Studies of the scattering/absorption of minerals

Reflectance spectra were computed for water ice and ammonia ice mixtures as functions of weight fraction, grain size, and viewing geometry to simulate possible outer solar system satellite surfaces. Reflectance spectra of planetary surfaces are most affected by the weight fraction and grain sizes of the minerals in the surface. The reflectance can range from 1.0 to about 0.01 by changing the grain size or weight fraction, a factor of 100. Viewing geometry changes the reflectance by about 25 percent or less

Automatic continuum analysis of reflectance spectra

A continuum algorithm based on a Segmented Upper Hull method (SUH) is described. An upper hull is performed on segments of a spectrum defined by local minima and maxima. The segments making a complete spectrum are then combined. The definition of the upper hull allows the continuum to be both concave and/or convex, adapting to the shape of the spectrum. The method performs multiple passes on a spectrum by segmenting each local maximum to minimum and performing an upper hull. The algorithm naturally adapts to the widths of absorption features, so that all features are found, including the nature of doublets, triplets, etc. The algorithm is also reasonably fast on common minicomputers so that it might be applied to the large data sets from imaging spectrometers

Causes of spurious features in spectral reflectance data

Several techniques are becoming common in the analysis of imaging spectrometer data that can lead to spurious absorption features or to changes in the position, width, and shape of actual absorption features. It is a common practice to calibrate AIS or other imaging spectrometer data by averaging each pixel along the flight line. The average is used to calibrate the spectral data by dividing the spectrum at each pixel by the average. If some pixels in the data set contain an absorption, then the average will also show an absorption. Some AIS data has had problems with wavelength stability from one scan line to the next which can produce spurious features with some analysis methods. If a pixel has a spectrum with an absorption having a different position or width than the spectrum used in a ratio, then the ratio can produce a spurious absorption at a different position and width than the true absorption feature. An average spectrum ratioed to each pixel will produce band shifts, and changes in width or shape. If continuum removal is performed by substraction rather than division, band positions can also be shifted

Spectral identification of minerals using imaging spectrometry data: Evaluating the effects of signal to noise and spectral resolution using the tricorder algorithm

The rapid development of sophisticated imaging spectrometers and resulting flood of imaging spectrometry data has prompted a rapid parallel development of spectral-information extraction technology. Even though these extraction techniques have evolved along different lines (band-shape fitting, endmember unmixing, near-infrared analysis, neural-network fitting, and expert systems to name a few), all are limited by the spectrometer's signal to noise (S/N) and spectral resolution in producing useful information. This study grew from a need to quantitatively determine what effects these parameters have on our ability to differentiate between mineral absorption features using a band-shape fitting algorithm. We chose to evaluate the AVIRIS, HYDICE, MIVIS, GERIS, VIMS, NIMS, and ASTER instruments because they collect data over wide S/N and spectral-resolution ranges. The study evaluates the performance of the Tricorder algorithm, in differentiating between mineral spectra in the 0.4-2.5 micrometer spectral region. The strength of the Tricorder algorithm is in its ability to produce an easily understood comparison of band shape that can concentrate on small relevant portions of the spectra, giving it an advantage over most unmixing schemes, and in that it need not spend large amounts of time reoptimizing each time a new mineral component is added to its reference library, as is the case with neural-network schemes. We believe the flexibility of the Tricorder algorithm is unparalleled among spectral-extraction techniques and that the results from this study, although dealing with minerals, will have direct applications to spectral identification in other disciplines

Spectroscopic studies of water and water/regolith mixtures on planetary surfaces at low temperatures

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Earth and Planetary Sciences, 1980.Microfiche copy available in Archives and Science.Includes bibliographies.by Roger Nelson Clark.Ph.D

Studies of Coat Protein-Mediated Resistance to TMV I. The PM2 Assembly Defective Mutant Confers Resistance to TMV

AbstractTobacco mosaic virus mutant PM2 contains two amino acid changes in coat protein sequence relative to the sequence of the coat protein of TMV U1. This results in unstable infectivity, inability to cause normal systemic infection, and accumulation of elongated open helixes of coat protein. Using site-directed mutagenesis we demonstrated that the characteristics of PM2 are due to the change of Thr28 → Ile, while the second change, Glu95 → Asp, had no apparent effect on virion structure or infectivity. Transgenic Nicotiana tabacum cv Xanthi NN and Xanthi nn plants that accumulate coat protein that contains one or both of the amino acid changes are as resistant to TMV infection as transgenic plants that contain wildtype TMV coat protein. The implication of these results on a model for coat protein-mediated resistance that involves the interaction of transgenic coat protein with the challenge virus is discussed

Mapping the mineralogy and lithology of Canyonlands, Utah with imaging spectrometer data and the multiple spectral feature mapping algorithm

The sedimentary sections exposed in the Canyonlands and Arches National Parks region of Utah (generally referred to as 'Canyonlands') consist of sandstones, shales, limestones, and conglomerates. Reflectance spectra of weathered surfaces of rocks from these areas show two components: (1) variations in spectrally detectable mineralogy, and (2) variations in the relative ratios of the absorption bands between minerals. Both types of information can be used together to map each major lithology and the Clark spectral features mapping algorithm is applied to do the job

Comparison of three methods for materials identification and mapping with imaging spectroscopy

We are comparing three methods of mapping analysis tools for imaging spectroscopy data. The purpose of this comparison is to understand the advantages and disadvantages of each algorithm so others would be better able to choose the best algorithm or combinations of algorithms for a particular problem. The three algorithms are: (1) the spectralfeature modified least squares mapping algorithm of Clark et al (1990, 1991): programs mbandmap and tricorder; (2) the Spectral Angle Mapper Algorithm(Boardman, 1993) found in the CU CSES SIPS package; and (3) the Expert System of Kruse et al. (1993). The comparison uses a ground-calibrated 1990 AVIRIS scene of 400 by 410 pixels over Cuprite, Nevada. Along with the test data set is a spectral library of 38 minerals. Each algorithm is tested with the same AVIRIS data set and spectral library. Field work has confirmed the presence of many of these minerals in the AVIRIS scene (Swayze et al. 1992)

Mapping vegetation types with the multiple spectral feature mapping algorithm in both emission and absorption

Vegetation covers a large portion of the Earth's land surface. Remotely sensing quantitative information from vegetation has proven difficult because in a broad sense, all vegetation is similar from a chemical viewpoint, and most healthy plants are green. Plant species are generally characterized by the leaf and flower or fruit morphology, not by remote sensing spectral signatures. But to the human eye, many plants show varying shades of green, so there is direct evidence for spectral differences between plant types. Quantifying these changes in a predictable manner has not been easy. The Clark spectral features mapping algorithm was applied to mapping spectral features in vegetation species