@Article{FreitasHaerShim:2008:LiSpMi,
author = "Freitas, Ramon Morais de and Haertel, V. b and Shimabukuro, Yosio
Edemir",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and
Universidade Federal do Rio Grande do Sul, Centro de Sensoriamento
Remoto e Meteorologia, Caixa Postal - 15044, Porto Alegre, RS,
Brazil and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Linear spectral mixture model in moderate spatial resolution image
data / Modelo linear de mistura espectral em imagem de moderada
resolu{\c{c}}{\~a}o espacial",
journal = "Boletim de Ci{\^e}ncias Geod{\'e}sicas",
year = "2008",
volume = "14",
number = "17",
pages = "55--71",
month = "Jan.",
keywords = "GEOBASE Subject Index: data set, image analysis, linearity, pixel,
radiometric method, remote sensing, spatial resolution, spectral
reflectance, CBERS-2.",
abstract = "The concept of spectral mixture offers a wide range of
applications in the Remote Sensing area. The application of this
concept, however, requires the prior estimation of the component's
(endmembers) spectral response. This latter requirement can be
achieved by different methods, as reported in the literature, such
as techniques for the detection of pure pixels, use of spectral
libraries, and field radiometric measurements. Among those, the
most often used is the pure pixel approach. In this approach, the
components' spectral reflectances are estimated by means of pixels
covered entirely by a single component. This approach offers the
advantage of allowing the extraction of the required spectral
reflectance directly from the image data. This approach, however,
becomes increasingly unfeasible as the spatial resolution of the
image data decreases, due to the larger ground area covered by a
single pixel. In this study we propose a methodology to estimate
the spectral reflectance for each component class in moderate
spatial resolution image data, by applying the linear mixing model
(MLME), and higher spatial resolution image data as auxiliary
data. It is expected that this methodology will provide a more
practical way to implement the spectral mixture approach to
moderate resolution image data, allowing in this way the expansion
of the information about the components' proportions across larger
areas, up-scaling information in regional and global studies.
Experiments were carried out using CCD (20 m ground resolution)
and IRMSS (80 m ground resolution) and WFI (260 m ground
resolution) CBERS-2 image data, as medium and moderate spatial
resolution data, respectively. The spectral reflectances for the
components in the IRMSS and WFI CBERS-2 spectral bands are
estimated by applying the proposed methodology. The reliability of
the proposed methodology was assessed by both analyzing scatter
plots for CBERS-2 data and by comparing the fraction images
produced by image data sets of the sensors analyzed.",
label = "self-archiving-INPE-MCTI-GOV-BR",
language = "en",
targetfile = "freitas_modelo.pdf",
urlaccessdate = "09 maio 2024"
}