@InProceedings{SantosVieAguCarSan:2017:IdClUs,
               author = "Santos, Erli Pinto dos and Vieira, {\'E}lton F{\'a}bio Santos 
                         and Aguilar, Caio Macieira de Almeida and Carelli, Liamara and 
                         Santos, Rosangela Leal",
                title = "Identifica{\c{c}}{\~a}o de classes de uso do solo em 
                         per{\'{\i}}metro irrigado do semi-{\'a}rido baiano 
                         utilizando-se produtos do CBERS-4",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "7150--7157",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The city of Rodelas is a Brazilian municipality located in the 
                         north of Bahia, located on the right bank of the S{\~a}o 
                         Francisco river. The municipality currently has a strong 
                         participation of irrigated agriculture in its economy, 
                         highlighting the culture of the C{\^o}co-da-bahia. For purposes 
                         of planning and advancement of areas and land occupation, one of 
                         the alternatives is currently the use of satellite images. Like 
                         the CBERS project, Sino-Brazilian satellite, the access to orbital 
                         images of high spatial resolution has made still more accessible 
                         to the society images with these characteristics. The quality of 
                         the CBERS-4 (Sino-Brazilian Satellite of Earth Resources 4) 
                         products improved significantly compared to previous versions, 
                         demonstrating this in results when compared with other sensors of 
                         equal spatial and spectral resolution. Thus, by means of maximum 
                         likelihood classification, the availability of images of different 
                         spatial and spectral resolutions by the embedded sensors was based 
                         on the principle of evaluating the potential of identification and 
                         separability of the classes of use and occupation of the soil, the 
                         different sensors On board this platform. The level of detail and 
                         definition of the CBERS image is very good, making it present 
                         results equivalent to other sensors of equal spatial and spectral 
                         resolution. The images classified had a high index of global 
                         accuracy, but this did not prevent a high rate of confusion, 
                         mainly between the Solo Exposure and Urban classes.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59455",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMF7N",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMF7N",
           targetfile = "59455.pdf",
                 type = "CBERS",
        urlaccessdate = "27 abr. 2024"
}