Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations
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...
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ftiowastateuniv:oai:lib.dr.iastate.edu:abe_eng_pubs-2315 2023-05-15T13:07:12+02:00 Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations Martins, Vitor S. Soares, João V. Novo, Evlyn M.L.M. Barbosa, Claudio C.F. Pinto, Cibele T. Arcanjo, Jeferson S. Kaleita, Amy 2018-12-01T08:00:00Z application/pdf https://lib.dr.iastate.edu/abe_eng_pubs/1029 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2315&context=abe_eng_pubs en eng Iowa State University Digital Repository https://lib.dr.iastate.edu/abe_eng_pubs/1029 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2315&context=abe_eng_pubs http://creativecommons.org/licenses/by-nc-nd/4.0/ CC-BY-NC-ND Agricultural and Biosystems Engineering Publications CBERS Surface reflectance CMPAC Landsat-8 MODIS VIIRS Agriculture Atmospheric Sciences Bioresource and Agricultural Engineering Environmental Monitoring text 2018 ftiowastateuniv 2021-08-28T22:48:54Z 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. Text Aerosol Robotic Network Digital Repository @ Iowa State University |
institution |
Open Polar |
collection |
Digital Repository @ Iowa State University |
op_collection_id |
ftiowastateuniv |
language |
English |
topic |
CBERS Surface reflectance CMPAC Landsat-8 MODIS VIIRS Agriculture Atmospheric Sciences Bioresource and Agricultural Engineering Environmental Monitoring |
spellingShingle |
CBERS Surface reflectance CMPAC Landsat-8 MODIS VIIRS Agriculture Atmospheric Sciences Bioresource and Agricultural Engineering Environmental Monitoring Martins, Vitor S. Soares, João V. Novo, Evlyn M.L.M. Barbosa, Claudio C.F. Pinto, Cibele T. Arcanjo, Jeferson S. Kaleita, Amy Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
topic_facet |
CBERS Surface reflectance CMPAC Landsat-8 MODIS VIIRS Agriculture Atmospheric Sciences Bioresource and Agricultural Engineering Environmental Monitoring |
description |
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. |
format |
Text |
author |
Martins, Vitor S. Soares, João V. Novo, Evlyn M.L.M. Barbosa, Claudio C.F. Pinto, Cibele T. Arcanjo, Jeferson S. Kaleita, Amy |
author_facet |
Martins, Vitor S. Soares, João V. Novo, Evlyn M.L.M. Barbosa, Claudio C.F. Pinto, Cibele T. Arcanjo, Jeferson S. Kaleita, Amy |
author_sort |
Martins, Vitor S. |
title |
Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
title_short |
Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
title_full |
Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
title_fullStr |
Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
title_full_unstemmed |
Continental-scale surface reflectance product from CBERS-4 MUX data: Assessment of atmospheric correction method using coincident Landsat observations |
title_sort |
continental-scale surface reflectance product from cbers-4 mux data: assessment of atmospheric correction method using coincident landsat observations |
publisher |
Iowa State University Digital Repository |
publishDate |
2018 |
url |
https://lib.dr.iastate.edu/abe_eng_pubs/1029 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2315&context=abe_eng_pubs |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Agricultural and Biosystems Engineering Publications |
op_relation |
https://lib.dr.iastate.edu/abe_eng_pubs/1029 https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=2315&context=abe_eng_pubs |
op_rights |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
op_rightsnorm |
CC-BY-NC-ND |
_version_ |
1766040267385733120 |