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@InProceedings{MouraHIGaSaLySo:2015:UsMuIm,
               author = "Moura, Yhasmin Mendes de and HIlker, Thomas and Galv{\~a}o, 
                         L{\^e}nio Soares and Santos, Jo{\~a}o Roberto dos and Lyapustin, 
                         Alexei and Sousa, Celio Helder Resende de",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Using Multi-Angle Implementation of Atmospheric Correction (MODIS) 
                         to characterize anisotropy in the Amazonian forests",
            booktitle = "Anais...",
                 year = "2015",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "2459--2467",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 17. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The objective of this work is to present initial results of a new 
                         method to evaluate vegetation patterns in the Amazon rainforests 
                         based on multi-angle satellite observations. We used MODIS 
                         Enhanced Vegetation Index (EVI) data processed by MAIAC algorithm 
                         to generate anisotropy, calculated by the differences between 
                         hotspot and darkspot reflectance. We compared Anisotropy with EVI 
                         using two images (June 2008), both processed by MAIAC, to 
                         demonstrate the potential of using anisotropy for mapping 
                         vegetation structure of different forests types. We also analyzed 
                         seasonal variability between anisotropy and EVI, and compared our 
                         findings with variability of monthly water deficit for the region. 
                         Finally, we discussed the use of anisotropy to infer 
                         spatial-temporal changes in vegetation structure. The results 
                         showed larger spatial variability of anisotropy, while EVI varied 
                         only to a limited extend across the study area. The regional 
                         differences in anisotropy may therefore better represent the 
                         structural heterogeneity across forested areas in the Amazon, 
                         based on the interaction of vegetation with multi-angle 
                         scattering. Seasonal changes were more gradual when using 
                         Anisotropy compared to using EVI. This gradient transition across 
                         months is in good agreement with water deficit patterns derived 
                         from the Tropical Rainfall Measurement Mission (TRMM). Our study 
                         hypothesizes that multiangular information are useful sources to 
                         analyze structural changes in different types of forests, and may 
                         provide new opportunities to monitor tropical forests, from 
                         optical remote sensing.",
  conference-location = "Jo{\~a}o Pessoa",
      conference-year = "25-29 abr. 2015",
                 isbn = "978-85-17-0076-8",
                label = "493",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3JM4A3C",
                  url = "http://urlib.net/rep/8JMKD3MGP6W34M/3JM4A3C",
           targetfile = "p0493.pdf",
                 type = "Floresta e vegeta{\c{c}}{\~a}o",
        urlaccessdate = "21 jan. 2021"
}


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