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QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation

The difficulty of atmospheric correction based on a radiative transfer model lies in the acquisition of synchronized atmospheric parameters, especially the aerosol optical depth (AOD). At the moment, there is no fully automatic and high-efficiency atmospheric correction method to make full use of th...

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Autores principales: Liu, Shumin, Zhang, Yunli, Zhao, Limin, Chen, Xingfeng, Zhou, Ruoxuan, Zheng, Fengjie, Li, Zhiliang, Li, Jiaguo, Yang, Hang, Li, Huafu, Yang, Jian, Gao, Hailiang, Gu, Xingfa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100192/
https://www.ncbi.nlm.nih.gov/pubmed/35590973
http://dx.doi.org/10.3390/s22093280
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author Liu, Shumin
Zhang, Yunli
Zhao, Limin
Chen, Xingfeng
Zhou, Ruoxuan
Zheng, Fengjie
Li, Zhiliang
Li, Jiaguo
Yang, Hang
Li, Huafu
Yang, Jian
Gao, Hailiang
Gu, Xingfa
author_facet Liu, Shumin
Zhang, Yunli
Zhao, Limin
Chen, Xingfeng
Zhou, Ruoxuan
Zheng, Fengjie
Li, Zhiliang
Li, Jiaguo
Yang, Hang
Li, Huafu
Yang, Jian
Gao, Hailiang
Gu, Xingfa
author_sort Liu, Shumin
collection PubMed
description The difficulty of atmospheric correction based on a radiative transfer model lies in the acquisition of synchronized atmospheric parameters, especially the aerosol optical depth (AOD). At the moment, there is no fully automatic and high-efficiency atmospheric correction method to make full use of the advantages of geostationary meteorological satellites in large-scale and efficient atmospheric monitoring. Therefore, a QUantitative and Automatic Atmospheric Correction (QUAAC) method is proposed which can efficiently correct high-spatial-resolution (HSR) satellite images. QUAAC uses the atmospheric aerosol products of geostationary satellites to match the synchronized AOD according to the temporal and spatial information of HSR satellite images. This method solves the problem that the AOD is difficult to obtain or the accuracy is not high enough to meet the demand of atmospheric correction. By using the obtained atmospheric parameters, atmospheric correction is performed to obtain the surface reflectance (SR). The whole process can achieve fully automatic operation without manual intervention. After QUAAC applied to Gaofen-2 (GF-2) HSR satellite and Himawari-8 (H-8) geostationary satellite, the results show that the effect of QUAAC correction is slightly better than that of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) correction, and the QUAAC−corrected surface spectral curves have good coherence to that of the synchronously measured by field experiments.
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spelling pubmed-91001922022-05-14 QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation Liu, Shumin Zhang, Yunli Zhao, Limin Chen, Xingfeng Zhou, Ruoxuan Zheng, Fengjie Li, Zhiliang Li, Jiaguo Yang, Hang Li, Huafu Yang, Jian Gao, Hailiang Gu, Xingfa Sensors (Basel) Article The difficulty of atmospheric correction based on a radiative transfer model lies in the acquisition of synchronized atmospheric parameters, especially the aerosol optical depth (AOD). At the moment, there is no fully automatic and high-efficiency atmospheric correction method to make full use of the advantages of geostationary meteorological satellites in large-scale and efficient atmospheric monitoring. Therefore, a QUantitative and Automatic Atmospheric Correction (QUAAC) method is proposed which can efficiently correct high-spatial-resolution (HSR) satellite images. QUAAC uses the atmospheric aerosol products of geostationary satellites to match the synchronized AOD according to the temporal and spatial information of HSR satellite images. This method solves the problem that the AOD is difficult to obtain or the accuracy is not high enough to meet the demand of atmospheric correction. By using the obtained atmospheric parameters, atmospheric correction is performed to obtain the surface reflectance (SR). The whole process can achieve fully automatic operation without manual intervention. After QUAAC applied to Gaofen-2 (GF-2) HSR satellite and Himawari-8 (H-8) geostationary satellite, the results show that the effect of QUAAC correction is slightly better than that of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) correction, and the QUAAC−corrected surface spectral curves have good coherence to that of the synchronously measured by field experiments. MDPI 2022-04-25 /pmc/articles/PMC9100192/ /pubmed/35590973 http://dx.doi.org/10.3390/s22093280 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Shumin
Zhang, Yunli
Zhao, Limin
Chen, Xingfeng
Zhou, Ruoxuan
Zheng, Fengjie
Li, Zhiliang
Li, Jiaguo
Yang, Hang
Li, Huafu
Yang, Jian
Gao, Hailiang
Gu, Xingfa
QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title_full QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title_fullStr QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title_full_unstemmed QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title_short QUantitative and Automatic Atmospheric Correction (QUAAC): Application and Validation
title_sort quantitative and automatic atmospheric correction (quaac): application and validation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9100192/
https://www.ncbi.nlm.nih.gov/pubmed/35590973
http://dx.doi.org/10.3390/s22093280
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