Paper
31 October 2005 Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm
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Abstract
Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Timothy Perkins, Steven Adler-Golden, Michael Matthew, Alexander Berk, Gail Anderson, James Gardner, and Gerald Felde "Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm", Proc. SPIE 5979, Remote Sensing of Clouds and the Atmosphere X, 59790E (31 October 2005); https://doi.org/10.1117/12.626526
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Cited by 35 scholarly publications and 1 patent.
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KEYWORDS
Reflectivity

Atmospheric corrections

Atmospheric modeling

Visibility

Sensors

Aerosols

Calibration

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