@Article{HaertelShim:2005:SpLiMi,
               author = "Haertel, V. F and Shimabukuro, Yosio Edemir",
          affiliation = "Center for Remote Sensing, Federal University at Rio Grande do 
                         Sul, Porto Alegre, RS, 91501-970, Brazil and Instituto Nacional de 
                         Pesquisas Espaciais, Divis{\~a}o de Sensoriamento Remoto (INPE, 
                         DSR)",
                title = "Spectral linear mixing model in low spatial resolution image 
                         data",
              journal = "IEEE Transactions on Geoscience and Remote Sensing",
                 year = "2005",
               volume = "43",
               number = "11",
                pages = "2555--2562",
                month = "Nov.",
             keywords = "Landset Enhanced Thematic Mapper Plus, Low spatial resolution 
                         image data, Mixed pixels, Spectral reflectance, Mathematical 
                         models, Mixtures, Optical resolving power, Radiometers, Spectrum 
                         analyzers, Image analysis.",
             abstract = "Different ways to estimate the spectral reflectance for the 
                         component classes in a mixture problem have been proposed in the 
                         literature (pure pixels, spectral library, field measurements). 
                         One of the most common approaches consists in the use of pure 
                         pixels, i.e., pixels that are covered by a single component class. 
                         This approach presents the advantage of allowing the extraction of 
                         the components' reflectance directly from the image data. This 
                         approach, however, is generally not feasible in the case of low 
                         spatial resolution image data, due to the large ground area 
                         covered by a single pixel. In this paper, a methodology aiming to 
                         overcome this limitation is proposed. The proposed approach makes 
                         use of the spectral linear mixing model. In the proposed 
                         methodology, the components' proportions in image data are 
                         estimated using a medium spatial resolution image as auxiliary 
                         data. The linear mixing model is then solved for the unknown 
                         spectral reflectances. Experiments are presented, using Terra 
                         Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 
                         Enhanced Thematic Mapper Plus, as low and medium spatial 
                         resolution image data, respectively, acquired on the same date 
                         over the Tapajos study site, Brazilian Amazon. Three component 
                         classes or endmembers are present in the scene covered by the 
                         experiment, namely vegetation, exposed soil, and shade. The 
                         components' spectral reflectance for the Terra MODIS spectral 
                         bands were then estimated by applying the proposed methodology. 
                         The reliability of these estimates is appraised by analyzing 
                         scatter diagrams produced by the Terra MODIS spectral bands and 
                         also by comparing the fraction images produced using both image 
                         datasets. This methodology appears appropriate for up-scaling 
                         information for regional and global studies.",
           copyholder = "SID/SCD",
                  doi = "10.1109/TGRS.2005.848692",
                  url = "http://dx.doi.org/10.1109/TGRS.2005.848692",
                 issn = "0196-2892",
             language = "en",
           targetfile = "spectral linear.pdf",
        urlaccessdate = "23 maio 2024"
}