Alexander Berk

MODTRAN Cloud and Multiple Scattering Upgrades with Application to AVIRIS

Abstract Recent upgrades to the MODTRAN atmospheric radiation code improve the accuracy of its radiance predictions, especially in the presence of clouds and thick aerosols, and for multiple scattering in regions of strong molecular line absorption. The current public-released version of MODTRAN (MODTRAN3.7) features a generalized specification of cloud properties, while the current research version of MODTRAN (MODTRAN4) implements a correlated-k (CK) approach for more accurate calculation of multiply scattered radiance. Comparisons to cloud measurements demonstrate the viability of the CK approach. The impact of these upgrades on predictions for AVIRIS viewing scenarios is discussed for both clear and clouded skies; the CK approach provides refined predictions for AVIRIS nadir and near-nadir viewing.

MODTRAN5: a reformulated atmospheric band model with auxiliary species and practical multiple scattering options

The MODTRAN5 radiation transport (RT) model is a major advancement over earlier versions of the MODTRAN atmospheric transmittance and radiance model. New model features include (1) finer spectral resolution via the Spectrally Enhanced Resolution MODTRAN (SERTRAN) molecular band model, (2) a fully coupled treatment of auxiliary molecular species, and (3) a rapid, high fidelity multiple scattering (MS) option. The finer spectral resolution improves model accuracy especially in the mid- and long-wave infrared atmospheric windows; the auxiliary species option permits the addition of any or all of the suite of HITRAN molecular line species, along with default and user-defined profile specification; and the MS option makes feasible the calculation of Vis-NIR databases that include high-fidelity scattered radiances.

MODTRAN5: 2006 update

The MODTRAN5 radiation transport (RT) model is a major advancement over earlier versions of the MODTRAN atmospheric transmittance and radiance model. New model features include (1) finer spectral resolution via the Spectrally Enhanced Resolution MODTRAN (SERTRAN) molecular band model, (2) a fully coupled treatment of auxiliary molecular species, and (3) a rapid, high fidelity multiple scattering (MS) option. The finer spectral resolution improves model accuracy especially in the mid- and long-wave infrared atmospheric windows; the auxiliary species option permits the addition of any or all of the suite of HITRAN molecular line species, along with default and user-defined profile specification; and the MS option makes feasible the calculation of Vis-NIR databases that include high-fidelity scattered radiances. Validations of the new band model algorithms against line-by-line (LBL) codes have proven successful.

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.

MODELS OVERESTIMATE DIFFUSE CLEAR-SKY SURFACE IRRADIANCE: A CASE FOR EXCESS ATMOSPHERIC ABSORPTION

Radiative transfer models consistently overestimate surface diffuse downward irradiance in cloud-free atmospheres by 9 to 40% at two low altitude sites while correctly calculating direct-normal Solar irradiance. For known systematic and random measurement errors and for realistic aerosol optical properties, the discrepancy can be resolved by a reduction in the vertical aerosol optical thickness (AOT) inferred from sunphotometric measurements by an average 0.02 ± 0.01 for 32 cases examined, together with a compensating increase in a continuum-like atmospheric absorptance over the solar spectrum of ∼5.0% ± 3.0%. This phenomenon is absent at two high altitude sites, where models and measurements agree to within their mutual uncertainties. Examination of apparent AOT at several locations around the globe also indicates presence of such excess atmospheric absorption. The proposed absorption and corresponding reduction in AOT would have important consequences for climate prediction and remote sensing.

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.

Validation of the QUick atmospheric correction (QUAC) algorithm for VNIR-SWIR multi- and hyperspectral imagery

We describe a new visible-near infrared short-wavelength infrared (VNIR-SWIR) atmospheric correction method for multi- and hyperspectral imagery, dubbed QUAC (QUick Atmospheric Correction) that also enables retrieval of the wavelength-dependent optical depth of the aerosol or haze and molecular absorbers. It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The approach is based on the empirical finding that the spectral standard deviation of a collection of diverse material spectra, such as the endmember spectra in a scene, is essentially spectrally flat. It allows the retrieval of reasonably accurate reflectance spectra even when the sensor does not have a proper radiometric or wavelength calibration, or when the solar illumination intensity is unknown. The computational speed of the atmospheric correction method is significantly faster than for the first-principles methods, making it potentially suitable for real-time applications. The aerosol optical depth retrieval method, unlike most prior methods, does not require the presence of dark pixels. QUAC is applied to atmospherically correction several AVIRIS data sets and a Landsat-7 data set, as well as to simulated HyMap data for a wide variety of atmospheric conditions. Comparisons to the physics-based Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) code are also presented.

A new method for atmospheric correction and aerosol optical property retrieval for VIS-SWIR multi- and hyperspectral imaging sensors: QUAC (QUick atmospheric correction)

Abstract : We describe a new VNIR-SWIR atmospheric correction method for multi- and hyperspectral imagery, dubbed QUAC (QUick Atmospheric Correction) that also enables retrieval of the wavelength-dependent optical depth of the aerosol or haze and molecular absorbers. It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The approach is based on the empirical finding that the spectral standard deviation of a collection of diverse material spectra, such as the endmember spectra in a scene, is essentially spectrally flat. It allows the retrieval of reasonably accurate reflectance spectra even when the sensor does not have a proper radiometric or wavelength calibration, or when the solar illumination intensity is unknown. The computational speed of the atmospheric correction method is significantly faster than for the first-principles methods, making it potentially suitable for realtime applications. The aerosol optical depth retrieval method, unlike most prior methods, does not require the presence of dark pixels. In this paper, QUAC is applied to atmospherically correction several AVIRIS data sets. Comparisons to the physics-based FLAASH code are also presented.