Henrique de Oliveira and Johann, Jerry Adriani and 
                         Moura, Valdir and Paludo, Alex and Souza, Ranieli dos Anjos de and 
                         Silveira, Jo{\~a}o Felipe Cesar",
          affiliation = "{Universidade Estadual do Oeste do Paran{\'a} (UNIOESTE)} and 
                         {Universidade Estadual do Oeste do Paran{\'a} (UNIOESTE)} and 
                         {Instituto Federal de Rond{\^o}nia (IFRO)} and {Universidade 
                         Estadual do Oeste do Paran{\'a} (UNIOESTE)} and {Instituto 
                         Federal de Rond{\^o}nia (IFRO)} and {Universidade Estadual do 
                         Oeste do Paran{\'a} (UNIOESTE)}",
                title = "Google Earth Engine no mapemento de {\'a}reas de pastagem e 
                         culturas anuais em Rond{\^o}nia",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155984",
         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 = "{\'{\i}}ndices de vegeta{\c{c}}{\~a}o, agricultura, 
                         pecu{\'a}ria, processamento em nuvem, vegetation indices, 
                         agriculture, livestock, cloud processing, orbital images.imagens 
                         orbitais.",
             abstract = "Este estudo teve como objetivo realizar o mapeamento de {\'a}reas 
                         com culturas anuais (ver{\~a}o e inverno) e pastagens no estado 
                         de Rond{\^o}nia, utilizando imagens de sat{\'e}lite e aplicando 
                         t{\'e}cnicas de sensoriamento remoto e de aprendizagem de 
                         m{\'a}quina. Para a realiza{\c{c}}{\~a}o dos mapeamentos se 
                         utilizaram as composi{\c{c}}{\~o}es RGB (8,11,4) para o Sentinel 
                         2 e RGB (5,6,4) para o Landsat 8 e {\'{\i}}ndices de 
                         vegeta{\c{c}}{\~a}o (NDVI, EVI e SAVI) de forma conjunta com no 
                         algoritmo classificador Naive Bayes. A classifica{\c{c}}{\~a}o 
                         foi realizada utilizando a platafor ABSTRACT: This study aimed to 
                         map areas with annual crops (summer and winter) and pastures in 
                         Rond{\^o}nia state, using satellite images and applying remote 
                         sensing and machine learning techniques. To carry out the 
                         mappings, the RGB (8,11,4) compositions Sentinel 2 and RGB (5,6,4) 
                         Landsat 8 and vegetation indices (NDVI, EVI and SAVI) were user 
                         together with the Naive Bayes classifier algorithm. The 
                         classification was performed using the Google Earth Engine 
                         platform. With the classification, the areas with summer, winter 
                         and pasture crops were quantified, by Rond{\^o}nia microregion, 
                         for 2020/2021 harvest. As a result, 384 thousand ha were mapped 
                         with summer crops, 219 thousand ha with winter crops and 7.73 
                         million ha with pasture.",
  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/492GAEH",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/492GAEH",
           targetfile = "155984.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "09 maio 2024"
}