@Article{AdamsSaKaAlRoSmGi:1995:ApLaCh,
               author = "Adams, John B. and Sabol, Donald E. and Kapos, Valerie and Almeida 
                         Filho, Raimundo and Roberts, Dar A. and Smith, Milton O. and 
                         Gillespie, Gillespie R.",
          affiliation = "Department of Geological Sciences, University of Washington, 
                         Seattle, WA 98195 and Department of Geological Sciences, 
                         University of Washington, Seattle, WA 98195 and Department of 
                         Plant Sciences, University of Cambridge, Cambridge, UK and {} and 
                         Department of Geological Sciences, University of Washington, 
                         Seattle, WA 98195 and Department of Geological Sciences, 
                         University of Washington, Seattle, WA 98195 and Department of 
                         Geological Sciences, University of Washington, Seattle, WA 98195",
                title = "Classification of multispectral images based on fractions of 
                         endmembers: application to land-cover change in the Brazilian 
                         Amazon",
              journal = "Remote Sensing of Environment",
                 year = "1995",
               volume = "52",
               number = "2",
                pages = "137--154",
             keywords = "endmember, land cover, TM, vegetation, Brazil, Manaus.",
             abstract = "Four time-sequential Landsat Thematic Mapper (TM)images of an area 
                         of Amazon forest, pasture, and second growth near Manaus, Brazil 
                         were classified according to dominant ground cover, using a new 
                         technique based on fractions of spectral endmembers. A simple 
                         four-endmember model consisting of reflectance spectra of green 
                         vegetation, nonphotosynthetic vegetation, soil, and shade was 
                         applied to all four images. Fractions of endmembers were used to 
                         define seven categories, each of which consisted of one or more 
                         classes of ground cover, where class names were based on field 
                         observations. Endmember fractions varied over time for many pixels 
                         reflecting processes operating on the ground such as felling of 
                         forest, or regrowth of vegetation in previously cleared areas. 
                         Changes in classes over time were used to establish superclasses 
                         which grouped pixels having common histories. Sources of 
                         classification error were evaluated, including system noise, 
                         endmember variability, and low spectral contrast. Field work 
                         during each of the four years showed consistently high accuracy in 
                         per-image classification. Classification accuracy in any one year 
                         was improved by considering the multiyear context. Although the 
                         method was tested in the Amazon basin, the results suggest that 
                         endmember classification may be generally useful for comparing 
                         multispectral images in space and time.",
           copyholder = "SID/SCD",
                  doi = "10.1016/0034-4257(94)00098-8",
                  url = "http://dx.doi.org/10.1016/0034-4257(94)00098-8",
                 issn = "0034-4257",
                label = "7318",
             language = "en",
           targetfile = "UW Remote Sensing Lab - Amazon Paper.htm",
        urlaccessdate = "23 maio 2024"
}