2014Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIERequires access

Long-wave infrared surface reflectance spectra retrieved from Telops Hyper-Cam imagery

S. M. Adler‐Golden, Patrick F. Conforti, Marc-André Gagnon, P. Tremblay, Martin Chamberland

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Abstract

Processing long-wave infrared (LWIR) hyperspectral imagery to surface emissivity or reflectance units via atmospheric compensation and temperature-emissivity separation (TES) affords the opportunity to remotely classify and identify solid materials with minimal interference from atmospheric effects. This paper describes an automated atmospheric compensation and TES method, called FLAASH®-IR (Fast Line-of-sight Atmospheric Analysis of Spectral Hypecubes-- Infrared), and its application to ground-to-ground imagery taken with the Telops Inc. Hyper-Cam interferometric hyperspectral imager. The results demonstrate that clean, quantitative surface spectra can be obtained, even with highly reflective (low emissivity) objects such as bare metal and in the presence of some illumination from the surroundings. In particular, the atmospheric compensation process suppresses the spectral features due to atmospheric water vapor and ozone, which are especially prominent in reflected sky radiance.

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What this paper is about

Processing long-wave infrared (LWIR) hyperspectral imagery to surface emissivity or reflectance units via atmospheric compensation and temperature-emissivity separation (TES) affords the opportunity to remotely classify and identify solid materials with minimal interference from atmospheric effects. This paper describes an automated atmospheric compensation and TES method, called FLAASH®-IR (Fast Line-of-sight Atmospheric Analysis of Spectral Hypecubes-- Infrared), and its application to ground-to-ground imagery taken with the Telops Inc. Hyper-Cam interferometric hyperspectral imager. The results demonstrate that clean, quantitative surface spectra can be obtained, even with highly reflective (low emissivity) objects such as bare metal and in the presence of some illumination from the surroundings. In particular, the atmospheric compensation process suppresses the spectral features due to atmospheric water vapor and ozone, which are especially prominent in reflected sky radiance.

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Available abstract

Processing long-wave infrared (LWIR) hyperspectral imagery to surface emissivity or reflectance units via atmospheric compensation and temperature-emissivity separation (TES) affords the opportunity to remotely classify and identify solid materials with minimal interference from atmospheric effects. This paper describes an automated atmospheric compensation and TES method, called FLAASH®-IR (Fast Line-of-sight Atmospheric Analysis of Spectral Hypecubes-- Infrared), and its application to ground-to-ground imagery taken with the Telops Inc. Hyper-Cam interferometric hyperspectral imager. The results demonstrate that clean, quantitative surface spectra can be obtained, even with highly reflective (low emissivity) objects such as bare metal and in the presence of some illumination from the surroundings. In particular, the atmospheric compensation process suppresses the spectral features due to atmospheric water vapor and ozone, which are especially prominent in reflected sky radiance.

Key concepts: Radiance, Hyperspectral imaging, Remote sensing, Emissivity, Atmospheric correction, Infrared, Environmental science, Infrared window

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