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@Article{MoreiraRudBarFarAda:2010:GeMaCo,
               author = "Moreira, Mauricio Alves and Rudorff, Bernardo Friedrich Theodor 
                         and Barros, Marco A. and Faria, Viviane G. C. de and Adami, 
                         Marcos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Geotecnologies to map coffee fields in the states of minas gerais 
                         and S{\~a}o Paulo / Geotecnologias para mapear lavouras de 
                         caf{\'e} nos estados de Minas Gerais e S{\~a}o Paulo",
              journal = "Engenharia Agr{\'{\i}}cola",
                 year = "2010",
               volume = "30",
               number = "6",
                pages = "1123--1135",
                month = "Dec.",
             keywords = "sensoriamento remoto, imagens de sat{\'e}lite, geoprocessamento, 
                         estat{\'{\i}}sticas agr{\'{\i}}colas, statistics, 
                         Geoprocessing, Remote sensing, Satellite images.",
             abstract = "The operational use of remote sensing images to map coffee fields 
                         in large areas, in order to obtain reliable and timely 
                         agricultural statistics, is still under development. Several 
                         factors raise difficulties to correctly identify and map the 
                         coffee crop. However, technological advances observed in the last 
                         years, in terms of image acquisition with improved quality and 
                         greater quantity, as well as the development of new tools for 
                         image analysis, is favoring the development of an operational 
                         method that may contribute to establish the official coffee crop 
                         statistics in Brazil. Therefore, the present work has the 
                         objective to describe the method and to present the result of the 
                         coffee fields mapped in the states of Minas Gerais and S{\~a}o 
                         Paulo using remote sensing images and geoprocessing techniques. 
                         The methodological approach consisted of four steps: a) image 
                         restoration and georeferencing; b) non-supervised classification; 
                         c) visual interpretation on the computer screen to suppress 
                         omission and commission errors; and d) coffee crop area 
                         estimation. The results indicated that the applied method was 
                         appropriate to map the coffee crop in the states of Minas Gerais 
                         and S{\~a}o Paulo.",
                  doi = "10.1590/S0100-69162010000600013",
                  url = "http://dx.doi.org/10.1590/S0100-69162010000600013",
                 issn = "0100-6916",
             language = "en",
           targetfile = "a13v30n6mo.pdf",
        urlaccessdate = "26 jan. 2021"
}


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