@Article{Paradella:1994:FrImDe,
               author = "Paradella, Waldir Renato",
                title = "Fraction images derived from NOAA AVHRR data for studying the 
                         deforestation in the brazilian Amazon",
              journal = "Inform{\'a}tica P{\'u}blica",
                 year = "1994",
               volume = "15",
               number = "3",
                pages = "517--520",
             keywords = "GEOLOGIA.",
             abstract = "Fraction images derived from National Oceanic and Atmospheric 
                         Administrations (NOAA)Advenced Very High Resolution Radiometer 
                         (AVHRR)imsgrs contain useful information for studying tropical 
                         deforestation. Vegetation,soil and shade fraction images are 
                         formed by the proportion amount od each component within the 
                         pixel. These values are estimated using the two reflective 
                         channels (0-58-0-68 um and 0-725-1.1 um)and the reflective 
                         component of the 3.55-3.95 um channel (Kaufman and Nakajima 1993, 
                         Kaufman and Remer 1993). The endmenbers for AVHRR image to run the 
                         Constrained Least Squares (CLS)Metrod (Shimabukuro nand Smith 
                         1991)were estimated using the fraction images derived from 
                         Landasat Thematic Mapper (TM)as a ground trutth as presented by 
                         Holben and Shimabukuro (1993).Figures 1 and 2 show teh color 
                         composite (Vegetation=Red,Soil=Gren andShade=Blue)of the fraction 
                         images and NDVI image, respectively for AVHRR data acquired on 26 
                         July 1988 over the Rondonia State in the Brazilian Amazon. Figures 
                         3 and 4 show the composite fraction and NDVI images, respectively 
                         obtained from AVHRR( 26 July 1988)and TM ( 8 August 1988)for the 
                         same region.The NDVI images are very similar to vegetaion fraction 
                         images and are highly correlates with the fraction images for both 
                         remote sensors.",
                 issn = "1516-697X",
                label = "6830",
           targetfile = "INPE 7637.pdf",
        urlaccessdate = "21 maio 2024"
}