Michael W. Matthew

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

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 Earths 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.

MODTRAN4: radiative transfer modeling for remote sensing

MODTRAN4, the newly released version of the U.S. Air Force atmospheric transmission, radiance and flux model is being developed jointly by the Air Force Research Laboratory/Space Vehicles Directorate and Spectral Sciences, Inc. It is expected to provide the accuracy required for analyzing spectral data for both atmospheric and surface characterization. These two quantities are the subject of satellite and aircraft campaigns currently being developed and pursued by, for instance: NASA (Earth Observing System), NPOESS (National Polar Orbiting Environmental Satellite System), and the European Space Agency (GOME--Global Ozone Monitoring Experiment). Accuracy improvements in MODTRAN relate primarily to two major developments: (1) the multiple scattering algorithms have been made compatible with the spectroscopy by adopting a corrected-k approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) radiative transfer calculations can be conducted with a Beer-Lambert formulation that improves the treatment of path inhomogeneities. Other code enhancements include the incorporation of solar azimuth dependence in the DISORT- based multiple scattering model, the introduction of surface BRDF (Bi-directional Radiance Distribution Functions) models and 15 cm-1 band model for improved computational speed.

MODTRAN4 radiative transfer modeling for atmospheric correction

MODTRAN4, the latest publicly released version of MODTRAN, provides many new and important options for modeling atmospheric radiation transport. A correlated-k algorithm improves multiple scattering, eliminates Curtis-Godson averaging, and introduces Beers Law dependencies into the band model. An optimized 15 cm-1 band model provides over a 10-fold increase in speed over the standard MODTRAN 1 cm-1 band model with comparable accuracy when higher spectral resolution results are unnecessary. The MODTRAN ground surface has been upgraded to include the effects of Bidirectional Reflectance Distribution Functions (BRDFs) and Adjacency. The BRDFs are entered using standard parameterizations and are coupled into line-of-sight surface radiance calculations.

Analysis of Hyperion data with the FLAASH atmospheric correction algorithm

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 Earths 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 spectra; recalibration algorithm, which has been incorporated into FLAASH, is described. Results from processing Hyperion data with FLAASH are discussed.

Remote bathymetry of the littoral zone from AVIRIS, LASH, and QuickBird imagery

An efficient, physics-based remote bathymetry method for the littoral zone is described and illustrated with applications to QuickBird, Littoral Airborne Sensor: Hyperspectral (LASH), and Airborne Visible/Infrared Spectrometer (AVIRIS) spectral imagery. The method combines atmospheric correction, water reflectance spectral simulations, and a linear unmixing bathymetry algorithm that accounts for water surface reflections, thin clouds, and variable bottom brightness, and can incorporate blends of bottom materials. Results include depth maps, bottom color visualizations, and in favorable cases, approximate descriptions of the water composition. In addition, atmospheric correction was advanced through new capabilities added to the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and Moderate Resolution Transmittance (MODTRAN) codes, including characterization of the aerosol wavelength dependence and a discrete-ordinate-method radiative transfer scaling technique for rapid calculation of multiply scattered radiance.

Speed and accuracy improvements in FLAASH atmospheric correction of hyperspectral imagery

Abstract. Remotely sensed spectral imagery of the earth’s surface can be used to fullest advantage when the influence of the atmosphere has been removed and the measurements are reduced to units of reflectance. Here, we provide a comprehensive summary of the latest version of the Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes atmospheric correction algorithm. We also report some new code improvements for speed and accuracy. These include the re-working of the original algorithm in C-language code parallelized with message passing interface and containing a new radiative transfer look-up table option, which replaces executions of the MODTRAN® model. With computation times now as low as ~10  s per image per computer processor, automated, real-time, on-board atmospheric correction of hyper- and multi-spectral imagery is within reach.

MODTRAN4-based atmospheric correction algorithm: FLAASH (fast line-of-sight atmospheric analysis of spectral hypercubes)

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 affedted by variations in lighting conditions. Atmospheric Correction (also referred to as Atmospheric Compensation, Characterization, etc.) Algorithms (ACAs) are used in application of remotely sensed HSI datat 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.

MODTRAN4 : Radiative transfer modeling for remote sensing

MODTRAN4, the newly released version of the U.S. Air Force atmospheric transmission, radiance and flux model is being developed jointly by the Air Force Research Laboratory / Space Vehicles Directorate (AFRL / VS) and Spectral Sciences, Inc. It is expected to provide the accuracy required for analyzing spectral data for both atmospheric and surface characterization. These two quantities are the subject of satellite and aircraft campaigns currently being developed and pursued by, for instance: NASA (Earth Observing System), NPOESS (National Polar Orbiting Environmental Satellite System), and the European Space Agency (GOME - Global Ozone Monitoring Experiment). Accuracy improvements in MODTRAN relate primarily to two major developments: (1) the multiple scattering algorithms have been made compatible with the spectroscopy by adopting a correlated-^ approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) radiative transfer calculations can be conducted with a Beer-Lambert formulation that improves the treatment of path inhomogeneities. Other code enhancements include the incorporation of solar azimuth dependence in the DISORT-based multiple scattering model, the introduction of surface BRDF (Bi-directional Radiance Distribution Functions) models and a 15 cm-1 band model for improved computational speed. Finally, recent changes to the HITRAN data base, relevant to the 0.94 and 1.13 um bands of water vapor, have been incorporated into the MODTRAN4 databases.

Laser Raman sensor for measurement of trace-hydrogen gas

A new optical hydrogen sensor based on spontaneous Raman scattering of laser light has been designed and constructed for rugged field use. It provides good sensitivity (better than 100 parts in 10(6)), rapid response (several seconds), and the inherent Raman characteristics of linearity and background gas independence of the signal. Efficient light collection and discrimination by using fast optics and a bandpass interference filter compensate for the inefficiency of the Raman-scattering process. A multipass optical cavity with a Herriott-type configuration provides intense illumination from an air-cooled cw gas laser. The observed performance is in good agreement with the theoretical signal and noise level predictions.

Shadow-insensitive material detection/classification with atmospherically corrected hyperspectral imagery

Shadow-insensitive detection or classification of surface materials in atmospherically corrected hyperspectral imagery can be achieved by expressing the reflectance spectrum as a linear combination of spectra that correspond to illumination by the direct sum and by the sky. Some specific algorithms and applications are illustrated using HYperspectral Digital Imagery Collection Experiment (HYDICE) data.