@Article{DuránPereKupl:2018:IdEsMa,
               author = "Dur{\'a}n, Gloria and Pereira Filho, Waterloo and Kuplich, 
                         Tatiana Mora",
          affiliation = "{} and {Universidade Federal de Santa Maria (UFSM)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Identifica{\c{c}}{\~a}o espectral de materiais urbanos com a 
                         t{\'e}cnica Mapeador de {\^A}ngulo Espectral (SAM) e o sensor de 
                         alta resolu{\c{c}}{\~a}o espacial GEOEYE-1",
              journal = "Boletim Geogr{\'a}fico do Rio Grande do Sul",
                 year = "2018",
               volume = "31",
                pages = "9--34",
             keywords = "Comportamento Espectral, Sensoriamento Remoto, {\'A}reas Urbanas. 
                         Spectral Angle Mapper, GeoEye-1, Spectral Characterization, Remote 
                         sensing, Urban Areas, Spectral Angle Mapper, GeoEye-1.",
             abstract = "As {\'a}reas urbanas s{\~a}o constitu{\'{\i}}das por um 
                         conjunto diversificado de materiais fabricados e naturais, 
                         dispostos de forma complexa pelo homem para sua 
                         sobreviv{\^e}ncia. O sensoriamento remoto {\'e} uma ferramenta 
                         com potencial para obten{\c{c}}{\~a}o de dados espectrais de 
                         materiais urbanos e suas condi{\c{c}}{\~o}es. Neste trabalho, 
                         foi avaliada a potencialidade de identifica{\c{c}}{\~a}o 
                         espectral dos materiais urbanos numa imagem multiespectral 
                         GeoEye-1 utilizando a t{\'e}cnica de mapeamento espectral SAM 
                         (Spectral Angle Mapper), que determina a similaridade espectral 
                         entre as curvas espectrais de v{\'a}rios p{\'{\i}}xeis, 
                         calculando um angulo entre eles, sendo que a varia{\c{c}}{\~a}o 
                         angular possibilita discriminar fei{\c{c}}{\~o}es espectrais dos 
                         alvos. Os resultados obtidos mostraram que a t{\'e}cnica SAM, 
                         permitiu a identifica{\c{c}}{\~a}o das caracter{\'{\i}}sticas 
                         espectrais de alvos fabricados e naturais com algumas 
                         limita{\c{c}}{\~o}es devido principalmente {\`a} 
                         heterogeneidade de alvos urbanos e mistura espectral. Assim foi 
                         poss{\'{\i}}vel a identifica{\c{c}}{\~a}o de alvos urbanos com 
                         exatid{\~a}o maior a 50%. A imagem GeoEye-1 proporciona uma 
                         aproxima{\c{c}}{\~a}o {\`a} identifica{\c{c}}{\~a}o de 
                         padr{\~o}es intraurbanos considerando a resposta espectral dos 
                         alvos, mas pode ser aperfei{\c{c}}oado utilizando imagens 
                         hiperespectrais assim como outros m{\'e}todos de 
                         classifica{\c{c}}{\~a}o que considerem padr{\~o}es de forma, 
                         textura e comportamento espectral. ABSTRACT: The urban areas are 
                         made up of a diverse set of manufactured and natural materials, 
                         arranged in a complex way by man for his survival. Remote sensing 
                         is a tool used to obtain spectral data of urban materials and 
                         their conditions. In this work, the potential of spectral 
                         identification of urban materials in a GeoEye-1 multispectral 
                         image was evaluated using the Spectral Angle Mapper (SAM) 
                         technique, which determines the spectral similarity between 
                         multi-pixel spectral curves. An angle between spectral curves and 
                         its variation are calculated, allowing discrimination between 
                         targets. The results showed that the SAM technique allowed 
                         identification of the spectral characteristics of manufactured and 
                         natural targets, although with some limitations mainly due to 
                         heterogeneity of urban targets and spectral mixing. It was 
                         possible to identify urban targets with an accuracy greater than 
                         50%. The GeoEye-1 image provides the identification of intra-urban 
                         patterns considering the spectral response of the targets, but 
                         results can be improved using hyperspectral images and a 
                         combination of spectral techniques with classification methods 
                         that consider patterns of shape and texture.",
                 issn = "0520-4062",
                label = "lattes: 8997858562195060 3 Dur{\'a}nPereKupl:2018:IdEsMa",
             language = "pt",
           targetfile = "duran_identificacao.pdf",
                  url = "https://revistas.fee.tche.br/index.php/boletim-geografico-rs/article/view/4011/3976",
        urlaccessdate = "26 abr. 2024"
}