Hyperspectral spectroscopy can be used remotely to measure emitted radiation from minerals and rocks at a series of narrow and continuous wavelength bands resulting in a continuous spectrum for each pixel, thereby providing ample spectral information to identify and distinguish spectrally unique materials. Linear mixture modeling ("spectral unmixing"), a commonly used method, is based on the theory that the radiance in the thermal infrared region (8-12 μm) from a multi-mineral surface can be modeled as a linear combination of the endmembers. A linear mixture model can thus potentially model the minerals present on planetary surfaces. It works by scaling the endmember spectra so that the sum of the scaled endmember spectra matches the measured spectrum with the smallest "error" (difference). But one of the drawbacks of this established method is that mathematically, a fit with an inverted spectrum is valid, which effectively returns a negative abundance of a material. Current models usually address the problem by elimination of endmembers that have negative scale factors. Eliminating the negative abundance problem is not a major issue when the endmembers are known. However, identifying unknown target composition (like on Mars) can be a problem. The goal of this study is to improve the understanding and find a subsequent solution of the negative abundance problem for Mars analog field data obtained from airborne and ground spectrometers. We are using a well-defined library of spectra to test the accuracy of hyperspectral analysis for the identification of minerals on planetary surfaces.
Stand-off identification in the field using thermal infrared spectrometers (hyperspectral) is a maturing technique for gases and aerosols. However, capabilities to identify solid-phase materials on the surface lag substantially, particularly for identification in the field without benefit of ground truth (e.g. for "denied areas"). Spectral signatures of solid phase materials vary in complex and non-intuitive ways, including non-linear variations with surface texture, particle size, and intimate mixing. Also, in contrast to airborne or satellite measurements, reflected downwelling radiance strongly affects the signature measured by field spectrometers. These complex issues can confound interpretations or cause a misidentification in the field.
Problems that remain particularly obstinate are (1) low ambiguity identification when there is no accompanying ground truth (e.g. measurements of denied areas, or Mars surface by the 2003 Mars lander spectrometer); (2) real- or near real-time identification, especially when a low ambiguity answer is critical; (3) identification of intimate mixtures (e.g. two fine powders mixed together) and targets composed of very small particles (e.g. aerosol fallout dust, some tailings); and (4) identification of non-diffuse targets (e.g. smooth coatings such as paint and desert varnish), particularly when measured at a high emission angle. In most studies that focus on gas phase targets or specific manmade targets, the solid phase background signatures are called "clutter" and are thrown out.
Here we discuss our field spectrometer images measured of test targets that were selected to include a range of particle sizes, diffuse, non-diffuse, high, and low reflectance materials. This study was designed to identify and improve understanding of the issues that complicate stand-off identification in the field, with a focus on developing identification capabilities to proceed without benefit of ground truth. This information allows both improved measurement protocols and identification quality.
The Aerospace Corporation has a mature program for field hyperspectral measurements using van-mounted thermal-infrared spectrometers that raster-scan images. Aerospace is a non-profit Federally Funded Research and Development Center (FFRDC), managed by the Department of Defense. The precisely controlled viewing geometery, imaging capabilities, and sensitivity of the spectrometers used are critical to identifying and studying issues that can confound interpretations or cause a misidentification. We have released a portion of this data set publicly, and encourage researchers interested in the data set to contact us. More information is at www.lpi.usra.edu/science/kirkland.
Although the throughput and multiplex advantages of Fourier transform spectrometry were established in the early 1950's (by Jacquinot and Fellgett , respectively) confusion and debate arise when these advantages are cited in reference to imaging spectrometry. In non-imaging spectrometry the terms throughput and spectral bandwidth clearly refer to the throughput of the entire field-of-view (FOV), and the spectral bandwidth of the entire FOV, but in imaging spectrometry these terms may refer to either the entire FOV or to a single element in the FOV. The continued development of new and fundamentally different types of imaging spectrometers also adds to the complexity of predictions of signal and comparisons of signal collection abilities. Imaging spectrometers used for remote sensing may be divided into classes according to how they relate the object space coordinates of cross-track position, along-track position, and wavelength (or wavenumber) to the image space coordinates of column number, row number, and exposure number for the detector array. This transformation must be taken into account when predicting the signal or comparing the signal collection abilities of different classes of imaging spectrometer. The invariance of radiance in an imaging system allows the calculation of signal to be performed at any space in the system, from the object space to the final image space. Our calculations of signal - performed at several different spaces in several different classes of imaging spectrometer - show an interesting result: regardless of the plane in which the calculation is performed, interferometric (Fourier transform) spectrometers have a dramatic advantage in signal, but the term in the signal equation from which the advantage results depends upon the space in which the calculation is performed. In image space, the advantage results from the spectral term in the signal equation, suggesting that this could be referred to as the multiplex (Fellgett) advantage. In an intermediate image plane the advantage results from a difference in a spatial term, while for the exit pupil plane it results from the angular term, both of which suggest the throughput (Jacquinot) advantage. When the calculation is performed in object coordinates the advantage results from differences in the temporal term.
The Mars exploration strategy calls first for the detection from orbit of minerals indicative of environments conducive to the support of life or the preservation of biomarkers. That information would then be used for astrobiology landing site selection. The near-term search will be conducted by the 1996 Global Surveyor Thermal Emission Spectrometer (TES) and the 2001 Mars Odyssey 9-band radiometer Thermal Emission Imaging System (THEMIS). This places the productivity of TES and THEMIS in the critical path of the Mars astrobiology strategy. Most predictions of mineral detection limits for TES and THEMIS are based on laboratory spectra of fresh mineral surfaces. However, standard laboratory measurements of fresh mineral surfaces generally do not reproduce all the spectral effects of weathering and surface roughness that are very apparent in field spectra, and these differences can critically affect interpretations of TES and THEMIS data. Here we examine causes of variations in spectral contrast, and differences in spectral signatures recorded in the field and in typical laboratory measurements, and show what the results indicate for the search for minerals and landing sites using TES and THEMIS. We conclude that for TES and THEMIS to attain their predicted mineral detection limits, minerals must be present under specific conditions: well-crystalline, smooth-surfaced at several scales, and low atmospheric downwelling radiance contribution. As a result, TES and THEMIS should not necessarily be used to exclude landing sites that are of interest for other reasons (e.g. geomorphology), but that exhibit no clear detections of minerals of interest to astrobiologists.
Static Fourier transform spectrometers have the ability to combine the principle advantages of the two traditional techniques used for imaging spectrometry: the throughput advantage offered by Fourier transform spectrometers, and the advantage of no moving parts offered by dispersive spectrometers. The imaging versions of these spectrometers obtain both spectral information, and spatial information in one dimension, in a single exposure. The second spatial dimension may be obtained by sweeping a narrow field mask across the object while acquiring successive exposures. When employed as a pushbroom sensor from an aircraft or spacecraft, no moving parts are required, since the platform itself provides this motion. But the use of this narrow field mask to obtain the second spatial dimension prevents the throughput advantage from being realized. We present a technique that allows the use of a field stop that is wide in the along-track direction, while preserving the spatial resolution, and thus enables such an instrument to actually exploit the throughput advantage when used as a pushbroom sensor. The basis of this advance is a deconvolution technique we have developed to recover the spatial resolution in data acquired with a field stop that is wide in the along-track direction. The effectiveness is demonstrated by application of this deconvolution technique to simulated data.