FLAASH, a MODTRAN4-based Atmospheric Correction Algorithm, Its Application and Validation

T Cooley,GP Anderson,GW Felde,ML Hoke,AJ Ratkowski,JH Chetwynd,JA Gardner,SM Adler-Golden,MW Matthew,A Berk,LS Bernstein,PK Acharya, D Miller,P Lewis

IGARSS 2002 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM AND 24TH CANADIAN SYMPOSIUM ON REMOTE SENSING, VOLS I-VI, PROCEEDINGS REMOTE SENSING INTEGRATING OUR VIEW OF THE PLANET（2002）

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摘要

Terrain categorization and target detection algorithms applied to Hyperspectral Imagery (HSI) typically operate on the measured reflectance (of Sun and sky illumination) by an object or scene. Since the reflectance is a non-dimensional ratio, the reflectance by an object is nominally not affected by variations In lighting conditions. Atmospheric Correction (also referred to as Atmospheric 'Compensation', 'Characterization', etc.) Algorithms (ACAs) are used in applications of remotely sensed HSI data to correct for the effects of atmospheric propagation on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is an ACA created for HSI applications in the visible through shortwave infrared (Vis-SWIR) spectral regime. FLAASH derives its 'physics-based' mathematics from MODTRAN4.

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atmospheric optics,geophysical signal processing,geophysical techniques,remote sensing,terrain mapping,FLAASH,Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes,IR,MODTRAN4,algorithm,atmospheric correction,geophysical measurement technique,hyperspectral imagery,hyperspectral remote sensing,infrared,land surface,multispectral remote sensing,optical imaging,optics,reflectance,shortwave infrared,target detection,terrain categorization,terrain mapping,validation,visible