@InProceedings{OliveiraJúniorFrei:2023:CoEsCa,
               author = "Oliveira J{\'u}nior, Alexandre Roberto de and Freitas, Eduardo 
                         Pinheiro de",
          affiliation = "Instituto Federal de Educa{\c{c}}{\~a}o, Ci{\^e}ncia e 
                         Tecnologia de S{\~a}o Paulo (IFSP) and Instituto Federal de 
                         Educa{\c{c}}{\~a}o, Ci{\^e}ncia e Tecnologia de S{\~a}o Paulo 
                         (IFSP)",
                title = "Comportamento espectral da cana-de-a{\c{c}}{\'u}car utilizando 
                         imagens Sentinel-2",
            booktitle = "Anais...",
                 year = "2023",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de and Sanches, Ieda DelArco",
                pages = "e155516",
         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 = "agricultura de precis{\~a}o, bandas espectrais, Google Earth 
                         Engine, sensoriamento remoto ABSTRACT: precision agriculture, 
                         spectral bands, Google Earth Engine, remote sensing.",
             abstract = "Importante {\`a} economia brasileira, a 
                         cana-de-a{\c{c}}{\'u}car demanda pesquisas relacionadas {\`a}s 
                         t{\'e}cnicas de agricultura de precis{\~a}o para um 
                         gerenciamento eficiente e sustent{\'a}vel, empregando 
                         caracter{\'{\i}}sticas espectrais da cultura. Este trabalho, com 
                         o objetivo de caracterizar o comportamento espectral de um cultivo 
                         de cana-de-a{\c{c}}{\'u}car, utilizou imagens da miss{\~a}o 
                         Sentinel-2, sensor MSI, processadas no ambiente interativo Code 
                         Editor da plataforma Google Earth Engine, empregando uma rotina em 
                         JavaScript que possibilitou obter matrizes envolvendo 
                         geoposicionamento, data e valor de reflet{\^a}ncia para cada 
                         banda espectral, utilizadas no estudo das variabilidades espacial 
                         e temporal destas bandas a partir de an{\'a}lises de medidas de 
                         tend{\^e}ncia central e de dispers{\~a}o, al{\'e}m de 
                         semivariogramas e correla{\c{c}}{\~o}es. A conclus{\~a}o {\'e} 
                         a de que tal variabilidade p{\^o}de ser adequadamente 
                         caracterizada e o comportamento da reflet{\^a}ncia concordou com 
                         o espectro da cana-de-a{\c{c}}{\'u}car, sendo observada uma 
                         homogeneidade no padr{\~a}o de cobertura do solo ao longo da 
                         safra. ABSTRACT: Important for the Brazilian economy, sugarcane 
                         demands research related to precision agriculture techniques for 
                         efficient and sustainable management, employing spectral 
                         characteristics of the crops. This work, with the aim of 
                         characterizing the spectral behavior of a sugarcane crop, used 
                         images from the Sentinel-2 mission, MSI sensor, processed in the 
                         Code Editor interactive environment of the Google Earth Engine 
                         platform. A JavaScript routine was used to obtain matrices 
                         involving geopositioning, date and reflectance value for each 
                         spectral band, used in the study of spatial and temporal 
                         variability of these bands from the analysis of measures of 
                         central tendency and dispersion, in addition to semivariograms and 
                         correlation. The conclusion is that such variability could be 
                         adequately characterized and the reflectance behavior agreed with 
                         the sugarcane spectrum, being observed a homogeneity in the soil 
                         cover pattern throughout the season.",
  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/4927AL2",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/4927AL2",
           targetfile = "155516.pdf",
                 type = "Produ{\c{c}}{\~a}o e previs{\~a}o agr{\'{\i}}cola",
        urlaccessdate = "09 maio 2024"
}