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27 April 2009 Atmospheric sampling for VNIR/SWIR hyperspectral data analysis
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Abstract
Data from hyperspectral sensors calibrated to spectral radiance allow the prediction of spectra to be measured under different conditions through the use of physical models. Predicted spectra used in material detection algorithms, for example, are typically computed over a wide range of environmental conditions since environmental conditions are often unknown in advance of the measurements, and sometimes even during the data collections proper. A radiative transfer (RT) code such as MODTRAN® is commonly used to generate such predicted spectra. This requires the specification of a set of environmental conditions. We have developed an automated method for generating environmental conditions to obtain a uniform sampling of spectra in the VNIR/SWIR radiance domain. Our technique accounts for the nonlinear relationship between the environmental inputs and the RT spectral functions that are the outputs of the RT codes. An initial set of bounding conditions is used to define the bounding edges of the radiance domain. Based on the edges, the bounding surfaces are determined. Then, based on the bounding surfaces, the volume is populated. Variations of the sun angle, vertical-path-integrated water vapor density, and aerosol or cloud scatterer density and type are considered. Our approach to atmospheric modeling is demonstrated in signature comparisons using hyperspectral imagery acquired by the Hyperion VNIR/SWIR sensor.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Perry Fuehrer, Glenn Healey, Brian Rauch, David Slater, and Anthony Ratkowski "Atmospheric sampling for VNIR/SWIR hyperspectral data analysis", Proc. SPIE 7334, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, 73340S (27 April 2009); https://doi.org/10.1117/12.818347
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