Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data

Sonoyo Mukai; Makiko Nakata; Toshiyuki Fujito; Itaru Sano

doi:doi:10.11648/j.ijema.20200805.16

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Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data

Sonoyo Mukai, Makiko Nakata, Toshiyuki Fujito, Itaru Sano

Published in International Journal of Environmental Monitoring and Analysis (Volume 8, Issue 5)

Received: 4 October 2020 Accepted: 19 October 2020 Published: 26 October 2020

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Abstract

This work aimed at detection of aerosols above clouds (AAC). It has been known that AAC has significant potential to change the global radiation budget, namely plays an important role in elucidating climate change. First we examined the advantages of multichannel data from near-UV to thermal infrared (IR) including polarization channels at red and near-IR collected using the GCOM-C/SGLI. The near-UV data at 0.38μm and 0.41μm not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but were also used to distinguish between BBA and DUST with short wavelength IR measurements at 1.63μm. Because understanding aerosol types facilitates subsequent aerosol characterization, classification algorithms for aerosol types have been dealt with since the previous work. Discriminant verification was performed using ground measurements from NASA/AERONET and practically examined in a case of large forest fire. Then the detection of optically thick clouds was challenged in a similar way to aerosol classification in order to lead such a final goal of this work as detection of aerosols above clouds. Subsequently some scenes concerned with DUST type aerosols or BBA ones above water clouds were detected using GCOM-C/SGLI radiance or polarization measurements, respectively, and validated with Terra/MODIS products.

Published in	International Journal of Environmental Monitoring and Analysis (Volume 8, Issue 5)
DOI	10.11648/j.ijema.20200805.16
Page(s)	170-180
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2020. Published by Science Publishing Group

Keywords

BBA (Biomass Burning Aerosol), DUST, Multichannel Satellite Data, Near-UV, Color Ratio, Polarization

References

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Sonoyo Mukai, Makiko Nakata, Toshiyuki Fujito, Itaru Sano. (2020). Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. International Journal of Environmental Monitoring and Analysis, 8(5), 170-180. https://doi.org/10.11648/j.ijema.20200805.16

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Sonoyo Mukai; Makiko Nakata; Toshiyuki Fujito; Itaru Sano. Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. Int. J. Environ. Monit. Anal. 2020, 8(5), 170-180. doi: 10.11648/j.ijema.20200805.16

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AMA Style

Sonoyo Mukai, Makiko Nakata, Toshiyuki Fujito, Itaru Sano. Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. Int J Environ Monit Anal. 2020;8(5):170-180. doi: 10.11648/j.ijema.20200805.16

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@article{10.11648/j.ijema.20200805.16,
  author = {Sonoyo Mukai and Makiko Nakata and Toshiyuki Fujito and Itaru Sano},
  title = {Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {8},
  number = {5},
  pages = {170-180},
  doi = {10.11648/j.ijema.20200805.16},
  url = {https://doi.org/10.11648/j.ijema.20200805.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20200805.16},
  abstract = {This work aimed at detection of aerosols above clouds (AAC). It has been known that AAC has significant potential to change the global radiation budget, namely plays an important role in elucidating climate change. First we examined the advantages of multichannel data from near-UV to thermal infrared (IR) including polarization channels at red and near-IR collected using the GCOM-C/SGLI. The near-UV data at 0.38μm and 0.41μm not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but were also used to distinguish between BBA and DUST with short wavelength IR measurements at 1.63μm. Because understanding aerosol types facilitates subsequent aerosol characterization, classification algorithms for aerosol types have been dealt with since the previous work. Discriminant verification was performed using ground measurements from NASA/AERONET and practically examined in a case of large forest fire. Then the detection of optically thick clouds was challenged in a similar way to aerosol classification in order to lead such a final goal of this work as detection of aerosols above clouds. Subsequently some scenes concerned with DUST type aerosols or BBA ones above water clouds were detected using GCOM-C/SGLI radiance or polarization measurements, respectively, and validated with Terra/MODIS products.},
 year = {2020}
}

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TY  - JOUR
T1  - Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data
AU  - Sonoyo Mukai
AU  - Makiko Nakata
AU  - Toshiyuki Fujito
AU  - Itaru Sano
Y1  - 2020/10/26
PY  - 2020
N1  - https://doi.org/10.11648/j.ijema.20200805.16
DO  - 10.11648/j.ijema.20200805.16
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 170
EP  - 180
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20200805.16
AB  - This work aimed at detection of aerosols above clouds (AAC). It has been known that AAC has significant potential to change the global radiation budget, namely plays an important role in elucidating climate change. First we examined the advantages of multichannel data from near-UV to thermal infrared (IR) including polarization channels at red and near-IR collected using the GCOM-C/SGLI. The near-UV data at 0.38μm and 0.41μm not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but were also used to distinguish between BBA and DUST with short wavelength IR measurements at 1.63μm. Because understanding aerosol types facilitates subsequent aerosol characterization, classification algorithms for aerosol types have been dealt with since the previous work. Discriminant verification was performed using ground measurements from NASA/AERONET and practically examined in a case of large forest fire. Then the detection of optically thick clouds was challenged in a similar way to aerosol classification in order to lead such a final goal of this work as detection of aerosols above clouds. Subsequently some scenes concerned with DUST type aerosols or BBA ones above water clouds were detected using GCOM-C/SGLI radiance or polarization measurements, respectively, and validated with Terra/MODIS products.
VL  - 8
IS  - 5
ER  -

