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With its combination of good spatial and spectral resolution, visible to near infrared spectral imaging from aircraft or spacecraft is a highly valuable technology for remote sensing of the earth's surface. Typically it is desirable to eliminate atmospheric effects on the imagery, a process known as atmospheric correction. In this paper we review the basic methodology of first-principles atmospheric correction and present results from the latest version of the FLAASH (Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes) algorithm. We show some comparisons of ground truth spectra with FLAASH-processed AVIRIS data, including results obtained using different processing options, and with results from the ACORN algorithm that derive from an older MODTRAN4 spectral database.

A combination of good spatial and spectral resolution make visible to shortwave infrared spectral imaging from aircraft or spacecraft a highly valuable technology for remote sensing of the earth's surface. Many applications require the elimination of atmospheric effects caused by molecular and particulate scattering; a process known as atmospheric correction, compensation, or removal. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) atmospheric correction code derives its physics-based algorithm from the MODTRAN4 radiative transfer code. A new spectral recalibration algorithm, which has been incorporated into FLAASH, is described. Results from processing Hyperion data with FLAASH are discussed.

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