@Article{GussoForRizAdaThe:2012:SoCrAr,
               author = "Gusso, Anibal and Formaggio, Antonio Roberto and Rizzi, Rodrigo 
                         and Adami, Marcos and Theodor Rudorff, Bernardo Friedrich",
          affiliation = "Universidade Federal de Pelotas, Caixa Postal 354, CEP 96001-970 
                         Cap{\~a}o do Le{\~a}o, RS, Brazil and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Soybean crop area estimation by Modis/Evi data",
              journal = "Pesquisa Agropecu{\'a}ria Brasileira",
                 year = "2012",
               volume = "47",
               number = "3",
                pages = "425 - 435",
                month = "Mar.",
             keywords = "Glycine max, algorithm, crop area, mapping, temporal profile 
                         images, classification, states.",
             abstract = "The objective of this work was to develop a procedure to estimate 
                         soybean crop areas in Rio Grande do Sul state, Brazil. Estimations 
                         were made based on the temporal profiles of the enhanced 
                         vegetation index (Evi) calculated from moderate resolution imaging 
                         spectroradiometer (Modis) images. The methodology developed for 
                         soybean classification was named Modis crop detection algorithm 
                         (MCDA). The MCDA provides soybean area estimates in December 
                         (first forecast), using images from the sowing period, and March 
                         (second forecast), using images from the sowing and maximum crop 
                         development periods. The results obtained by the MCDA were 
                         compared with the official estimates on soybean area of the 
                         Instituto Brasileiro de Geografia e Estatistica. The coefficients 
                         of determination ranged from 0.91 to 0.95, indicating good 
                         agreement between the estimates. For the 2000/2001 crop year, the 
                         MCDA soybean crop map was evaluated using a soybean crop map 
                         derived from Landsat images, and the overall map accuracy was 
                         approximately 82%, with similar commission and omission errors. 
                         The MCDA was able to estimate soybean crop areas in Rio Grande do 
                         Sul State and to generate an annual thematic map with the 
                         geographic position of the soybean fields. The soybean crop area 
                         estimates by the MCDA are in good agreement with the official 
                         agricultural statistics.",
                  doi = "10.1590/S0100-204X2012000300015",
                  url = "http://dx.doi.org/10.1590/S0100-204X2012000300015",
                 issn = "0100-204X",
             language = "en",
           targetfile = "Gusso_A et al.pdf",
        urlaccessdate = "15 jun. 2024"
}