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@Article{BispoSanValTouSei:2014:InPoPA,
               author = "Bispo, Polyanna da Concei{\c{c}}{\~a}o and Santos, Jo{\~a}o 
                         Roberto dos and Valeriano, M{\'a}rcio de Morisson and Touzi, 
                         Ridha and Seifert, Frank Martin",
          affiliation = "{European Space Agency (ESA)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Canada Centre for Remote Sensing} and {European Space 
                         Agency (ESA)}",
                title = "Integration of polarimetric PALSAR attributes and local 
                         geomorphometric variables derived from SRTM for forest biomass 
                         modeling in central Amazonia",
              journal = "Canadian Journal of Remote Sensing",
                 year = "2014",
               volume = "40",
               number = "1",
                pages = "1--16",
                 note = "Setores de Atividade: Pesquisa e desenvolvimento 
                         cient{\'{\i}}fico, Atividades ligadas ao patrim{\^o}nio 
                         cultural e ambiental.",
             keywords = "Amaz{\^o}nia, sensoriamento remoto, vegeta{\c{c}}{\~a}o 
                         natural, RADAR, SRTM, geomorfometria.",
             abstract = "The objective of this work is to generate a predictive model for 
                         biomass estimation in a forested area of central Amazonia based on 
                         the integration of incoherent target scattering decomposition 
                         polarimetric attributes extracted from Phased Array type L-band 
                         Synthetic Aperture Radar (PALSAR) data and geomorphometric 
                         variables derived from Shuttle Radar Topography Mission (SRTM). In 
                         addition to their incorporation as variables of ecophysiological 
                         nature in biomass modeling, the geomorphometrics variables were 
                         also evaluated with regard to the possibility of minimization of 
                         topographic effects that affect the acquisition of PALSAR data. 
                         Based on the processed data, three biomass models were generated. 
                         The first model involves independent parameters extracted from 
                         polarimetric PALSAR data, the second includes the same 
                         polarimetric variables, which are additionally adjusted for the 
                         cosine factor effect. The third model integrates both the 
                         polarimetric parameters extracted from PALSAR and the 
                         geomorphometric variables derived from SRTM. The latter model 
                         showed the best results of biomass estimation among the models 
                         generated. Our results confirm the importance of geomorphometric 
                         variables as additional input in prognostic biomass models that 
                         use radar remote sensing, in this case L band, because of their 
                         causal relationship with ecophysiological aspects that condition 
                         the growth of forest communities and because of minimization of 
                         the terrain effects on the radar signal.",
                  doi = "10.1080/07038992.2014.913477",
                  url = "http://dx.doi.org/10.1080/07038992.2014.913477",
                 issn = "1712-7971",
                label = "lattes: 8678564148136140 3 BispoSanValTouSei:2014:InPoPA",
             language = "pt",
                  url = "http://www.tandfonline.com/doi/full/10.1080/07038992.2014.913477#preview",
        urlaccessdate = "29 nov. 2020"
}


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