Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations

dc.contributor.author Martins, Vitor
dc.contributor.author Martins, Vitor
dc.contributor.author Soares, João
dc.contributor.author Novo, Evlyn
dc.contributor.author Kaleita, Amy
dc.contributor.author Barbosa, Claudio
dc.contributor.author Pinto, Cibele
dc.contributor.author Arcanjo, Jeferson
dc.contributor.author Kaleita, Amy
dc.contributor.department Agricultural and Biosystems Engineering
dc.date 2019-06-30T23:38:55.000
dc.date.accessioned 2020-06-29T22:36:19Z
dc.date.available 2020-06-29T22:36:19Z
dc.date.copyright Mon Jan 01 00:00:00 UTC 2018
dc.date.embargo 2020-09-26
dc.date.issued 2018-12-01
dc.description.abstract <p>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.</p>
dc.description.comments <p>This is a manuscript of an article published as Martins, Vitor S., João V. Soares, Evlyn MLM Novo, Claudio CF Barbosa, Cibele T. Pinto, Jeferson S. Arcanjo, and Amy Kaleita. "Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations." <em>Remote Sensing of Environment</em> 218 (2018): 55-68. DOI: <a href="http://dx.doi.org/10.1016/j.rse.2018.09.017" target="_blank">10.1016/j.rse.2018.09.017</a>. Posted with permission.</p>
dc.format.mimetype application/pdf
dc.identifier archive/lib.dr.iastate.edu/abe_eng_pubs/1029/
dc.identifier.articleid 2315
dc.identifier.contextkey 14472454
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath abe_eng_pubs/1029
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/728
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/abe_eng_pubs/1029/2018_MartinsVitor_ContinentalScale.pdf|||Fri Jan 14 18:17:38 UTC 2022
dc.source.uri 10.1016/j.rse.2018.09.017
dc.subject.disciplines Agriculture
dc.subject.disciplines Atmospheric Sciences
dc.subject.disciplines Bioresource and Agricultural Engineering
dc.subject.disciplines Environmental Monitoring
dc.subject.keywords CBERS
dc.subject.keywords Surface reflectance
dc.subject.keywords CMPAC
dc.subject.keywords Landsat-8
dc.subject.keywords MODIS
dc.subject.keywords VIIRS
dc.title Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations
dc.type article
dc.type.genre article
dspace.entity.type Publication
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relation.isAuthorOfPublication 8a405b08-e1c8-4a10-b458-2f5a82fcf148
relation.isOrgUnitOfPublication 8eb24241-0d92-4baf-ae75-08f716d30801
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