Steven C. Richtsmeier

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.

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.

Validation and refinement of hyperspectral/multispectral atmospheric compensation using shadowband radiometers

First-principles atmospheric compensation of Earth-viewing spectral imagery requires atmospheric property information derived from the image itself or measured independently. A field experiment was conducted in May, 2003 at Davis, CA to investigate the consistency of atmospheric properties and surface reflectances derived from simultaneous ground-, aircraft- and satellite-based spectral measurements. The experiment involved the simultaneous collection of HyMap hyperspectral and Landsat-7 multispectral imagery, in situ reflectance spectra of calibration surfaces, and sun and sky radiances from ultraviolet and visible multifilter rotating shadowband radiometers (MFRSRs). The data were analyzed using several different radiation transport and atmospheric compensation algorithms. Reasonable self-consistency was found between aerosol property retrievals from the radiometers and from dark pixels of the imagery, and, when using the most accurate algorithm, there was excellent agreement between the retrieved surface spectra and the ground truth measurements.

Fast Monte Carlo Full Spectrum Scene Simulation

This paper discusses the formulation and implementation of an acceleration approach for the MCScene code, a high fidelity model for full optical spectrum (UV to LWIR) hyperspectral image (HSI) simulation. The MCScene simulation is based on a Direct Simulation Monte Carlo approach for modeling 3D atmospheric radiative transport, as well as spatially inhomogeneous surfaces including surface BRDF effects. The model includes treatment of land and ocean surfaces, 3D terrain, 3D surface objects, and effects of finite clouds with surface shadowing. This paper will review an acceleration algorithm that exploits spectral redundancies in hyperspectral images. In this algorithm, the full scene is determined for a subset of spectral channels, and then this multispectral scene is unmixed into spectral end members and end member abundance maps. Next, pure end member pixels are determined at their full hyperspectral resolution, and the full hyperspectral scene is reconstructed from the hyperspectral end member spectra and the multispectral abundance maps. This algorithm effectively performs a hyperspectral simulation while requiring only the computational time of a multispectral simulation. The acceleration algorithm will be demonstrated, and errors associated with the algorithm will be analyzed.

TEMPERATURE AND TEMPERATURE PROFILE MEASUREMENTS IN THE COMBUSTOR FLOWPATH USING STRUCTURED EMISSION THERMOGRAPHY

Structured Emission Thermometry (SET) is a new optical technique for deriving temperature and species concentrations in high-temperature regions of a combustor flow-path from measurements of water and soot emission spectra in the 1 micron region. A prototype instrument has been built for gas- and liquid-fuel combustors with temperatures ranging from 1400–2500K (2100–4000F). This instrument can be used for test stand instrumentation and routine monitoring in fixed installations. With further evolution, the technique may be suitable for an aircraft engine control system. The emissions are measured along narrow lines of sight using small, simple passive fiber probes placed at a short standoff distance from the hot gas flow-path. With proper placement of multiple probes, data may be collected over overlapping lines of sight and inverted to produce a low-resolution spatial map of the temperature and emitter density in the flow-path. In this work, we describe a series of combustor measurements, including cross-validation measurements in a well-controlled laboratory flame and measurements in combustor test stands. Both line-of-sight measurements and reconstructed temperature profiles are presented and discussed.Copyright

Cloud effects in hyperspectral imagery from first-principles scene simulations

Clouds and cloud fields introduce important backscattering, obscuration, shadowing and radiative trapping effects in visible-NIR(near-infrared)-SWIR(short-wavelength infrared) hyperspectral imagery of the ground, especially in off-nadir (slant) viewing geometries where cloud thickness effects reduce the cloud-free line of sight (CFLOS). An investigation of these effects was conducted using monochromatic, multispectral and hyperspectral scene simulations performed with the Spectral Sciences, Inc. MCScene Monte Carlo code. Cloud fields were obtained from the Cloud Scene Simulation Model (CSSM) of Cianciolo and Raffensberger. The simulations took advantage of a data-fusion-based noise-removal method that enabled a dramatic reduction in computation time. Illumination levels at the sunlit ground showed enhancements of up to ~50% due to cloud scattering. Illumination in the cloud shadows was 20% of the full solar illumination or greater, with cloud optical depths of up to 10. Most of this illumination arises from solar scattering off the cloud tops and sides; however, a significant part can be ascribed to radiative trapping between the ground and the clouds, as represented by a local atmospheric spherical albedo. A simulation of a hyperspectral scene with cloud shadows was found to reproduce shadowing effects found in real data. Deeper shadowing is observed with increasing wavelength and in water-band regions, consistent with a previous analysis of cloud shadows in real imagery. The MCScene calculations also predict shadow enhancements of column water vapor retrievals from atmospheric correction/compensation codes, also in accord with field observations. CFLOS fractions were calculated as a function of off-nadir viewing angle and were found to be very accurately represented by a semi-empirical analytical function of both angle and cloud cover.

Full optical spectrum hyperspectral scene simulation

Abstract - Full optical spectrum (UV to LWIR) hyperspectral scene simulation provides an accurate, robust, and efficient means for algorithm validation and sensor design trade studies. This paper reviews the development of a first-principles, high-fidelity HSI/MSI image simulation capability, dubbed MCScene and demonstrates how the model can be used for sensor design trade studies. MCScene incorporates all optical effects important for solar-illuminated and thermal scenes, including molecular and aerosol scattering, absorption and emission, surface scattering and emission with material-dependent bidirectional reflectance distribution functions (BRDFs), multiple scattering events, surface adjacency effects, and scattering, emission and shading by clouds, for arbitrary solar illumination and sensor viewing geometries. The “world” of the simulation is a cube that encloses a user-definable atmosphere containing molecular species, aerosols, and clouds, and a terrain representing the ground. The sensor spatial and spectral resolution, its location, and the viewing angle are also specified. 3D objects can also be inserted into the scene. A particular strength of MCScene is that a simulation can be data driven. Terrain information can be imported from USGS digital elevation maps. Surface reflectance or emissivity/temperature maps can be derived from collected imagery, thus incorporating natural spectral and spatial texturing into a simulation. Basic features of the model will be discussed and illustrated with a full spectrum simulation for a prototype hyperspectral sensor.