@InProceedings{Bernardes:1994:UtLiMi,
               author = "Bernardes, Sergio",
                title = "Utilization of linear mixing model applied to Landsat-TM data to 
                         characterize brazilian Amazon forest",
            booktitle = "Abstracts...",
                 year = "1994",
                pages = "27",
         organization = "Symposium on Resource and Environmental Monitoring.",
             abstract = "The necessity to provide periodical studies of the amazon region, 
                         characterizing its natural resources and anthropic alteration 
                         processes is a source of several Remote Sensing studies, many of 
                         them applying digital image processing techniques. Conventional 
                         methods of image classification underline, predominantly, in the 
                         spectral characteristics of the pixels, understanding them as 
                         composed by a single class of a land cover. Usually, a digital 
                         number results from integration of the responses of many targets 
                         in the ground. In this way, the signal produced by the 
                         combination, in one pixel, of two or more classes of land cover 
                         will not representative of none of them, resulting in a 
                         misunderstood classification. Therefore the spectral mixture is a 
                         limiting factor in a automatic classification approach. The aim of 
                         this work is to evaluate the use of synthetic images, obtained by 
                         a Linear Mixing Model, to characterize Brazilian amazon 
                         vegetation. The study area consists of approximately 690 Km of the 
                         Brazilian amazon, situated in the forest/savana 
                         ({"}cerrado{"})contact region, between 11R00'S and 51R00'W to 
                         52R30'W. For the methodology implementation, a visual 
                         interpretation of Landsat-TM data was performed, identifying 
                         classes of land cover (forest, second growth forest, savanna, bare 
                         soil, ...). A Linear Mixing Model was applied to generate three 
                         synthetic images ({"}vegetation{"}, {"}soil{"} and {"}shade{"}). 
                         These images will be classified using a maximum likelihood 
                         algorithm. The product of this approach will be compared with the 
                         visual interpretation in a geographic information system, 
                         generating an error matrix. Kappa coefficient of agreement will be 
                         used to determine the classification accuracy obtained with the 
                         application of this methodology. In this way, this work intends to 
                         contribute to future space-time analysis of the large amazon 
                         region, estimating deforesting and monitoring land occupation.",
  conference-location = "Rio de Janeiro",
      conference-year = "26-30 Sept.1994",
                label = "7699",
         organisation = "ISSPRS Commission VII",
           targetfile = "INPE 6362.pdf",
        urlaccessdate = "30 abr. 2024"
}