@InProceedings{RizziRudo:2003:ImLaEs,
               author = "Rizzi, Rodrigo and Rudorff, Bernardo Friedrich Theodor",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Imagens Landsat na estimativa da {\'a}rea plantada com soja em 
                         munic{\'{\i}}pios do Rio Grande do Sul",
            booktitle = "Anais...",
                 year = "2003",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "231--238",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 11. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "crop area estimation, image classification, Landsat, soybean.",
             abstract = "The objective of this work was to estimate soybean crop area in 
                         municipalities of Rio Grande do Sul State, Brazil, using Landsat 
                         images. Two scenes from path 223 row 79 and 80 were acquired at 
                         two different dates during the crop year of 2000/01. The soybean 
                         crop area was estimated using both digital and visual 
                         classification. The official crop area estimation at the 
                         municipality level was provided by the Systematic Survey 
                         Agricultural Production (LSPA) from the Brazilian Geography and 
                         Statistics Institute (IBGE) and used for comparison with the 
                         estimates obtained from the image classification. The overall 
                         result showed a very low difference between the LSPA estimation 
                         and the image classification. However, the large relative 
                         differences were observed in municipalities with very low soybean 
                         crop area, although the highest absolute differences were observed 
                         in municipalities with high soybean crop area (above 10.000 ha). 
                         Due to the acquisition of cloud free scenes during the most 
                         critical period to map soybean areas, this method proved to be 
                         very accurate.",
  conference-location = "Belo Horizonte",
      conference-year = "5-10 abr. 2003",
           copyholder = "SID/SCD",
                 isbn = "85-17-00017-X",
             language = "English",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2002/11.18.16.47",
                  url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2002/11.18.16.47",
           targetfile = "01_411.pdf",
                 type = "Agronomia / Agriculture",
        urlaccessdate = "28 abr. 2024"
}