Ronald B. Lockwood

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.

Hyperspectral Detection Algorithms: Use Covariances or Subspaces?

There are two broad classes of hyperspectral detection algorithms.1, 2 Algorithms in the first class use the spectral covariance matrix of the background clutter; in contrast, algorithms in the second class characterize the background using a subspace model. In this paper we show that, due to the nature of hyperspectral imaging data, the two families of algorithms are intimately related. The link between the two representations of the background clutter is the low-rank of the covariance matrix of natural hyperspectral backgrounds and its relation to the spectral linear mixture model. This link is developed using the method of dominant mode rejection. Finally, the effects of regularization

Vibrational relaxation of NO(υ=1) by oxygen atoms

The rate constant kO(υ=1) for NO(υ=1) vibrational relaxation by O has been measured at room temperature using a laser photolysis-laser probe technique. Vibrationally excited NO and relaxer O atoms were formed using 355 nm laser photolysis of a dilute mixture of NO2 in argon bath gas. The time evolution of both the NO(υ=1) and the O atoms was monitored using laser-induced fluorescence (LIF). The required absolute O-atom densities were obtained through a comparison of O-atom LIF signals from the photolysis source and from a titrated cw microwave source. At early times the O atoms constitute the most important loss mechanism for the nascently produced NO(υ=1). Possible effects from NO(υ=1) vibrational ladder-climbing and from thermal expansion have been shown to be minimal. The rate constant kO(υ=1)=(2.4±0.5)×10−11 cm3 s−1 determined herein is a factor of 2 to 3 lower than the generally accepted value of kO(υ=1) used in thermospheric modeling. The present value for kO(υ=1) is the same, within the error bars,...

Iterative algorithms for unmixing of hyperspectral imagery

This paper addresses the use of multiplicative iterative algorithms to compute the abundances in unmixing of hyperspectral pixels. The advantage of iterative over direct methods is that they allow incorporation of positivity and sum-to-one constraints of the abundances in an easy fashion while also allowing better regularization of the solution for the ill-conditioned case. The derivation of two iterative algorithms based on minimization of least squares and Kulback-Leibler distances are presented. The resulting algorithms are the same as the ISRA and EMML algorithms presented in the emission tomography literature respectively. We show that the ISRA algorithm and not the EMML algorithm computes the maximum likelihood estimate of the abundances under Gaussian assumptions while the EMML algorithm computes a minimum distance solution based on the Kulback-Leibler generalized distance. In emission tomography, the EMML computes the maximum likelihood estimate of the reconstructed image. We also show that, since the unmixing problem is in general overconstrained and has no solutions, acceleration techniques for the EMML algorithm such as the RBI-EMML will not converge.

MightySat II.1 hyperspectral imager: summary of on-orbit performance

The primary payload on a small-satellite, the Air Force Research Laboratorys MightySat II.1, is a spatially modulated Fourier Transform Hyperspectral Imager (FTHSI) designed for terrain classification. The heart of this instrument is a solid block Sagnac interferometer with 85cm-1 spectral resolution over the 475nm to 1050nm bands and 30m spatial resolution. Coupled with this hyperspectral imager is a Quad-C40 card, used for on-orbit processing. The satellite was launched on 19 July 2000 into a 575km, 97.8 degree inclination, sun-synchronous orbit. The hyperspectral imager collected its first data set on 1 August 2000, and has been in continuous operation since that time. To the best of our knowledge, the MightySat II.1 sensor is the first true hyperspectral imager to be successfully operated in space. The paper will describe the satellite and instrument, pre-launch calibration results, on-orbit performance, and the calibration process used to characterize the sensor. We will also present data on the projected lifetime of the sensor along with samples of the types of data being collected.

On The Spectral Correlation Structure of Hyperspectral Imaging Data

Spectral correlation, as quantified by the elements of the covariance matrix, plays a prominent role in the development of optimum statistical algorithms for hyperspectral data exploitation. Indeed, the most useful statistical models for hyperspectral image modeling, namely the multivariate normal distribution and the multivariate t-distribution, are parameterized by the spectral covariance matrix. The inverse of the covariance matrix, however, also has important interpretations. In this paper, we discuss the properties connected with the inverse covariance matrix and we describe their use in hyperspectral data analysis.

Testing an automated unsupervised classification algorithm with diverse land covers

We test a new automatic unsupervised classification algorithm designed for hyperspectral images. The algorithm automatically determines the number of clusters in the image by finding dense regions of the pixel cloud. A variation on migrating means clustering is used to find the dense regions. Five scenes from an airborne AVIRIS data set are used to test the algorithm. The algorithm successfully finds the dominant land covers and many areally small land covers, such as roads and other man-made structures.

Background spectral library for Fort A.P. Hill, Virginia

We describe development of a background spectral library for Fort A. P. Hill, located in northeastern Virginia, based on hyperspectral images and an extensive land cover database. The database was used to identify areas of uniform land cover. The library contains means and standard deviations for 15 spectra measured in these uniform areas. Terrain categorization products consist of classification maps and fractional abundance maps determined by linear mixture analysis. There is excellent qualitative agreement between the linear unmixing results and the known land covers.

Fractional population of NO(v − 1) from vibrational relaxation of NO(v = 2, 3) by O and NO

Significant populations of NO in excited vibrational levels v 2 have recently been observed in the lower thermosphere, for which the relaxation rates and pathways are largely governed by collisions with O atoms. Laboratory experiments can provide accurate kinetic parameters for modelling and interpreting such steady-state v-dependent population distributions. In this study, a two-laser, pump–probe arrangement has been used to measure the fractional population of NO(v − 1) arising from the collision-induced relaxation of NO(v = 3) by O atoms and, in an ancillary experiment, NO(v = 2, 3) by NO. The branching fraction χ O (v = 3→2) = 0.35 ± 0.12 for O-atom collisions. The χ O value is consistent with a long-lived NO 2 * collision complex, in which the total energy is randomly distributed among the internal degrees of freedom prior to dissociation, and agrees with a recent quasiclassical trajectory calculation. For collisions with NO, χ NO (v = 3→2) = 0.73 ± 0.19, indicating a significant multiquantum component. The branching fraction χ NO (v = 2→1) = 1.19 ± 0.31 can be considered an effective value only, since its interpretation relies on an assumption regarding the relaxation mechanism. The rate constants k O (v = 3) = (3.0 ± 0.6) × 10 −11 cm 3 s −1 for the vibrational relaxation of NO(v = 3) by O atoms, and k NO (v = 2) = (2.7 ± 0.5) × 10 −12 cm 3 s −1 and k NO (v = 3) = (3.4 ± 0.7) × 10 −12 cm 3 s −1 for the relaxation of NO(v = 2, 3) by NO have also been obtained, and are in good agreement with previous results from this laboratory.