@InProceedings{AmaralAGWMPS:2017:MoSpAb,
               author = "Amaral, Cibele Hummel do and Arag{\~a}o, Luiz Eduardo Oliveira e 
                         Cruz de and Galv{\~a}o, L{\^e}nio Soares and Wu, Jin and 
                         memoriam, Thomas Hilker - In and Moura, Yhasmin Mendes de and 
                         Prohaska, Neil and Saleska, Scott Reid",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {} and {} 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Monitoring the species-specific absorption of solar energy by 
                         chlorophyll through near-surface imaging spectroscopy in central 
                         eastern Amazon",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "5620--5627",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "The aim of this research was to monitor the amount of solar energy 
                         absorbed by chlorophyll at branch scale during the dry season, in 
                         a central eastern Amazonian evergreen forest, and verify how 
                         broadband and narrowband vegetation indices, as well as canopy 
                         fractions can be used for monitoring the absorption of energy by 
                         chlorophyll at the species level. Seventeen hyperspectral images 
                         (385-1050 nm, ~ 4 nm spectral resolution), which were acquired 
                         from a tower-mounted camera (late July to late September, 2012), 
                         were used in this study. Seven vegetation indices, three canopy 
                         fractions (green vegetation, GV, non-photosynthetic vegetation, 
                         NPV, and shade fractions), and the depth of the chlorophyll 
                         absorption band, were calculated for three tree species in the 
                         camera image: Chamaecrista xinguensis (CHXI), Erisma uncinatum 
                         (ERUN) and Manilkara huberi (MAHU). Each individual (and species) 
                         displays a distinct phenological behavior, and ERUN has the 
                         highest values and the lowest variation of chlorophyll absorption 
                         band depth during the studied period. Our results show that the 
                         dry season changes in chlorophyll absorption band depth are not 
                         correlated with the shade fraction; instead, it can be explained 
                         by the dry season variations in GV and NPV, as well as by three 
                         vegetation indices: Normalized Difference Vegetation Index (NDVI), 
                         Enhanced Vegetation Index (EVI) and Plant Senescence Reflectance 
                         Index (PSRI). Although NDVI and EVI are more consistent during the 
                         time, only NDVI and PSRI are correlated with the absorption of the 
                         electromagnetic energy by chlorophyll within the studied crowns 
                         (and species).",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "59332",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMBE3",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMBE3",
           targetfile = "59332.pdf",
                 type = "Sensoriamento remoto hiperespectral",
        urlaccessdate = "27 abr. 2024"
}