@InProceedings{ServelloKuplShim:2010:TrLaCo,
               author = "Servello, Emerson Luiz and Kuplich, Tatiana Mora and Shimabukuro, 
                         Yosio Edemir",
          affiliation = "Inst Brasileiro Meio Ambiente \& Recursos Nat Reno, Av Ludovico 
                         da Riva Neto 2643, BR-78580000 Alta Floresta, MT, Brazil and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Tropical land cover change detection with polarimetric SAR data",
            booktitle = "Proceedings...",
                 year = "2010",
         organization = "International Geoscience and Remote Sensing Symposium, (IGARSS).",
            publisher = "IEEE",
              address = "New York",
             keywords = "Brazilian Amazonia, Change detection, Classification, 
                         Classification accuracy, Classification results, Cloud cover, 
                         Field campaign, Forest conversion, Forest cover, Images 
                         interpretation, Incidence angles, Land cover, Land-cover change, 
                         Polarimetric image, Polarimetric SAR data, Radarsat-2, RADARSAT-2 
                         images, SAR data, SAR Images, Test samples, Tropical lands, 
                         Deforestation, Geology, Landforms, Polarimeters, Polarographic 
                         analysis, Remote sensing, Signal detection, Synthetic aperture 
                         radar, Tropics, Mapping, Brazil, Classification, Data Processing, 
                         Deforestation, Mapping, Polarography, Radar, Remote Sensing, 
                         Signals, Tropics.",
             abstract = "There is an increasing need for fast and accurate data on tropical 
                         land cover status, and a baseline for land cover monitoring. 
                         Remotely sensed SAR data are not sensitive to cloud cover and can 
                         be useful for such purpose. Polarimetric SAR data are available in 
                         orbital systems, such as RADARSAT-2, and still have to be tested 
                         for the classification of tropical land cover and the detection of 
                         land cover change, particularly forest conversion. This work 
                         presents a study of RADARSAT-2 polarimetric images, acquired in 
                         two different dates (September 2008 and October 2009), to assess 
                         their potential in classifying forest and non-forest classes in 
                         Brazilian Amazonia. SAR images were acquired following different 
                         orbit and incidence angles, which anticipated varied conditions 
                         for images interpretation and classes discrimination. The complex 
                         SAR data were classified based on the distance of Wishart, and 
                         information from field campaigns was used for the training and 
                         test samples. Classification results were compared to evaluate 
                         possibilities for change detection in the forest cover. 
                         Classification accuracy figures were around 80%. The use of 
                         RADARSAT-2 images allowed the mapping of land cover and land cover 
                         change, considering forest and non-forest classes.",
  conference-location = "Honolulu",
      conference-year = "25-30 July 2010",
                  doi = "10.1109/IGARSS.2010.5653215",
                  url = "http://dx.doi.org/10.1109/IGARSS.2010.5653215",
                 isbn = "978-1-4244-9564-1 and 978-1-4244-9565-8",
                 issn = "2153-6996",
             language = "en",
           targetfile = "05653215.pdf",
        urlaccessdate = "01 maio 2024"
}