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Proceedings Paper

The importance of accurate atmospheric modeling
Author(s): Dylan Payne; John Schroeder; Pang Liang
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Paper Abstract

This paper will focus on the effect of atmospheric conditions on EO sensor performance using computer models. We have shown the importance of accurately modeling atmospheric effects for predicting the performance of an EO sensor. A simple example will demonstrated how real conditions for several sites in China will significantly impact on image correction, hyperspectral imaging, and remote sensing. The current state-of-the-art model for computing atmospheric transmission and radiance is, MODTRAN® 5, developed by the US Air Force Research Laboratory and Spectral Science, Inc. Research by the US Air Force, Navy and Army resulted in the public release of LOWTRAN 2 in the early 1970’s. Subsequent releases of LOWTRAN and MODTRAN® have continued until the present. Please verify that (1) all pages are present, (2) all figures are correct, (3) all fonts and special characters are correct, and (4) all text and figures fit within the red margin lines shown on this review document. Complete formatting information is available at Return to the Manage Active Submissions page at and approve or disapprove this submission. Your manuscript will not be published without this approval. Please contact with any questions or concerns. The paper will demonstrate the importance of using validated models and local measured meteorological, atmospheric and aerosol conditions to accurately simulate the atmospheric transmission and radiance. Frequently default conditions are used which can produce errors of as much as 75% in these values. This can have significant impact on remote sensing applications.

Paper Details

Date Published: 8 November 2014
PDF: 16 pages
Proc. SPIE 9259, Remote Sensing of the Atmosphere, Clouds, and Precipitation V, 92591D (8 November 2014); doi: 10.1117/12.2073519
Show Author Affiliations
Dylan Payne, Ontar Corp. (United States)
John Schroeder, Ontar Corp. (United States)
Pang Liang, HystarMap Technology Co., Ltd. (China)

Published in SPIE Proceedings Vol. 9259:
Remote Sensing of the Atmosphere, Clouds, and Precipitation V
Eastwood Im; Song Yang; Peng Zhang, Editor(s)

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