@InProceedings{ZalotiJrGonFreSanSan:2006:EvPoSA,
               author = "Zaloti Jr., Orlando D. and Gon{\c{c}}alves, F{\'a}bio G. and 
                         Freitas, Corina da Costa and Sant’Anna, Sidnei Jo{\~a}o S. and 
                         Santos, Jo{\~a}o Roberto dos",
          affiliation = "Divis{\~a}o de Geo-Intelig{\^e}ncia. Instituto de Estudos 
                         Avan{\c{c}}ados, IEAv, S{\~a}o Jos{\'e} dos Campos and 
                         {Instituto Nacional de Pesquisas Espaciais. Divis{\~a}o de 
                         Processamento de Imagens} and {nstituto Nacional de Pesquisas 
                         Espaciais. Divis{\~a}o de Sensoriamento Remoto}",
                title = "Evaluating the Potential of SAR-R99B L and X Bands Data for Amazon 
                         Deforestation Increment Mapping",
            booktitle = "Proceedings...",
                 year = "2006",
                pages = "2662 - 2665",
         organization = "Geoscience and Remote Sensing Symposium (IGARSS); Canadian 
                         Symposium on Remote Sensing, 28.",
            publisher = "IEEE",
              address = "IEEE",
             keywords = "Algorithms, Radar imaging, Synthetic aperture radar, Change 
                         detection, Forest monitoring, Iterated Conditional Modes (ICM), 
                         Tropical forest, Deforestation, Algorithms, Deforestation, 
                         Radar.",
             abstract = "The main objective of this paper is to evaluate the potential of 
                         the SAR-R99B airborne radar images (L-band Quad-Pol and X-band HH) 
                         from the Amazon Protection System (SIPAM) to discriminate the 
                         increment of deforested areas. In order to achieve this purpose, 
                         two classification approaches are considered. In the first 
                         approach, the contextual algorithm Iterated Conditional Modes 
                         (ICM) is used to classify only amplitude SAR images. The second 
                         approach consists on synthesizing TM/Landsat fraction images from 
                         several polarimetric SAR attributes, preserving the automated 
                         procedures currently developed in the Amazon annual monitoring 
                         activity throughout the Prodes Digital Project methodology.",
  conference-location = "Denver",
      conference-year = "31 July - 4 Aug.",
                  doi = "10.1109/IGARSS.2006.687",
                  url = "http://dx.doi.org/10.1109/IGARSS.2006.687",
                 isbn = "0780395107 and 9780780395107",
             language = "en",
         organisation = "IEEE",
           targetfile = "04_14A04.pdf",
        urlaccessdate = "20 maio 2024"
}