@InProceedings{FreitasRosaShim:2010:UsGrPa,
               author = "Freitas, Ramon Morais de and Rosa, Reinaldo Roberto and 
                         Shimabukuro, Yosio Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Using Gradient Pattern Analysis for land use and land cover change 
                         detection",
            booktitle = "Proceedings...",
                 year = "2010",
         organization = "Geoscience and Remote Sensing Symposium, (IGARSS).",
            publisher = "IEEE",
              address = "Piscataway",
             keywords = "Amazon region, Amazonia, Brazilian Amazonia, Composite products, 
                         Computational operations, Gradient pattern analysis, Land use and 
                         land cover change, LULC, Modis images, New approaches, Noise 
                         reductions, Phase disorder, Remote sensing images, Spatial 
                         temporals, Study areas, Symmetry-breaking, Wavelets transform.",
             abstract = "In this work, the computational operation based on Gradient 
                         Pattern Analysis - GPA was applied for the first time in MODIS 
                         spatial-temporal images over the Amazon region. The study area is 
                         located in the Par{\'a} State, eastern Brazilian Amazonia. Using 
                         MOD09 8-day composite product from 2000 to 2009 was elaborated the 
                         EVI2 spatial-temporal series of the study area. For each pixel we 
                         performed smooth time-series applying wavelets transform method 
                         for noise reduction. The GPA objective was characterizing small 
                         symmetry breaking, amplitude and phase disorder due to 
                         spatial-temporal fluctuations driven by the deforestation and 
                         flooded changes detected by MODIS images. For the characterization 
                         of spatial-temporal series the Gradient Pattern Analysis showed a 
                         new approach to understand LULC changes in the remote sensing 
                         images.",
  conference-location = "Honolulu",
      conference-year = "25-30 July 2010",
                  doi = "10.1109/IGARSS.2010.5650698",
                  url = "http://dx.doi.org/10.1109/IGARSS.2010.5650698",
                 isbn = "978-1-4244-9564-1 and 978-1-4244-9565-8",
                 issn = "2153-6996",
             language = "en",
         organisation = "IEEE",
           targetfile = "05650698.pdf",
        urlaccessdate = "30 abr. 2024"
}