Spatially mapping the spectral evolution of imaging spectrometer data
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Viewgraph topics include: optical image of Taurus; dust extinction in IR has provided a new tool for probing cloud morphology; observations of the gas can contribute critical information on gas temperature, gas column density and distribution, mass, and kinematics; the Taurus molecular cloud complex; average spectra in each mask region; mas 2 data; dealing with mask 1 data; behavior of mask 1 pixels; distribution of CO column densities; conversion to H2 column density; variable CO/H2 ratio with values much less than 10(exp -4) at low N indicated by UV results; histogram of N(H2) distribution; H2 column density distribution in Taurus; cumulative distribution of mass and area; lower CO fractional abundance in mask 0 and 1 regions greatly increases mass determined in the analysis; masses determined with variable X(CO) and including diffuse regions agrees well with the found from L(CO); distribution of young stars as a function of molecular column density; star formation efficiency; star formation rate and gas depletion; and enlarged images of some of the regions with numerous young stars. Additional slides examine the origin of the Taurus molecular cloud, evolution from HI gas, kinematics as a clue to its origin, and its relationship to star formation.
Investigations are reported of digital array scanned interferometers (DASI) with silicon CCD array detectors to define the operational capabilities of a mapping (polarimetric) spectrometer for astronomical applications based on these instruments. For spectral mapping, spatially resolved spectra using a cylindrical lens to image in the interferometers's redundant coordinate are given. The signal-to-noise characteristics of the Fourier transformed data are demonstrated with regard to the effects of a rectangular sampling function, spectral multiplexing and the pixel-to-pixel variation of the CCD array. These data indicate that DASIs can offer simple, versatile (polarization) mapping spectrometers suitable for spectral mapping observations from the ultraviolet to the infrared of extended sources at variable spatial resolution, particularly where long term stable operation is essential, as for spacecraft instruments.
Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.
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Intensity mapping experiments survey the spectrum of diffuse line radiation rather than detect individual objects at high signal-to-noise ratio. Spectral maps of unresolved atomic and molecular line radiation contain three-dimensional information about the density and environments of emitting gas and efficiently probe cosmological volumes out to high redshift. Intensity mapping survey volumes also contain all other sources of radiation at the frequencies of interest. Continuum foregrounds are typically approximately 10(sup 2)-10(Sup 3) times brighter than the cosmological signal. The instrumental response to bright foregrounds will produce new spectral degrees of freedom that are not known in advance, nor necessarily spectrally smooth. The intrinsic spectra of fore-grounds may also not be well known in advance. We describe a general class of quadratic estimators to analyze data from single-dish intensity mapping experiments and determine contaminated spectral modes from the data themselves. The key attribute of foregrounds is not that they are spectrally smooth, but instead that they have fewer bright spectral degrees of freedom than the cosmological signal. Spurious correlations between the signal and foregrounds produce additional bias. Compensation for signal attenuation must estimate and correct this bias. A successful intensity mapping experiment will control instrumental systematics that spread variance into new modes, and it must observe a large enough volume that contaminant modes can be determined independently from the signal on scales of interest.
Remote sensing and its application as an alternative technique to mineral resource exploration are reviewed. Emphasis is given here to the analysis of the three basic attributes of remote sensing, i.e., spatial attributes related to regional structural mapping, spectral attributes related to rock discrimination and seasonal attributes related to geobotanic anomalies mapping, all of which are employed in mineral exploration. Special emphasis is given to new developments of the Thematic Mapper of the LANDSAT-5, principally with reference to the application of the bands 1.6 and 2.2 microns to map hydrothermally altered rocks and the band of red and blue shift to geobotanical anomalies mapping.
The diffuse interstellar medium inventory of organic material (Pendleton et al. 1994, Pendleton Allamandola 2002) was likely incorporated into the molecular cloud in which the solar nebula condensed. This provided the feedstock for the formation of the Sun, major planets, and the smaller icy bodies in the region outside Neptune's orbit (transneptunian objects, or TNOs). Saturn's satellites Phoebe, Iapetus, and Hyperion open a window to the composition of one class of TNO as revealed by the near-infrared mapping spectrometer (VIMS - Visible and Infrared Mapping Spectrometer) on the Cassini spacecraft at Saturn. Phoebe (mean diameter 213 kilometers) is a former TNO now orbiting Saturn. VIMS spectral maps of Phoebe's surface reveal a complex organic spectral signature consisting of prominent aromatic (CH) and aliphatic hydrocarbon (CH2, CH3) absorption bands (3.2-3.6 meters). Phoebe is the source of a huge debris ring encircling Saturn, and from which particles (5-20 meter size) spiral inward toward Saturn. They encounter Iapetus and Hyperion where they mix with and blanket the native H2O ice of those two bodies. Quantitative analysis of the hydrocarbon bands on Iapetus demonstrates that aromatic CH is 10 times as abundant as aliphatic CH2 plus CH3, significantly exceeding the strength of the aromatic signature in interplanetary dust particles, comet particles, and in carbonaceous meteorites (Cruikshank et al. 2013). A similar excess of aromatics over aliphatics is seen in the qualitative analysis of Hyperion and Phoebe itself (Dalle Ore et al. 2012). The Iapetus aliphatic hydrocarbons show CH2/CH3 4, which is larger than the value found in the diffuse ISM (InterStellar Matter - (2-2.5). Insofar as Phoebe is a primitive body that formed in the outer regions of the solar nebula and has preserved some of the original nebula inventory, it can be key to understanding the content and degree of processing of that nebular material. There are other Phoebe-like TNOs that are presently beyond our ability to study in the organic spectral region, but JWST (James Webb Space Telescope) will open that possibility for a number of objects. We now need to explore and understand the connection of this organic-bearing Solar System material to the solar nebula and the inventory of ISM (Interstellar Medium) materials incorporated therein.
