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@Article{DutraShimArai:2019:SpMuAp,
               author = "Dutra, Andeise Cerqueira and Shimabukuro, Yosio Edemir and Arai, 
                         Egidio",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)}",
                title = "Linear spectral mixing model applied in images from 
                         PROBA-V-Sensor: a spatial multiresolution approach",
              journal = "Ra' e Ga: O Espa{\c{c}}o Geogr{\'a}fico em An{\'a}lise",
                 year = "2019",
               volume = "46",
               number = "3",
                pages = "48--62",
                 note = "{7 GeoPantanal - Simp{\'o}sio de Geotecnologias no Pantanal}",
             keywords = "Estimated Endmembers, Moderate Spatial Resolution, Linear 
                         Regression, Regional Scale, Pantanal, Endmembers estimados, 
                         Moderada Resolu{\c{c}}{\~a}o Espacial, Regress{\~a}o Linear, 
                         Escala Regional, Pantanal.",
             abstract = "The complexity of pixel composition of orbital images has been 
                         commonly referred to the spectral mixture problem. The acquisition 
                         of endmembers (pure pixels) direct from image under study is one 
                         of the most commonly employed approaches. However, it becomes 
                         limited in low or moderate spatial resolutions due to the lower 
                         probability of finding those pixels. In this way, this work 
                         proposes the combined use of images with different spatial 
                         resolutions to estimate the spectral responses of the endmembers 
                         in low spatial resolution image, from the obtained proportions 
                         derived from the spatial higher-resolution images. The proposed 
                         methodology was applied to products provided by PROBA-V satellite 
                         with spatial resolution of 100 m and 1 km in the Pantanal region 
                         of Mato Grosso state. Initially, the fraction images (proportions) 
                         were generated from the 100 m dataset using the endmembers 
                         selected directly in the image, considering the higher probability 
                         of finding pure pixels in such images. Following the spectral 
                         responses of the endmembers in 1 km were estimated by multiple 
                         linear regression, using the proportions of the endmembers in the 
                         pixels derived from 100 m images. For the evaluation, the 
                         endmembers fraction images were compared and field data was used. 
                         These analyses indicated that the spectral responses estimated 
                         allowed to improve the results with regard to error, to 
                         variability, and to the identification of endmembers proportions, 
                         considering that inadequate choice of pixels considered as pure in 
                         low spatial resolution images can affect the quality of the 
                         fraction images for operational use. RESUMO: A complexidade da 
                         composi{\c{c}}{\~a}o de um pixel nas imagens orbitais tem sido 
                         comumente referida ao problema de mistura espectral. A 
                         aquisi{\c{c}}{\~a}o de endmember (pixel puro) a partir da 
                         pr{\'o}pria imagem em estudo {\'e} uma das abordagens mais 
                         comumente empregadas, entretanto, torna-se limitada em sensores de 
                         baixa ou moderada resolu{\c{c}}{\~a}o espacial pela menor 
                         probabilidade de encontrar tais pixels. Dessa maneira, este 
                         trabalho prop{\~o}e o uso combinado de imagens de diferentes 
                         resolu{\c{c}}{\~o}es espaciais para estimar as respostas 
                         espectrais dos endmembers na imagem de baixa resolu{\c{c}}{\~a}o 
                         espacial a partir das propor{\c{c}}{\~o}es obtidas nas imagens 
                         de maior resolu{\c{c}}{\~a}o espacial. O m{\'e}todo proposto 
                         foi aplicado nos produtos fornecidos do minissat{\'e}lite PROBA-V 
                         com resolu{\c{c}}{\~a}o espacial de 100 m e 1 km na regi{\~a}o 
                         do Pantanal Mato Grossense. Inicialmente, as imagens 
                         fra{\c{c}}{\~a}o (propor{\c{c}}{\~o}es) foram geradas para os 
                         dados de 100 m utilizando os endmembers da pr{\'o}pria imagem 
                         considerando a maior probabilidade de encontrar pixels puros 
                         nestas imagens. A seguir, as respostas espectrais dos endmembers 
                         nos dados de 1 km foram estimadas por regress{\~a}o linear 
                         m{\'u}ltipla considerando que as propor{\c{c}}{\~o}es dos 
                         endmembers nos pixels s{\~a}o derivadas das imagens de 100 m. 
                         Para avalia{\c{c}}{\~a}o, foram comparadas as imagens 
                         fra{\c{c}}{\~a}o e utilizados dados de campo. Conclui-se que as 
                         respostas espectrais estimadas permitiram a melhoria dos 
                         resultados no que se refere ao erro, {\`a} variabilidade e {\`a} 
                         identifica{\c{c}}{\~a}o das propor{\c{c}}{\~o}es dos 
                         endmembers, visto que a escolha indevida de pixels considerados 
                         como puros em produtos de baixa resolu{\c{c}}{\~a}o espacial 
                         pode afetar a qualidade das imagens fra{\c{c}}{\~a}o para uso 
                         operacional.",
                  doi = "10.5380/raega",
                  url = "http://dx.doi.org/10.5380/raega",
             language = "en",
           targetfile = "dutra_linear.pdf",
        urlaccessdate = "19 nov. 2019"
}


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