Anthony J. Ratkowski

Status of atmospheric correction using a MODTRAN4-based algorithm

The present disclosure is directed to maintaining horizontal alignment of peeling and cleaning rolls in a shrimp peeler and cleaner by restricting rotary movement of the posts without inhibiting up and down movement of adjacent posts at the base of which are journalled the peeling rolls. This is accomplished by molding flat walled projections at the base of the posts over which are received a locking member having a plurality of openings therethrough the walls of which are complemental to the flat walls of the projections in one direction and which are slightly greater in the other direction to permit relative vertical movement between adjacent posts.

The sequential maximum angle convex cone (SMACC) endmember model

A new endmember extraction method has been developed that is based on a convex cone model for representing vector data. The endmembers are selected directly from the data set. The algorithm for finding the endmembers is sequential: the convex cone model starts with a single endmember and increases incrementally in dimension. Abundance maps are simultaneously generated and updated at each step. A new endmember is identified based on the angle it makes with the existing cone. The data vector making the maximum angle with the existing cone is chosen as the next endmember to add to enlarge the endmember set. The algorithm updates the abundances of previous endmembers and ensures that the abundances of previous and current endmembers remain positive or zero. The algorithm terminates when all of the data vectors are within the convex cone, to some tolerance. The method offers advantages for hyperspectral data sets where high correlation among channels and pixels can impair un-mixing by standard techniques. The method can also be applied as a band-selection tool, finding end-images that are unique and forming a convex cone for modeling the remaining hyperspectral channels. The method is described and applied to hyperspectral data sets.

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.

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.

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.

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.

MODTRAN4, version 2: Radiative transfer modeling

MODTRAN4, version 2, will soon be released by the U.S. Air Force Geophysics Laboratory; it is an extension of the MODTRAN4, v1, atmospheric transmission, radiance and flux model developed jointly by the Air Force Research Laboratory / Space Vehicles Directorate (AFRL / VS) and Spectral Sciences, Inc. The primary accuracy improvements in MODTRAN4 remain those previously published: (1) the multiple scattering correlated-k approach to describe the statistically expected transmittance properties for each spectral bin and atmospheric layer, and (2) the Beer-Lambert formulation that improves the treatment of path inhomogeneities. Version 2 code enhancements are expected to include: *pressure-dependent atmospheric profile input, as an auxiliary where the hydrostatic equation is integrated explicitly to compute the altitudes, *CFC cross-sections with band model parameters derived from pseudo lines, *additional pressure-induced absorption features from O2, and *a new 5 cm-1 band model option. Prior 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. Last years changes to the HITRAN database, relevant to the 0.94 and 1.13 micrometers bands of water vapor, have been maintained in the MODTRAN4,v2 databases.

Improved reflectance retrieval from hyper-and multispectral imagery without prior scene or sensor information

We describe improvements to a recently developed VNIR-SWIR atmospheric correction method for hyper- and multispectral imagery, dubbed QUAC (QUick Atmospheric Correction). It determines the atmospheric compensation parameters directly from the information contained within the scene using the observed pixel spectra. The newest implementation of QUAC is based on the assumption that the average reflectance of a collection of diverse material spectra, such as the endmember spectra in a scene, is effectively scene independent. This enables 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 on aircraft and spacecraft. QUAC is applied to a diverse collection of hyper- and multispectral data sets and the results are compared to those obtained with the physics-based atmospheric correction code FLAASH (Fast Line of sight Atmospheric Analysis of Spectral Hypercubes).