@InProceedings{FonsecaOlivRizz:2001:AvIdÁr,
               author = "Fonseca, Eliana Lima da and Oliveira, J{\'u}lio C{\'e}sar de and 
                         Rizzi, Rodrigo",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Avalia{\c{c}}{\~a}o da identifica{\c{c}}{\~a}o de {\'a}reas 
                         com cultivos agr{\'{\i}}colas para fins de previs{\~a}o de 
                         safras utilizando procedimentos de classifica{\c{c}}{\~a}o 
                         digital de imagens do sensor TM/Landsat 5",
            booktitle = "Anais...",
                 year = "2001",
               editor = "Krug, Thelma and Fonseca, Leila Maria Garcia",
                pages = "79--86",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 10. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "AGRONOMIA, {\'{\i}}ndice de vegeta{\c{c}}{\~a}o da 
                         diferen{\c{c}}a normalizada, classifica{\c{c}}{\~a}ode imagens, 
                         {\'a}reas plantadas, agricultura, alvos, 
                         classifica{\c{c}}{\~a}o supervissionada, normalized difference 
                         vegetation index, image classification, targets, supervised 
                         classification.",
             abstract = "In this paper we tested two digital classifications procedures 
                         (supervised and automatic)in order to distinguish crop areas from 
                         other targets and evaluate the supervised classification results 
                         with the target's NDVI patters. The study area covers part of 
                         Ipu{\~a} municipality in S{\~a}o Paulo State, where land use 
                         were mostly agriculture, with corn, sorghum and sugar cane, and 
                         other areas with grassland and gallery forest. The digital image 
                         classification procedures are useful to separate and quantify 
                         agriculture areas. To separate different agricultural targets this 
                         present classification techniques and sensor spatial and spectral 
                         resolution are not appropriate.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "21-26 abr. 2001",
                 isbn = "85-17-00016-1",
                label = "9261",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "dpi.inpe.br/lise/2001/09.12.17.10",
                  url = "http://urlib.net/ibi/dpi.inpe.br/lise/2001/09.12.17.10",
           targetfile = "0079.86.276.pdf",
                 type = "Agronomia",
        urlaccessdate = "03 maio 2024"
}