@InProceedings{LatorreCarvShim:2003:AbGeSo,
               author = "Latorre, Marcelo Lopes and Carvalho, Osmar Ab{\'{\i}}lio de and 
                         Shimabukuro, Yosio Edemir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE). Instituto de 
                         Estudos Avan{\c{c}}ados (IEAv).} and {Universidade de 
                         Bras{\'{\i}}lia (UnB). Departamento de Geografia.} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Uma abordagem geral sobre um modelo de corre{\c{c}}{\~a}o 
                         atmosf{\'e}rica aplicado ao sensoriamento remoto hiperespectral",
            booktitle = "Anais...",
                 year = "2003",
               editor = "Epiphanio, Jos{\'e} Carlos Neves and Fonseca, Leila Maria 
                         Garcia",
                pages = "1069--1076",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 11. (SBSR).",
            publisher = "INPE",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "Hyperspectral Remote Sensing, atmospheric correction.",
             abstract = "In the last two decades a new phase of data acquisition has 
                         appeared. It is denominated Hyperspectral Remote Sensing or 
                         Espectrometry by Imaging. This is a new concept of sensor system, 
                         which has overcome the known multispectral sensor. While these is 
                         base on the use of some areas of the spectrum, the Hyperspectral 
                         instruments are capable of acquiring dozens of images from the 
                         same area and generating a spectrum practically continuous for 
                         each pixel of the scene. This innovation generated, as a 
                         consequence, the development of methods of atmospheric correction 
                         addressed to its products, once, great part of the spectral 
                         channels of these sensors are affected by atmospheric gases (Gao 
                         et al.,1993), masking the subtler and crucial spectral variations 
                         for target identification (Leprier, 1995). This new phase of 
                         acquisition of data was motivated by the limitations of some 
                         sensors in the market, like TM/LANDSAT, in mineral identification 
                         of targets, mainly because of their low spectral resolution. Thus, 
                         given the importance of this new phase of data acquisition 
                         nowadays, this work has the objective to give a general 
                         description of Hyperspectral Remote Sensing, emphasizing the model 
                         of atmospheric correction (Greens Method) addressed for 
                         spectrometry imaging.",
  conference-location = "Belo Horizonte",
      conference-year = "5-10 abr. 2003",
           copyholder = "SID/SCD",
                 isbn = "85-17-00017-X",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais",
                  ibi = "ltid.inpe.br/sbsr/2002/11.14.11.48",
                  url = "http://urlib.net/ibi/ltid.inpe.br/sbsr/2002/11.14.11.48",
           targetfile = "10_111.pdf",
                 type = "Imageamento Hiperespectral / Hyperspectral Imaging",
        urlaccessdate = "10 maio 2024"
}