@InProceedings{SoaresFormGalv:2007:ÁrAgSe,
               author = "Soares, D{\^e}nis de Moura and Formaggio, Ant{\^o}nio Roberto 
                         and Galv{\~a}o, L{\^e}nio Soares",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE). Diretoria de 
                         Servi{\c{c}}o Geogr{\'a}fico (DSG).} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "{\'A}reas agr{\'{\i}}colas em sensores com 
                         resolu{\c{c}}{\~a}o espacial de 30 m estimadas a partir de dados 
                         MODIS e m{\'e}tricas da paisagem",
            booktitle = "Anais...",
                 year = "2007",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares and Fonseca, Leila Maria Garcia",
                pages = "407--414",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 13. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "coarse resolution, spatial pattern, landscape metric, regression 
                         analysis, resolu{\c{c}}{\~a}o moderada, padr{\~a}o espacial, 
                         m{\'e}trica da paisagem, an{\'a}lise de regress{\~a}o.",
             abstract = "The objective of this work was to evaluate the differences between 
                         crop area estimation from coarse resolution data (e.g. 
                         MODIS/Terra, with 250m) and ETM+/Landsat-7 resolution data (30m), 
                         considering different crop types and their spatial pattern 
                         quantified by landscape metrics. The analysis was applied for 
                         three different crops: corn, sugarcane and soybean. The thematic 
                         classes woodland, pasture and exposed soils were also included in 
                         the analysis. Simple (area) and multiple (area plus landscape 
                         metrics) regression models were performed using ETM+ and MODIS 
                         data. One global and three single statistical models were 
                         developed. The global approach (the three crops, simple 
                         regression) produced a coefficient of determination (R˛) of 0.46. 
                         On the other hand, the developing of statistic models for each 
                         crop (landscape metrics, multiple regression) improved the R˛ 
                         value to 0.52, 0.67 and 0.87 for corn, sugarcane and soybean, 
                         respectively. Results showed that accurate crop estimation area 
                         from coarse resolution data is much more difficult for corn than 
                         for sugarcane and soybean because of the high fragmentation of 
                         corn distribution in the study area.",
  conference-location = "Florian{\'o}polis",
      conference-year = "21-26 abr. 2007",
           copyholder = "SID/SCD",
                 isbn = "978-85-17-00031-7",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2006/11.14.11.06",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2006/11.14.11.06",
           targetfile = "407-414.pdf",
                 type = "Agricultura",
        urlaccessdate = "11 maio 2024"
}