@Article{MartinsSoNoBaPiArKa:2018:AsAtCo,
author = "Martins, Vitor S. and Soares, Jo{\~a}o Vianei and Novo, Evlyn
M{\'a}rcia Le{\~a}o de Moraes and Barbosa, Cl{\'a}udio Clemente
Faria and Pinto, Cibele T. and Arcanjo, Jeferson de Souza and
Kaleita, Amy",
affiliation = "{Iowa State University (ISU)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)} and
{South Dakota State Universit} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Iowa State University (ISU)}",
title = "Continental-scale surface reflectance product from CBERS-4 MUX
data: Assessment of atmospheric correction method using coincident
Landsat observations",
journal = "Remote Sensing of Environment",
year = "2018",
volume = "218",
pages = "55--68",
month = "Dec.",
keywords = "CBERS, Surface reflectance, CMPAC, Landsat-8, MODIS VIIRS.",
abstract = "A practical atmospheric correction algorithm, called Coupled
Moderate Products for Atmospheric Correction (CMPAC), was
developed and implemented for the Multispectral Camera (MUX)
on-board the China-Brazil Earth Resources Satellite (CBERS-4).
This algorithm uses a scene-based processing and sliding window
technique to derive MUX surface reflectance (SR) at continental
scale. Unlike other optical sensors, MUX instrument imposes
constraints for atmospheric correction due to the absence of
spectral bands for aerosol estimation from imagery itself. To
overcome this limitation, the proposed algorithm performs a
further processing of atmospheric products from Moderate
Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared
Imaging Radiometer Suite (VIIRS) sensors as input parameters for
radiative transfer calculations. The success of CMPAC algorithm
was fully assessed and confirmed by comparison of MUX SR data with
the Landsat-8 OLI Level-2 and Aerosol Robotic Network
(AERONET)-derived SR products. The spectral adjustment was
performed to compensate for the differences of relative spectral
response between MUX and OLI sensors. The results show that MUX SR
values are fairly similar to operational Landsat-8 SR products
(mean difference < 0.0062, expressed in reflectance). There is a
slight underestimation of MUX SR compared to OLI product (except
the NIR band), but the error metrics are typically low and
scattered points are around the line 1:1. These results suggest
the potential of combining these datasets (MUX and OLI) for
quantitative studies. Further, the robust agreement of MUX and
AERONET-derived SR values emphasizes the quality of moderate
atmospheric products as input parameters in this application, with
root-mean-square deviation lower than 0.0047. These findings
confirm that (i) CMPAC is a suitable tool for estimating surface
reflectance of CBERS MUX data, and (ii) ancillary products support
the application of atmospheric correction by filling the gap of
atmospheric information. The uncertainties of atmospheric
products, negligence of the bidirectional effects, and two aerosol
models were also identified as a limitation. Finally, this study
presents a framework basis for atmospheric correction of CBERS-4
MUX images. The utility of CBERS data comes from its use, and this
new product enables the quantitative remote sensing for land
monitoring and environmental assessment at 20 m spatial
resolution.",
doi = "10.1016/j.rse.2018.09.017",
url = "http://dx.doi.org/10.1016/j.rse.2018.09.017",
issn = "0034-4257",
language = "en",
targetfile = "martins_continental.pdf",
urlaccessdate = "19 abr. 2024"
}