@InProceedings{NicolauMerJohGrzPal:2015:MaÁrCu,
               author = "Nicolau, Rafaela Fernandes and Mercante, Erivelto and Johann, 
                         Jerry Adriani and Grzegozewski, Denise Maria and Paludo, Alex",
                title = "Mapeamento de {\'a}reas das culturas de trigo e milho 2ª safra 
                         para o estado do Paran{\'a} por meio de imagens multitemporais 
                         Modis",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2468--2475",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "Obtaining effective technologies for quantifying and forecasting 
                         the monitoring of agricultural crops highlights the search for 
                         methodologies that provide this information before harvest. The 
                         study of agricultural monitoring and/or estimated yields of winter 
                         crops using vegetation indices derived from multi-temporal data 
                         from Modis sensor, is being studied in the search for greater 
                         objectivity to the values generated. In this context, the research 
                         aims to map areas with winter crops (wheat and corn 2nd harvest), 
                         using time series of vegetation index EVI from the Modis sensor of 
                         Terra and Aqua satellites, the 2013 harvest for the state of 
                         Paran{\'a}. As a way to adjust the mapping through Modis (250 
                         meters) sensor visual analysis, where images of high spatial 
                         resolution (30 meters) to identify the desired cultures were used 
                         was performed. Checking the quality of the mapping was assessed by 
                         using the error matrix analysis of accuracy as the Global Accuracy 
                         and the Kappa coefficient. For corn (2nd crop) and wheat, the 
                         overall accuracy reached values of 92.5% and 87.3% for corn (2nd 
                         crop) and wheat respectively, reaching the minimum acceptable 
                         value that is 85%. The Kappa index was classified as excellent and 
                         very good for the corn (2nd crop) and wheat respectively.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "495",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4A3H",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3JM4A3H",
           targetfile = "p0495.pdf",
                 type = "An{\'a}lise de s{\'e}ries de tempo de imagens de sat{\'e}lite",
        urlaccessdate = "08 maio 2024"
}