Atmospheric correction of spectral imagery: evaluation of the FLAASH algorithm with AVIRIS data

Abstract

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. 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 (airborne visible/infrared imaging spectrometer) data, including results obtained using different processing options, and with results from the ACORN (atmospheric correction now) algorithm that derive from an older MODTRAN4 spectral database.