A Method for the Recovery of Aura Satellite Remote Sensing Ozone Products

PENG Xiaolin; SHEN Huanfeng; ZENG Chao; ZHANG Liangpei; HE Zongyi

doi:10.13203/j.whugis20150390

Volume 42 Issue 6

Jun. 2017

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Geomatics and Information Science of Wuhan University > 2017 > 42(6): 789-796. > DOI: 10.13203/j.whugis20150390

PENG Xiaolin, SHEN Huanfeng, ZENG Chao, ZHANG Liangpei, HE Zongyi. A Method for the Recovery of Aura Satellite Remote Sensing Ozone Products[J]. Geomatics and Information Science of Wuhan University, 2017, 42(6): 789-796. DOI: 10.13203/j.whugis20150390

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A Method for the Recovery of Aura Satellite Remote Sensing Ozone Products

1.
School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China
2.
The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

Funds:

The National Natural Science Foundation of China 41271376

The National Natural Science Foundation of China 41422108

the Natural Science Foundation of Hubei Province of China 2015CFA002

the Program for Changjiang Scholars and Innovative Research Team in University IRT1278

More Information

Author Bio:
PENG Xiaolin, PhD, specialize in image restoration and super-resolution. E-mail: pxlin2014@whu.edu.cn
Corresponding author:
SHEN Huanfeng, PhD, professor. E-mail: shenhf@whu.edu.com
Received Date: January 11, 2016
Published Date: June 04, 2017

Graphical Abstract

Abstract

Abstract

Total ozone data plays is essential for monitoring the spatial distribution and temporal change in the total ozone. However, since late 2006, total ozone production from OMI (ozone monitoring instrument) aboard on Aura OMTO3e satellite began show defects resulting from an OMI instrument anomaly. The missing parts accounting for one third or even more of one set data, which is a serious obstacle for normal usage. Therefore, the recovery pf missing OMTO3e data is necessary. In this paper, a multi-temporal fitting model, based on the characteristics of OMTO3e data, is proposed to reconstruct the missing data. Experimental results and comparitive quantitative evaluation, verify that the proposed method has higher feasibility and superior to traditional methods.
- Aura satellite,
- remote sensing ozone product,
- missing data,
- temporal fitting

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References

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