@InProceedings{ReisPanDutSanEsc:2019:EfDiMe,
               author = "Reis, Mariane Souza and Pantale{\~a}o, Eliana and Dutra, Luciano 
                         Vieira and Sant'Anna, Sidnei Jo{\~a}o Siqueira and Escada, Maria 
                         Isabel Sobral",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federa de Uberl{\^a}ndia (UFU)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Effects of different methods of radiometric calibration on the use 
                         of training data for supervised classification of Landsat5/TM 
                         images from other dates",
            booktitle = "Proceedings...",
                 year = "2019",
                pages = "1566--1569",
         organization = "International Geoscience and Remote Sensing Symposium (IGARSS)",
            publisher = "IEEE",
             keywords = "Generalization of training samples, signature extension, 
                         multi-temporal classification, Landsat data, Maximum Likelihood.",
             abstract = "In studies that involves supervised classification of several 
                         temporal images, the use of specific samples extracted from each 
                         image may require field work or image interpretation and is often 
                         expensive. The cost could be reduced with the use of reference 
                         data from a different time. However, there may appear differences 
                         in the spectral behavior of land cover classes across time due to 
                         imaging issues, which can prevent the proper reuse of this type of 
                         training data. This paper assesses the influence of image 
                         calibration on the classification of Landsat5/Thematic Mapper (TM) 
                         images using Maximum Likelihood classifier and the use of land 
                         cover training samples collected in images obtained at different 
                         times. Results show that, although the calibration method may 
                         affect the classification results, it had a small impact on 
                         classification global accuracy.",
  conference-location = "Yokohama, Japan",
      conference-year = "28 July - 02 Aug.",
             language = "en",
           targetfile = "reis_effects.pdf",
        urlaccessdate = "12 maio 2024"
}