@InProceedings{SilvaLimFonNovRib:2007:AsImRe,
               author = "Silva, Thiago Sanna Freire and Lima, Andr{\'e} de and Fonseca, 
                         Leila Maria Garcia and Novo, Evlyn M{\'a}rcia Le{\~a}o de Moraes 
                         and Ribeiro, Milton Cezar",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE). University of 
                         Victoria. Department of Geography.} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)} and {Universidade de S{\~a}o Paulo (USP). Instituto de 
                         Bioci{\^e}ncias (IB).}",
                title = "Assessment of image restoration techniques to enhance the 
                         applicability of MODIS images on Amazon floodplain landscape 
                         studies",
            booktitle = "Anais...",
                 year = "2007",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Galv{\~a}o, L{\^e}nio 
                         Soares and Fonseca, Leila Maria Garcia",
                pages = "6969--6976",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 13. (SBSR).",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "MODIS, remote sensing, Amazon floodplain, image restoration, 
                         spatial resolution, sensoriamento remoto, plan{\'{\i}}cie de 
                         inunda{\c{c}}{\~a}o Amaz{\^o}nica, restaura{\c{c}}{\~a}o de 
                         imagens, resolu{\c{c}}{\~a}o espacial.",
             abstract = "The Amazon floodplain represents a significant portion of the 
                         worlds wetlands, and participates actively in the carbon cycling 
                         in the region. Due to its large extent, remote sensing is the most 
                         appropriate tool for studying the Amazonian landscape; image 
                         acquisition, however, is highly hindered by the frequent cloud 
                         cover. Medium resolution sensors such as MODIS can overcome this 
                         problem with a larger swath and high frequency of image 
                         acquisition, at the expense of spatial resolution. In the present 
                         study, MODIS images were submitted to an image restoration 
                         algorithm (RESTAU), to assess the capability of this technique for 
                         recovering the spatial detail lost due to the sensor PSF 
                         characteristics. Landsat TM and MODIS Aqua reflectance images were 
                         acquired for a region of the central Amazon during the high water 
                         season. These images were co-registered and the MODIS imagery was 
                         submitted to the restoration algorithm. Two sets of TM and MODIS 
                         images were then analyzed visually and by the calculation of 
                         landscapes indices (i.e. area, shape and patch aggregation). The 
                         results show that image restoration can improve the spatial 
                         information content of MODIS imagery as whole, but gains are more 
                         effective towards area estimations, whereas mapping of shape is 
                         still highly affected by scale even after application of the 
                         algorithm. Overall, it is suggested that use of image restoration 
                         could increase the applicability of MODIS as a tool for area 
                         estimations and continuous monitoring of floodplain cover, while 
                         accurate delineation of shape still requires higher resolution 
                         data to yield acceptable accuracies.",
  conference-location = "Florian{\'o}polis",
      conference-year = "21-26 abr. 2007",
           copyholder = "SID/SCD",
                 isbn = "978-85-17-00031-7",
             language = "en",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "dpi.inpe.br/sbsr@80/2006/11.23.11.20",
                  url = "http://urlib.net/ibi/dpi.inpe.br/sbsr@80/2006/11.23.11.20",
           targetfile = "6969-6976.pdf",
                 type = "Sensoriamento Remoto da Amaz{\^o}nia",
        urlaccessdate = "10 maio 2024"
}