@InProceedings{PetriPestBour:2019:AbMuMu,
               author = "Petri, Caio Arlanche and Pestana, Lu{\'{\i}}s Fernando de Abreu 
                         and Bourscheidt, Vandoir",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal de S{\~a}o Carlos (UFSCar)} and 
                         {Universidade Federal de S{\~a}o Carlos (UFSCar)}",
                title = "Mistura espectral em {\'a}reas de Cerrado: abordagem multisensor 
                         e multiresolu{\c{c}}{\~a}o",
            booktitle = "Anais...",
                 year = "2019",
               editor = "Gherardi, Douglas Francisco Marcolino and Sanches, Ieda DelArco 
                         and Arag{\~a}o, Luiz Eduardo Oliveira e Cruz de",
                pages = "1624--1627",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 19. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "MLME, VANT, CBERS4, PlanetScope, LSMM, UAV, CBERS4, PlanetScope.",
             abstract = "Tr{\^e}s diferentes fontes de dados (VANT, Planet e CBERS4/Pan) 
                         foram utilizadas para a aplica{\c{c}}{\~a}o do modelo linear de 
                         mistura espectral (MLME), buscando evidenciar a influ{\^e}ncia da 
                         resolu{\c{c}}{\~a}o espacial e espectral em uma {\'a}rea de 
                         Cerrado. As imagens obtidas com VANT resultaram em um mosaico com 
                         resolu{\c{c}}{\~a}o espacial de 0,01 m. Imagens dos 
                         sat{\'e}lites PlanetScope e CBERS4/Pan, com resolu{\c{c}}{\~a}o 
                         espacial de 3 e de 10 metros, respectivamente, complementaram a 
                         base de dados. O MLME foi aplicado em cada imagem, e uma 
                         amostragem aleat{\'o}ria de pontos foi estabelecida para avaliar 
                         a varia{\c{c}}{\~a}o e variabilidade entre os dados. 
                         Posteriormente, a imagem VANT foi reamostrada para 
                         resolu{\c{c}}{\~o}es de 1 e 10 m visando demonstrar a 
                         influ{\^e}ncia do procedimento no resultado do MLME. Os 
                         resultados mostraram que a resolu{\c{c}}{\~a}o espacial promove 
                         diferen{\c{c}}as na detec{\c{c}}{\~a}o de sombras pelo modelo, 
                         assim como a presen{\c{c}}a de bandas do azul e do infravermelho 
                         pr{\'o}ximo. De forma geral, a reamostragem de pixels resultou na 
                         redu{\c{c}}{\~a}o da quantidade de sombras e aumento na 
                         fra{\c{c}}{\~a}o solo. Os autores concluem que o trabalho 
                         auxiliou na demonstra{\c{c}}{\~a}o dos impactos dos fatores 
                         analisados na capacidade de distin{\c{c}}{\~a}o de 
                         fra{\c{c}}{\~o}es do modelo utilizado, assim como na 
                         compreens{\~a}o das implica{\c{c}}{\~o}es do uso de diferentes 
                         sensores. ABSTRACT: Images from three instruments (UAV, 
                         PlanetScope and CBERS4/Pan) were used to evaluate the influence of 
                         spatial and spectral resolution when using the spectral mixing 
                         linear model (LSMM) in a Cerrado area. An Orthmosaic with 0.01 m 
                         spatial resolution was obtained for the UAV imagery. PlanetScope 
                         and CBERS4/Pan images with resolutions of 3 and 10 meters, 
                         respectively, completed the database. The LSMM was applied to each 
                         image, and a random sampling of points was established to evaluate 
                         the variation and variability between the datasets. In an 
                         additional step, the UAV orthomosaic was resampled to 1 and 10 m 
                         to demonstrate the influence of the procedure on the LSMM. The 
                         results showed that the spatial resolution promotes differences in 
                         the detection of shadows by the model, as well as the presence of 
                         blue and near infrared bands. In general, pixel resampling 
                         promoted reduction in the amount of shadows and increase in the 
                         soil fraction. The authors concluded that the work contribute to 
                         better understand the impacts of the analysed factors on the 
                         fractional capacity of the used model, as well as to understand 
                         the implications of the use of different sensors.",
  conference-location = "Santos",
      conference-year = "14-17 abril 2019",
                 isbn = "978-85-17-00097-3",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3U254EL",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3U254EL",
           targetfile = "97355.pdf",
                 type = "Floresta e outros tipos de vegeta{\c{c}}{\~a}o",
        urlaccessdate = "28 abr. 2024"
}