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Proceedings Paper

Water vapor retrieval from near-IR measurements of polarized scanning atmospheric corrector
Author(s): Lili Qie; Yuanming Ning; Yang Zhang; Xingfeng Chen; Yan Ma; Zhengqiang Li; Wenyu Cui
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Paper Abstract

Water vapor and aerosol are two key atmospheric factors effecting the remote sensing image quality. As water vapor is responsible for most of the solar radiation absorption occurring in the cloudless atmosphere, accurate measurement of water content is important to not only atmospheric correction of remote sensing images, but also many other applications such as the study of energy balance and global climate change, land surface temperature retrieval in thermal remote sensing. A multi-spectral, single-angular, polarized radiometer called Polarized Scanning Atmospheric Corrector (PSAC) were developed in China, which are designed to mount on the same satellite platform with the principle payload and provide essential parameters for principle payload image atmospheric correction. PSAC detect water vapor content via measuring atmosphere reflectance at water vapor absorbing channels (i.e. 0.91 μm) and nearby atmospheric window channel (i.e. 0.865μm). A near-IR channel ratio method was implemented to retrieve column water vapor (CWV) amount from PSAC measurements. Field experiments were performed at Yantai, in Shandong province of China, PSAC aircraft observations were acquired. The comparison between PSAC retrievals and ground-based Sun-sky radiometer measurements of CWV during the experimental flights illustrates that this method retrieves CWV with relative deviations ranging from 4% ~ 13%. This method retrieve CWV more accurate over land than over ocean, as the water reflectance is low.

Paper Details

Date Published: 19 February 2018
PDF: 6 pages
Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 106070N (19 February 2018); doi: 10.1117/12.2284282
Show Author Affiliations
Lili Qie, Institute of Remote Sensing and Digital Earth (China)
Yuanming Ning, Lunar Exploration and Space Engineering Ctr. (China)
Yang Zhang, Institute of Remote Sensing and Digital Earth (China)
Xingfeng Chen, Institute of Remote Sensing and Digital Earth (China)
Yan Ma, Institute of Remote Sensing and Digital Earth (China)
Zhengqiang Li, Institute of Remote Sensing and Digital Earth (China)
Wenyu Cui, Anhui Institute of Optics and Fine Mechanics (China)


Published in SPIE Proceedings Vol. 10607:
MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Jun Zhang; Hongshi Sang, Editor(s)

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