@Article{GalvćoPonzLiesSant:2009:PoDiTr,
               author = "Galv{\~a}o, L{\^e}nio Soares and Ponzoni, Fl{\'a}vio Jorge and 
                         Liesenberg, Veraldo and Santos, Jo{\~a}o Roberto dos",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Possibilities of discriminating tropical secondary succession in 
                         Amaz{\^o}nia using hyperspectral and multiangular CHRIS/PROBA 
                         data",
              journal = "International Journal of Applied Earth Observation and 
                         Geoinformation",
                 year = "2009",
               volume = "11",
               number = "1",
                pages = "8--14",
             keywords = "Amaz{\^o}nia, CHRIS/PROBA, Hyperspectral, Multiangular, Secondary 
                         succession.",
             abstract = "CHRIS/PROBA data collected in the Brazilian Amaz{\^o}nia in 4 
                         view angles (-36°, nadir, +36°, +55°) and 62 bands (410-1000 nm 
                         range) were evaluated for the discrimination between primary 
                         forest and 3 stages of secondary succession after deforestation: 
                         initial (SS1; <5 years), intermediate (SS2; 5-15 years) and 
                         advanced (SS3; >15 years). Single view angle and multiangular 
                         approaches (nadir plus anisotropic information derived from 
                         reflectance ratios between view angles) were tested for 
                         discrimination. Both approaches used principal components analysis 
                         (PCA) applied to pixel spectra representative of each class in 
                         order to reduce data dimensionality at each dataset, to enhance 
                         separability between the classes, and to provide input variables 
                         for multiple discriminant analysis (MDA). The results showed that 
                         the off-nadir viewing improved discrimination between the 
                         successional stages. Discrimination between SS2 and SS3 was 
                         enhanced with PCA at +36° view angle. Primary forest and SS3 
                         presented a more anisotropic behavior than SS2 and SS1, especially 
                         in the backward scattering direction (positive view angles) in 
                         which great amounts of sunlit canopy components were viewed by the 
                         sensor. MDA classification results showed that the multiangular 
                         approach produced an overall improvement in the discrimination. 
                         From the single (nadir) to the multiangular approach, 
                         classification accuracy using a separate set of pixels increased 
                         from 83.3% to 98.3% for SS1, 53.3% to 70.0% for SS2, and 58.3% to 
                         76.7% for SS3. The nadir and multiangular classifications were 
                         statistically different at a 0.05% level of significance. Kappa 
                         statistics increased from 0.63 to 0.82. The results showed that 
                         multiangular data can improve the differentiation between primary 
                         forest and old stages of natural vegetation regrowth, which have 
                         been reported in the literature as the most difficult classes to 
                         be mapped in the Amazonian environment.",
                  doi = "10.1016/j.jag.2008.04.001",
                  url = "http://dx.doi.org/10.1016/j.jag.2008.04.001",
                 issn = "0303-2434",
             language = "en",
           targetfile = "lenio1.pdf",
        urlaccessdate = "27 abr. 2024"
}