The incorporation of atmospheric variability in hyperspectral synthetic scene simulation

Brian M. Dobbs; Niek J. Sanders; John R. Schott

doi:10.1117/12.682733

1 September 2006 The incorporation of atmospheric variability in hyperspectral synthetic scene simulation

Brian M. Dobbs, Niek J. Sanders, John R. Schott

Proceedings Volume 6302, Imaging Spectrometry XI; 63020C (2006) https://doi.org/10.1117/12.682733
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

This paper describes an effort to improve the modeling of the atmosphere in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The goal of this research can be divided into two main areas. The first is to improve the existing manner in which DIRSIG samples and references the atmosphere. The second is to give DIRSIG the ability to incorporate atmospheric inhomogeneities, as well as, the ability to accurately model them. DIRSIG has limitations in how it currently samples the atmosphere. From a geometric standpoint, it does not fully sample the energy which is scattered by the atmosphere towards the sensor (upwelled radiance). There are also other geometric issues which lead to inaccurate modeling results. One significant inaccuracy is the fact that DIRSIG can miscalculate the atmospheric effects resulting from modeling objects with non-zero altitudes. The plan is to correct this by completely reworking the procedure and geometry used by DIRSIG to sample the atmosphere. This research also addresses the effects of an inhomogeneous atmosphere and includes methods to model this variability in synthetic scenes. DIRSIG currently utilizes a single atmospheric look up table (LUT) that it references when creating an image. This LUT contains the information DIRSIG will need to predict the various radiance and transmission values for a homogeneous sky. There is no ability for DIRSIG to make one part of the sky optically thick, and the other clear. This will be remedied by having DIRSIG create a series of LUTs with different atmospheric properties that it can reference. With this ability DIRSIG can reference an optically different atmosphere depending on its viewing geometry, allowing a horizontally varying atmosphere.

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Brian M. Dobbs, Niek J. Sanders, and John R. Schott "The incorporation of atmospheric variability in hyperspectral synthetic scene simulation", Proc. SPIE 6302, Imaging Spectrometry XI, 63020C (1 September 2006); https://doi.org/10.1117/12.682733

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KEYWORDS

Atmospheric modeling

Sensors

Atmospheric sensing

Data modeling

Atmospheric optics

Atmospheric particles

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