@Article{LuLiMorBatFre:2011:CaStUr,
               author = "Lu, Dengsheng and Li, Guiying and Moran, Emilio and Batistella, 
                         Mateus and Freitas, Corina da Costa",
          affiliation = "Anthropological Center for Training and Research on Global 
                         Environmental Change (ACT), Indiana University, Bloomington, IN 
                         47405, USA and Anthropological Center for Training and Research on 
                         Global Environmental Change (ACT), Indiana University, 
                         Bloomington, IN 47405, USA and Anthropological Center for Training 
                         and Research on Global Environmental Change (ACT), Indiana 
                         University, Bloomington, IN 47405, USA and Embrapa Satellite 
                         Monitoring, Av. Julio Soares de Arruda, 803, Campinas, SP 
                         13088-300, Brazil and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Mapping impervious surfaces with the integrated use of Landsat 
                         Thematic Mapper and radar data: A case study in an urban rural 
                         landscape in the Brazilian Amazon",
              journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
                 year = "2011",
               volume = "66",
               number = "6",
                pages = "798--808",
                month = "Nov.",
             keywords = "Landsat TM, ALOS PALSAR, L-band, RADARSAT-2, C-band, 
                         Wavelet-merging technique, Spectral mixture analysis, Impervious 
                         surface.",
             abstract = "This research explored the integrated use of Landsat Thematic 
                         Mapper (TM) and radar (i.e., ALOS PALSAR L-band and RADARSAT-2 
                         C-band) data for mapping impervious surface distribution to 
                         examine the roles of radar data with different spatial resolutions 
                         and wavelengths. The wavelet-merging technique was used to merge 
                         TM and radar data to generate a new dataset. A constrained 
                         least-squares solution was used to unmix TM multispectral data and 
                         multisensor fusion images to four fraction images (high-albedo, 
                         low-albedo, vegetation, and soil). The impervious surface image 
                         was then extracted from the high-albedo and low-albedo fraction 
                         images. QuickBird imagery was used to develop an impervious 
                         surface image for use as reference data to evaluate the results 
                         from TM and fusion images. This research indicated that increasing 
                         spatial resolution by multisensor fusion improved spatial patterns 
                         of impervious surface distribution, but cannot significantly 
                         improve the statistical area accuracy. This research also 
                         indicated that the fusion image with 10-m spatial resolution was 
                         suitable for mapping impervious surface spatial distribution, but 
                         TM multispectral image with 30 m was too coarse in a complex 
                         urban-rural landscape. On the other hand, this research showed 
                         that no significant difference in improving impervious surface 
                         mapping performance by using either PALSAR L-band or RADARSAT 
                         C-band data with the same spatial resolution when they were used 
                         for multi-sensor fusion with the wavelet-based method.",
                  doi = "10.1016/j.isprsjprs.2011.08.004",
                  url = "http://dx.doi.org/10.1016/j.isprsjprs.2011.08.004",
                 issn = "0924-2716",
                label = "lattes: 2549014594120288 5 LuLiMorBatFre:2011:CaStUr",
             language = "en",
           targetfile = "lu.pdf",
        urlaccessdate = "16 jun. 2024"
}