@Article{HaertelShimAlme:2004:FrImMu,
               author = "Haertel, Victor F. and Shimabukuro, Yosio Edemir and Almeida 
                         Filho, Raimundo",
          affiliation = "Universidade Federal do Rio Grande do Sul, Center for Remote 
                         Sensing, Porto Alegre, Brazil and Instituto Nacional de Pesquisas 
                         Espaciais, Divis{\~a}o de Sensoriamento Remoto(INPE,DSR)",
                title = "Fraction images in multitemporal change detection",
              journal = "International Journal of Remote Sensing",
                 year = "2004",
               volume = "25",
               number = "23",
                pages = "5473 - 5489",
                month = "Dec.",
             keywords = "Image analysis, Satellites, Fraction images, Land-covers, Remote 
                         sensing, digital image, image classification, land cover, Landsat 
                         thematic mapper, pixel, remote sensing.",
             abstract = "The concept of mixed pixels allows the interpretation of remote 
                         sensing digital image data at sub-pixel level. Fraction-image 
                         data, obtained using the notion of mixed pixels, offer a 
                         potentially powerful method to detect changes in land-cover over a 
                         given period of time. This study proposes a new approach to detect 
                         land-cover changes, using two sets of fraction-image data obtained 
                         from sets of multispectral image data acquired at two different 
                         dates, over the same area. Changes based on the selected pixel 
                         components are then used to generate the fraction-change image 
                         data, including both positive (increase) and negative (decrease) 
                         changes in each component. The proposed analysis is then performed 
                         in the fraction-change space in two different ways: (1) by 
                         implementing unsupervised classification methods and (2) by 
                         comparing the fraction-change images among themselves. The 
                         proposed methodology is tested on two sets of Landsat Thematic 
                         Mapper (TM) multispectral image data obtained at two different 
                         dates and covering a test area mapped in previous works. Results 
                         obtained by the proposed methodology are presented and 
                         discussed.",
           copyholder = "SID/SCD",
                  doi = "10.1080/01431160412331269751",
                  url = "http://dx.doi.org/10.1080/01431160412331269751",
                 issn = "0143-1161",
             language = "en",
           targetfile = "raimundo3.pdf",
        urlaccessdate = "12 maio 2024"
}