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Author Information

Sonoyo Mukai

School of Applied Information Technology, The Kyoto College of Graduate Studies for Informatics, Kyoto, Japan
Makiko Nakata

Faculty of Applied Sociology, Kindai University, Higashi-Osaka, Japan
Toshiyuki Fujito

School of Applied Information Technology, The Kyoto College of Graduate Studies for Informatics, Kyoto, Japan
Itaru Sano

Faculty of Science and Engineering, Kindai University, Higashi-Osaka, Japan

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APA Style

Sonoyo Mukai, Makiko Nakata, Toshiyuki Fujito, Itaru Sano. (2020). Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. International Journal of Environmental Monitoring and Analysis, 8(5), 170-180. https://doi.org/10.11648/j.ijema.20200805.16

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ACS Style

Sonoyo Mukai; Makiko Nakata; Toshiyuki Fujito; Itaru Sano. Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. Int. J. Environ. Monit. Anal. 2020, 8(5), 170-180. doi: 10.11648/j.ijema.20200805.16

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AMA Style

Sonoyo Mukai, Makiko Nakata, Toshiyuki Fujito, Itaru Sano. Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data. Int J Environ Monit Anal. 2020;8(5):170-180. doi: 10.11648/j.ijema.20200805.16

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@article{10.11648/j.ijema.20200805.16,
  author = {Sonoyo Mukai and Makiko Nakata and Toshiyuki Fujito and Itaru Sano},
  title = {Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data},
  journal = {International Journal of Environmental Monitoring and Analysis},
  volume = {8},
  number = {5},
  pages = {170-180},
  doi = {10.11648/j.ijema.20200805.16},
  url = {https://doi.org/10.11648/j.ijema.20200805.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20200805.16},
  abstract = {This work aimed at detection of aerosols above clouds (AAC). It has been known that AAC has significant potential to change the global radiation budget, namely plays an important role in elucidating climate change. First we examined the advantages of multichannel data from near-UV to thermal infrared (IR) including polarization channels at red and near-IR collected using the GCOM-C/SGLI. The near-UV data at 0.38μm and 0.41μm not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but were also used to distinguish between BBA and DUST with short wavelength IR measurements at 1.63μm. Because understanding aerosol types facilitates subsequent aerosol characterization, classification algorithms for aerosol types have been dealt with since the previous work. Discriminant verification was performed using ground measurements from NASA/AERONET and practically examined in a case of large forest fire. Then the detection of optically thick clouds was challenged in a similar way to aerosol classification in order to lead such a final goal of this work as detection of aerosols above clouds. Subsequently some scenes concerned with DUST type aerosols or BBA ones above water clouds were detected using GCOM-C/SGLI radiance or polarization measurements, respectively, and validated with Terra/MODIS products.},
 year = {2020}
}

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TY  - JOUR
T1  - Efficient Detection of Aerosols Above Clouds Utilizing GCOM-C/SGLI Data
AU  - Sonoyo Mukai
AU  - Makiko Nakata
AU  - Toshiyuki Fujito
AU  - Itaru Sano
Y1  - 2020/10/26
PY  - 2020
N1  - https://doi.org/10.11648/j.ijema.20200805.16
DO  - 10.11648/j.ijema.20200805.16
T2  - International Journal of Environmental Monitoring and Analysis
JF  - International Journal of Environmental Monitoring and Analysis
JO  - International Journal of Environmental Monitoring and Analysis
SP  - 170
EP  - 180
PB  - Science Publishing Group
SN  - 2328-7667
UR  - https://doi.org/10.11648/j.ijema.20200805.16
AB  - This work aimed at detection of aerosols above clouds (AAC). It has been known that AAC has significant potential to change the global radiation budget, namely plays an important role in elucidating climate change. First we examined the advantages of multichannel data from near-UV to thermal infrared (IR) including polarization channels at red and near-IR collected using the GCOM-C/SGLI. The near-UV data at 0.38μm and 0.41μm not only detected absorbing aerosols such as biomass burning aerosols (BBA) or mineral dust (DUST), but were also used to distinguish between BBA and DUST with short wavelength IR measurements at 1.63μm. Because understanding aerosol types facilitates subsequent aerosol characterization, classification algorithms for aerosol types have been dealt with since the previous work. Discriminant verification was performed using ground measurements from NASA/AERONET and practically examined in a case of large forest fire. Then the detection of optically thick clouds was challenged in a similar way to aerosol classification in order to lead such a final goal of this work as detection of aerosols above clouds. Subsequently some scenes concerned with DUST type aerosols or BBA ones above water clouds were detected using GCOM-C/SGLI radiance or polarization measurements, respectively, and validated with Terra/MODIS products.
VL  - 8
IS  - 5
ER  -

Copy | Download