@ElectronicSource{NumataRoChScGaSo::EvHyDa,
             abstract = "We used two hyperspectral sensors at two different scales to test 
                         their potential to estimate biophysical properties of grazed 
                         pastures in Rond{\^o}nia in the Brazilian Amazon. Using a field 
                         spectrometer, ten remotely sensed measurements (i.e., two 
                         vegetation indices, four fractions of spectral mixture analysis, 
                         and four spectral absorption features) were generated for two 
                         grass species, Brachiaria brizantha and Brachiaria decumbens. 
                         These measures were compared to above ground biomass, live and 
                         senesced biomass, and grass canopy water content. The sample size 
                         was 69 samples for field grass biophysical data and grass canopy 
                         reflectance. Water absorption measures between 1100 and 1250 nm 
                         had the highest correlations with above ground biomass, live 
                         biomass and canopy water content, while ligno-cellulose absorption 
                         measures between 2045 and 2218 nm were the best for estimating 
                         senesced biomass. These results suggest possible improvements on 
                         estimating grass measures using spectral absorption features 
                         derived from hyperspectral sensors. However, relationships were 
                         highly influenced by grass species architecture. B. decumbens, a 
                         more homogeneous, low growing species, had higher correlations 
                         between remotely sensed measures and biomass than B. brizantha, a 
                         more heterogeneous, vertically oriented species. The potential of 
                         using the Earth Observing-1 Hyperion data for pasture 
                         characterization was assessed and validated using field 
                         spectrometer and CCD camera data. Hyperion-derived NPV fraction 
                         provided better estimates of grass surface fraction compared to 
                         fractions generated from convolved ETM+/Landsat 7 data and 
                         minimized the problem of spectral ambiguity between NPV and Soil. 
                         The results suggest possible improvement of the quality of 
                         land-cover maps compared to maps made using multispectral sensors 
                         for the Amazon region. © 2007 Elsevier Inc. All rights reserved.",
              address = "S{\~a}o Jos{\'e} dos Campos",
          affiliation = "{} and {} and {} and {} and {} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
               author = "Numata, Izaya and Roberts, Dar and Chadwick, Oliver A. and 
                         Schimel, Josh and Galv{\~a}o, Leonio and Soares, J. V.",
             keywords = "Pasture biophysical characterization, Spectral absorption 
                         features, Hyperion, Spectral mixture analysis, Amazon.",
             language = "en",
       lastupdatedate = "2007-12-08",
            publisher = "Instituto and Nacional and de and Pesquisas and Espaciais",
                  ibi = "sid.inpe.br/mtc-m17@80/2007/12.07.18.06",
                  url = "http://urlib.net/ibi/sid.inpe.br/mtc-m17@80/2007/12.07.18.06",
           targetfile = "v1.pdf",
                title = "Evaluation of hyperspectral data for pasture estimate in the 
                         Brazilian Amazon using imaging spectrometers",
         typeofmedium = "On-line",
        urlaccessdate = "11 maio 2024"
}