@InProceedings{ShimabukuroAndeAragHuet:2006:UsFrIm,
               author = "Shimabukuro, Yosio Edemir and Anderson, Liana O. and Arag{\~a}o, 
                         Luiz Eduardo Oliveira e Cruz de and Huete, Alfredo Ramon",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais. Divis{\~a}o de 
                         Sensoriamento Remoto} and {} and University of Oxford, Centre for 
                         the Environment, Dyson Perrins Building, South Parks Road, Oxford 
                         OX1 3QY, United Kingdom and University of Arizona, Dept. of Soil, 
                         Water and Environmental Sciences, Shantz Bldg. 38, 1200 E. South 
                         Campus Dr., Tucson, AZ 85721-0038, United States",
                title = "Using fraction images to study natural land cover changes in the 
                         Amazon",
            booktitle = "Proceedings...",
                 year = "2006",
                pages = "2103 - 2106",
         organization = "International Geoscience and Remote Sensing Symposium (IGARSS); 
                         Canadian Symposium on Remote Sensing, 28.",
            publisher = "IEEE",
             keywords = "vegeta{\c{c}}{\~a}o, Amaz{\^o}nia, Mato Grosso (Estado), 
                         phenology, fraction image, vegetation indices, sensor MODIS, 
                         Normalized Difference Vegetation Index (NDVI).",
             abstract = "Satellite data such as the vegetation indices are a crucial tool 
                         for studying vegetation phenology patterns from regional to global 
                         scales. In this study, we investigated the relationship of the 
                         fraction images, derived from the linear spectral mixture model, 
                         with the NDVI and EVI, the most used indices to evaluate the 
                         phenological response using remote sensing data from the MODIS 
                         sensor. Our objectives were to understand how the vegetation 
                         indices are related with the vegetation fraction and to evaluate 
                         if the information provided by the shade and soil fraction images 
                         can be used to explain the vegetation indices behavior. We used a 
                         temporal series data of the MOD13A1 product for the 2002 year, the 
                         precipitation data from 125 meteorological stations, and a land 
                         cover map generated based on the 2002 images. We studied two 
                         different vegetation physiognomies to analyse if the fraction 
                         images were landscape dependent. Our results showed that for the 
                         Open Tropical Forest, the vegetation fraction image presented a 
                         significant correlation with the EVI (r2=0.84) but not with the 
                         NDVI. For the Cerrado grassland landscape, the vegetation fraction 
                         image presented high correlation with the NDVI (r2=0.93) and EVI 
                         (r2=0.98). Significant correlations were also found for the shade 
                         and soil fraction images for the land cover studied, showing that 
                         these additional information are a useful source of data to 
                         understand the vegetation canopy structural changes and to analyze 
                         the responses provided by the vegetation indices correctly.",
  conference-location = "Denver",
      conference-year = "31 July - 4 Aug.",
           copyholder = "SID/SCD",
                  doi = "10.1109/IGARSS.2006.544",
                  url = "http://dx.doi.org/10.1109/IGARSS.2006.544",
                 isbn = "{0780395107;978-078039510-7}",
             language = "en",
         organisation = "IEEE Geoscience and Remote Sensing Society,Canadian Remote Sensing 
                         Society,National Aeronautics and Space Administration, 
                         NASA,National Oceanic and Atmospheric Administration,Office of 
                         Naval Research",
           targetfile = "03_11A09.pdf",
        urlaccessdate = "14 maio 2024"
}