@InProceedings{FreitasShimRosa:2007:WaTrLi,
               author = "Freitas, Ramon Morais de and Shimabukuro, Yosio Edemir and Rosa, 
                         Reinaldo Roberto",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Wavelets Transform and Linear Spectral Mixture Model applied to 
                         MODIS time series for land cover change analysis",
            booktitle = "Proceedings...",
                 year = "2007",
                pages = "1951--1954",
         organization = "International Geoscience and Remote Sensing Symposium (IGARSS)",
            publisher = "IEEE",
             keywords = "Wavelet transforms, Image analysis, Land use, Mathematical models, 
                         Precipitation (meteorology), Time series analysis, Land cover 
                         change analysis, Linear Spectral Mixture Models.",
             abstract = "This work presents a methodology that uses fraction images derived 
                         from Linear Spectral Mixture Model and wavelets transform from 
                         MODIS time-series for land cover change analysis. Our approach 
                         uses MODIS/Terra surface reflectance images acquired from 2000 to 
                         2006 time period. For this study, a test site was selected in the 
                         Mato Grosso State, Brazilian Amazonia, encompassing several 
                         landscape types as tropical forest, savanna, transitional forest, 
                         regrowth, deforested areas, croplands and pasture. The samples of 
                         land cover classes were collected during four field campaigns 
                         (2003, 2004, 2005, and 2006) to be used as ground truth. The 
                         linear spectral mixture model was applied to the MODIS surface 
                         reflectance images of RED, NIR and MIR spectral bands. This model 
                         generated the vegetation, shade, and soil fraction images. In the 
                         next step, the Meyer orthogonal Discrete Wavelets Transform was 
                         used for filtering the time-series of MODIS fraction images. The 
                         filtered signal was reconstructed excluding high frequencies for 
                         each pixel in the fraction images (soil, vegetation, and shade) of 
                         the time-series. This procedure allows to observe the original 
                         signal without clouds and other noises. The accumulated 
                         precipitation data were used for dynamic phenological analysis, 
                         which showed the temporal lags between wet season and vegetation 
                         growing stages. The results show that wavelets transform can 
                         provide a gain in multitemporal analysis and visualization on 
                         inter-annual fraction images variability patterns.",
  conference-location = "Barcelona, Espanha",
      conference-year = "23 - 27 de julho.",
                  doi = "10.1109/IGARSS.2007.4423209",
                  url = "http://dx.doi.org/10.1109/IGARSS.2007.4423209",
                 isbn = "{1424412129;978-142441212-9 09}",
             language = "en",
           targetfile = "ramon morais freitas.pdf",
        urlaccessdate = "10 maio 2024"
}