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@Article{MouraHGGSLMS:2016:ScEsVe,
               author = "Moura, Yhasmin Mendes and Hilker, Thomas and Gon{\c{c}}alves, 
                         F{\'a}bio Guimar{\~a}es and Galv{\~a}o, L{\^e}nio Soares and 
                         Santos, Jo{\~a}o Roberto dos and Lyapustin, Alexei and Maeda, 
                         Eduardo Eiji and Silva, Camila Val{\'e}ria de Jesus",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Oregon 
                         State University} and {Agrosatelite Geotecnologia Aplicada} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {NASA Goddard Space 
                         Flight Center} and {University of Helsinki} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Scaling estimates of vegetation structure in Amazonian tropical 
                         forests using multi-angle MODIS observations",
              journal = "International Journal of Applied Earth Observation and 
                         Geoinformation",
                 year = "2016",
               volume = "52",
                pages = "580--590",
                month = "Oct.",
             keywords = "Canopy roughness, Multi-angle, MODIS, MAIAC, LiDAR, Anisotropy.",
             abstract = "Detailed knowledge of vegetation structure is required for 
                         accurate modelling of terrestrial ecosystems, but direct 
                         measurements of the three dimensional distribution of canopy 
                         elements, for instance from LiDAR, are not widely available. We 
                         investigate the potential for modelling vegetation roughness, a 
                         key parameter for climatological models, from directional 
                         scattering of visible and near-infrared (NIR) reflectance acquired 
                         from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). 
                         We compare our estimates across different tropical forest types to 
                         independent measures obtained from: (1) airborne laser scanning 
                         (ALS), (2) spaceborne Geoscience Laser Altimeter System 
                         (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results 
                         showed linear correlation between MODIS-derived anisotropy to 
                         ALS-derived entropy (r(2) = 0.54, RMSE = 0.11), even in high 
                         biomass regions. Significant relationships were also obtained 
                         between MODIS-derived anisotropy and GLAS-derived entropy (0.52 <= 
                         r(2) <= 0.61; p<0.05), with similar slopes and offsets found 
                         throughout the season, and RMSE between 0.26 and 0.30 (units of 
                         entropy). The relationships between the MODIS-derived anisotropy 
                         and backscattering measurements (sigma(0)) from SeaWinds/QuikSCAT 
                         presented an r(2) of 0.59 and a RMSE of 0.11. We conclude that 
                         multi-angular MODIS observations are suitable to extrapolate 
                         measures of canopy entropy across different forest types, 
                         providing additional estimates of vegetation structure in the 
                         Amazon.",
                  doi = "10.1016/j.jag.2016.07.017",
                  url = "http://dx.doi.org/10.1016/j.jag.2016.07.017",
                 issn = "0303-2434",
             language = "en",
           targetfile = "moura_scaling.pdf",
        urlaccessdate = "20 jan. 2021"
}


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