@Article{CostaNiemNovoAher:2002:BiPrMa,
               author = "Costa, Maycira Pereira de Farias and Niemann, O. and Novo, Evlyn 
                         M{\'a}rcia Le{\~a}o de Moraes and Ahern, F",
                title = "Biophysical properties and mapping of aquatic vegetation during 
                         the hydrological cycle of the Amazon floodplain using JERS-1 and 
                         Radarsat",
              journal = "International Journal of Remote Sensing",
                 year = "2002",
               volume = "23",
               number = "7",
                pages = "1401--1426",
                month = "Apr.",
             keywords = "ESTUDOS INTEGRADOS DO MEIO AMBIENTE, Amaz{\^o}nia (Regi{\~a}o), 
                         plantas aqu{\'a}ticas, biomassa, ciclo hidrol{\'o}gico, 
                         plan{\'{\i}}cies inundadas, imagens de radar, 
                         classifica{\c{c}}{\~a}o de imagens, mapeamento, radar de 
                         abertura sintetica, SAR, forestas, JERS 1, biomass, synthetic 
                         aperture radar, forest, rice, canopy, aquatic plants, hydrological 
                         cycle, food plains, radar imagery, image classification, 
                         mapping.",
             abstract = "Field measurements were combined with Synthetic Aperture Radar 
                         (SAR)images to evaluate the use of radar for estimating biomass 
                         changes and mapping of aquatic vegetation in the lower Amazon. 
                         Field campaigns were conducted concomitant to the acquisition of 
                         Radarsat and JERS-1 images at five different stages of the 
                         hydrological cycle. The temporal variability of the SAR data for 
                         aquatic vegetation shows a dynamic range of 5 dB, however this is 
                         due dominantly to the significant differences (p<0.05)between the 
                         low water season when vegetation is small and just emerging and 
                         other seasons when vegetation is fully developed. The spatial 
                         variability of the above-water biomass is detectable with radar 
                         data. Significant correlation (p<0.05)exist between backscattering 
                         coefficients and both above-water dry biomass and height of the 
                         plants. The logarithmic relationship between backscattering 
                         coefficients and biomass suggests that (1)at low biomass, high 
                         transmissivity of the microwave radiation through the vegetation 
                         canopy occurs and the backscattering is a result of quasi-specular 
                         reflection of both C and L bands and a minor contribution of 
                         canopy volume scattering from C band; (2)at intermediate levels of 
                         biomass, moderate changes in backscattering values occur and the 
                         saturation point of backscattering is reached; and (3)at high 
                         biomass, the transmissivity of C and L band radiation is equally 
                         attenuated and backscattering approaches similar values for both. 
                         A combination of Radarsat and JERS-1 images from high and low 
                         water periods were classified using a segmentation algorithm and 
                         had an accuracy higher than 97 percent for vegetated areas of the 
                         floodplain. Although further research is needed to better 
                         understand the saturation points for Radarsat and JERS-1 data, 
                         these findings clearly show that C and L bands can accurately map 
                         aquatic vegetation of the Amazon floodplain.",
           copyholder = "SID/SCD",
                 issn = "0143-1161",
                label = "9556",
           targetfile = "INPE 8579.pdf",
        urlaccessdate = "20 maio 2024"
}