@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 = "27 abr. 2024"
}