Retrieving Aerosol Optical Depth over Land from Landsat-8 Satellite Images with the Aid of Cloud Shadows
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作者:
Zhu, Jingmiao
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Chinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R ChinaChinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Zhu, Jingmiao
[1
,2
]
Qiao, Congcong
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Chinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R ChinaChinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Qiao, Congcong
[1
,3
]
Duan, Minzheng
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Chinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R ChinaChinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
Duan, Minzheng
[1
,3
]
机构:
[1] Chinese Acad Sci, Inst Atmospher & Phys, Beijing 100029, Peoples R China
[2] Lanzhou Univ, Sch Math & Stat, Lanzhou 730000, Peoples R China
[3] Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China
Clouds and their shadows can be clearly identified from high-spatial-resolution satellite images, such as those provided by Landsat-8/9 with a spatial resolution of approximately 30 m and Sentinel-2 with a spatial resolution of around 20 m. Consequently, the difference between satellite measurements over cloud-shadowed and nearby illuminated pixels can be used to derive the aerosol optical depth (AOD), even in the absence of detailed surface optical properties. Based on this assumption, an algorithm for AOD retrieval over land is developed and tested using Landsat-8/9 images containing scattered clouds over Xuzhou, China, and Dalanzadgad, Mongolia. The retrieved AODs are compared against MODIS and ground-based sun photometer measurements. The findings reveal that, in cloudy regions, over 90% of the discrepancies between the AODs retrieved using the cloud-shadow method and ground-based measurements fall within 0.05 +/- 0.20 AOD. This cloud-shadow algorithm represents a valuable complement to existing satellite aerosol retrieval methods, particularly in sparsely cloud-covered areas.
机构:
Univ Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
NASA Goddard Space Flight Ctr, Greenbelt, MD USAUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
Sayer, A. M.
Hsu, N. C.
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NASA Goddard Space Flight Ctr, Greenbelt, MD USAUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
Hsu, N. C.
Bettenhausen, C.
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NASA Goddard Space Flight Ctr, Greenbelt, MD USA
Sci Syst Applicat Inc, Lanham, MD USAUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
Bettenhausen, C.
Jeong, M. -J.
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Gangneung Wonju Natl Univ, Dept Atmospher & Environm Sci, Kangnung, Gangwon Do, South KoreaUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
Jeong, M. -J.
Holben, B. N.
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NASA Goddard Space Flight Ctr, Greenbelt, MD USAUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
Holben, B. N.
Zhang, J.
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Univ N Dakota, Dept Atmospher Sci, Grand Forks, ND 58201 USAUniv Space Res Assoc, Goddard Earth Sci Technol & Res GESTAR, Columbia, MD USA
机构:
Morgan State Univ, GESTAR, Columbia, MD 21046 USA
NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USAMorgan State Univ, GESTAR, Columbia, MD 21046 USA
Patadia, Falguni
Levy, Robert C.
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NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USAMorgan State Univ, GESTAR, Columbia, MD 21046 USA
Levy, Robert C.
Mattoo, Shana
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NASA, Goddard Space Flight Ctr, Greenbelt, MD 20771 USA
SSAI, Lanham, MD USAMorgan State Univ, GESTAR, Columbia, MD 21046 USA
机构:
Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R ChinaBeijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R China
Hao, Hongfei
Wang, Kaicun
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Peking Univ, Inst Carbon Neutral, Sino French Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing 100871, Peoples R ChinaBeijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R China
Wang, Kaicun
Zhao, Chuanfeng
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Peking Univ, Inst Carbon Neutral, Coll Urban & Environm Sci, Sch Phys,Dept Atmospher & Ocean Sci, Beijing 100871, Peoples R ChinaBeijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R China
Zhao, Chuanfeng
Wu, Guocan
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Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R ChinaBeijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R China
Wu, Guocan
Li, Jing
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Peking Univ, Inst Carbon Neutral, Coll Urban & Environm Sci, Sch Phys,Dept Atmospher & Ocean Sci, Beijing 100871, Peoples R ChinaBeijing Normal Univ, Coll Global Change & Earth Syst Sci, Fac Geog Sci, Beijing 100875, Peoples R China
机构:
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Shi, Shuaiyi
Cheng, Tianhai
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Cheng, Tianhai
Gu, Xingfa
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Gu, Xingfa
Letu, Husi
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Letu, Husi
Guo, Hong
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Guo, Hong
Chen, Hao
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Chen, Hao
Wang, Ying
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China
Wang, Ying
Wu, Yu
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Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote sensing Sci, Beijing, Peoples R China