@Article{PereiraFreSanLuMor:2013:OpRaDa,
               author = "Pereira, Luciana de Oliveira and Freitas, Corina da Costa and 
                         Sant'Anna, Sidnei Jo{\~a}o Siqueira and Lu, Dengsheng and Moran, 
                         Emilio F.",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         Anthropological Center for Training and Research on Global 
                         Environmental Change (ACT), Indiana University , Bloomington , IN 
                         , USA and Anthropological Center for Training and Research on 
                         Global Environmental Change (ACT), Indiana University , 
                         Bloomington , IN , USA",
                title = "Optical and radar data integration for land use and land cover 
                         mapping in the Brazilian Amazon",
              journal = "GIScience and Remote Sensing",
                 year = "2013",
               volume = "50",
               number = "3",
                pages = "301--321",
             keywords = "optical sensors, SAR, image fusion, LULC, Brazilian Amazon.",
             abstract = "This study aims to evaluate different methods of integrating 
                         optical and multipolarized radar data for land use and land cover 
                         (LULC) mapping in an agricultural frontier region in the Central 
                         Brazilian Amazon, which requires continuous monitoring due to the 
                         increasing human intervention. The evaluation is performed using 
                         different sets of fused and combined data. This article also 
                         proposes to apply the principal component (PC) technique to the 
                         multipolarized synthetic aperture radar (SAR), prior to the 
                         optical and radar data PC fusion process, aiming at the use of all 
                         available polarized information in the fusion process. Although 
                         the fused images improve the visual interpretation of the land use 
                         classes, the best results are achieved with the simple combination 
                         of the Advanced Land Observing Satellite (ALOS)/phased array 
                         L-Band SAR (PALSAR) with the LANDSAT5/Thematic Mapper (TM) images. 
                         Radar information is found to be particularly useful for improving 
                         the user accuracies (UAs) of Soybean with 40 days after seeding 
                         (an increase of about 55%), Dirty Pasture (22%), Degraded Forest 
                         and Regeneration (5%), and the producer accuracies (PAs) of Clean 
                         Pasture (39%), Fallow Agriculture (16%), Degraded Forest and 
                         Regeneration (3%), and Primary Forest (2%). Information from the 
                         HH (horizontal transmit and horizontal receive) polarization 
                         contributes more than that from HV (horizontal transmit and 
                         vertical receive) polarization to discriminate the classes, 
                         although the use of both polarizations produces results that are 
                         statistically better than those obtained with a single 
                         polarization.",
                  doi = "10.1080/15481603.2013.805589",
                  url = "http://dx.doi.org/10.1080/15481603.2013.805589",
                 issn = "1548-1603",
             language = "en",
           targetfile = "oliveira optical.pdf",
        urlaccessdate = "28 abr. 2024"
}