Spectral Sciences, Inc.

Other

United States of America As Represented by the Secretary of the Air Force

Alexander Berk

Lawrence S Bernstein

Steven M Adler-Golden

Gail P Anderson

Prabhat K Acharya

Timothy C Perkins

James H Chetwynd

Robert Y Levine

Jamine Lee

Michael W Matthew

Eric P Shettle

David C Robertson

Larry S Bernstein

Michael L Hoke

Leonid Muratov

Paul Lewis

A radiative transport band model method for prediction and analysis of high spectral resolution radiometric measurements. Atomic and molecular line center absorption is determined from finite spectral bin equivalent widths. A mathematically exact expansion for finite bin equivalent widths provides high accuracy at any desired spectral resolution. The temperature and pressure dependent Voigt line tail spectral absorption contributing to each spectral bin is pre-computed and fit to Pad&#xe9; approximants for rapid and accurate accounting of neighboring-to-distant lines. A specific embodiment has been incorporated into the MODTRAN&#x2122; radiation transport model.

Reformulated atmospheric band model method for modeling atmospheric propagation at arbitrarily fine spectral resolution and expanded capabilities.

A radiative transport band model algorithm has been developed for prediction and analysis of high spectral resolution radiometric measurements. Atomic and molecular line center absorption is determined from finite spectral bin equivalent widths. A new mathematically exact expansion for finite bin equivalent widths provides high accuracy at any desired spectral resolution. The temperature and pressure dependent Voigt line tail spectral absorption contributing to each spectral bin is pre-computed and fit to Pad&#xe9; approximants for rapid and accurate accounting of neighboring-to-distant lines.

Band model method for modeling atmospheric propagation at arbitrarily fine spectral resolution

This invention discloses several improved methods of correcting for atmospheric effects on a remote image of the Earth's surface taken from above, wherein the image comprises a number of simultaneously acquired images of the same scene, each including a large number of pixels, each at a different wavelength band, and including infrared through ultraviolet wavelengths. One method is for retrieving the aerosol/haze amount (i.e., visible range) from an assumed ratio of in-band reflectances, rather than from an assumed reflectance value. Another method is for identifying cloud-containing pixels. This is used to improve the calculation of the spatially averaged radiance L*and reflectance &#x3c1;images in standard equations. Another method greatly reduces the number of mathematical operations required to generate the reflectance values. This method operates by averaging the water vapor and &#x3c1;values over small groups of neighboring pixels, so that the same A, B, S, L*parameter values may also be assigned to all pixels within the group. Yet another new method accounts for shifts in the wavelength calibration within the image, such as would be caused by spectral 'smile'. This method loops the calculation of A, B, S and L*over a set of possible wavelength shifts with respect to the input channel centers, and assigns the appropriate set of parameters to each pixel based on a pixel-location-dependent formula for the wavelength shift.

Methods for atmospheric correction of solar-wavelength hyperspectral imagery over land

A method of automatically determining a measure of atmospheric aerosol optical properties using a multi- or hyper-spectral, multi-pixel image. A plurality of spectrally-diverse pixels are resolved from the image. A statistical spectral deviation of the spectrally-diverse pixels is determined, and then corrected for non-aerosol transmittance losses. One or more wavelength-dependent aerosol optical depths are derived from the statistical spectral deviation. Wavelength-dependent gaseous optical depths can be derived from the statistical spectral deviation.

Methods for determining a measure of atmospheric aerosol optical properties using a multi- or hyperspectral, multi-pixel image

A method of automatically compensating a multi- or hyper-spectral, multi-pixel image for atmospheric effects, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a spectral baseline from the spectrally-diverse pixels, determining a statistical spectral deviation of the spectrally-diverse pixels, normalizing the statistical spectral deviation by applying a scale factor, and compensating image pixels with both the spectral baseline and the normalized spectral deviation. Another embodiment features a method of automatically determining a measure of atmospheric aerosol optical properties using a multi- or hyper-spectral, multi-pixel image, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a statistical spectral deviation of the spectrally-diverse pixels, correcting the statistical spectral deviation for non-aerosol transmittance losses, and deriving from the statistical spectral deviation one or more wavelength-dependent aerosol optical depths. A final embodiment features a method of automatically determining a measure of atmospheric gaseous optical properties using a multi- or hyper-spectral, multi-pixel image, comprising resolving a plurality of spectrally-diverse pixels from the image, determining a statistical spectral deviation of the spectrally-diverse pixels, and deriving from the statistical spectral deviation wavelength-dependent gaseous optical depths.

Method for performing automated in-scene based atmospheric compensation for multi-and hyperspectral imaging sensors in the solar reflective spectral region

Recent upgrades to the MOTRAN 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. MODTRAN3.5 features a generalized specification of cloud properties, while research version 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.

System and method for modelling moderate resolution atmospheric

Growing community of inventors

Canton, MA, United States of America

Alexander Berk