Paper
1 September 2015 Improved atmospheric retrievals of hyperspectral data using geometric constraints
Author Affiliations +
Abstract
Within urban environments and other complex illumination conditions, tilted target surface or partial sky occlusions from nearby raised objects can have a significant impact on a target’s radiance observed from a spectral sensor. At the pixel level, these terms can be predicted and corrected for by modeling the impact collocated height data has on the scene radiometry. After properly accounting for these impacts, a Lambertian material’s retrieved spectral reflectivity should be the same at any location or orientation within the scene. This paper proposes a novel approach for using this constraint to iterate on atmospheric aerosol parameters until the difference of retrieved spectral reflectance of two pixels of the same material, but under different illumination conditions, is minimized.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth Ewald, Emmett J. Ientilucci, Alan Buswell, and John Jacobson "Improved atmospheric retrievals of hyperspectral data using geometric constraints", Proc. SPIE 9611, Imaging Spectrometry XX, 961113 (1 September 2015); https://doi.org/10.1117/12.2188376
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Reflectivity

Atmospheric particles

Visibility

Sun

Aerosols

Binary data

LIDAR

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