The author has identified the following significant results. Computer-aided analysis techniques used with aircraft MSS data showed that the spatial resolution was sufficient to recognize each soil mapping unit of the test site. Some difficulties occurred where different soil series were intricately mixed, and this mixture showed as a separate spectral mapping unit, or where the difference between two soils depended on the depth of silty surface material. Analysis of LANDSAT data with computer-aided techniques showed that it was not possible to find spectrally homogeneous soil features of the seven soil series on the 40 ha test site on the digital display or on a picture print map. Cluster techniques could be used on an extended test area to group spectrally similar data points into cluster classes.
Aliphatic hydrocarbons and PAHs have been observed in the interstellar medium (e.g., Allamandola et al. 1985, Pendleton et al. 1994, Pendleton & Allamandola 2002, Tielens 2013, Kwok 2008, Chiar & Pendleton 2008) The inventory of organic material in the ISM was likely incorporated into the molecular cloud in which the solar nebula condensed, contributing to the feedstock for the formation of the Sun, major planets, and the smaller icy bodies in the region outside Neptune's orbit (transneptunian objects, or TNOs). Additional organic synthesis occurred in the solar nebula (Ciesla & Sandford 2012). Saturn's satellites Phoebe, Iapetus, and Hyperion open a window to the composition of one class of TNO as revealed by the near-infrared mapping spectrometer (VIMS) on the Cassini spacecraft at Saturn. Phoebe (mean diameter 213 km) is a former TNO now orbiting Saturn (Johnson & Lunine 2005). VIMS spectral maps of Phoebe's surface reveal a complex organic spectral signature consisting of prominent aromatic (CH) and aliphatic hydrocarbon (=CH2, -CH3) absorption bands (3.2-3.6 micrometers). Phoebe is the source of a huge debris ring encircling Saturn, and from which particles ((is) approximately 5-20 micrometers size) spiral inward toward Saturn (Verbiscer et al. 2009). They encounter Iapetus and Hyperion where they mix with and blanket the native H2O ice of those two bodies. Quantitative analysis of the hydrocarbon bands on Iapetus demonstrates that aromatic CH is approximately 10 times as abundant as aliphatic CH2+CH3, significantly exceeding the strength of the aromatic signature in interplanetary dust particles, comet particles, and in carbonaceous meteorites (Cruikshank et al. 2014). A similar excess of aromatics over aliphatics is seen in the qualitative analysis of Hyperion and Phoebe itself (Dalle Ore et al. 2012). The Iapetus aliphatic hydrocarbons show CH2/CH3 (is) approximately 4, which is larger than the value found in the diffuse ISM ((is) approximately 2-2.5). Insofar as Phoebe is a primitive body that formed in the outer regions of the solar nebula and has preserved some of the original nebula inventory, it can be key in understanding the content and degree of processing of that nebular material. A dynamical subset of TNOs define the Kuiper Belt, from which the short-period comets originate. Particles collected from comet 81P/Wild contain PAHs with an interstellar signature of deuterium. By inference, the PAHs contained in Phoebe and now dusted on the surfaces of two other Saturn satellites share that interstellar origin. There are other Phoebe-like TNOs that are presently beyond our ability to study in the organic spectral region, but JWST will open that possibility for a number of objects.
The seminar concentrated on the science applications of spectral imaging, multispectral imaging sensors, and spectral filtering. Papers are presented on spectroscopic remote sensing for geological applications, spectral mapping of Jupiter, system design of an interferometer imaging sounder and a common module imaging spectral radiometer. Other topics discussed include the performance and application of an intensified linear self-scanned array instrument, tunable optical filtering using an interferometer for selective modulation, design studies for a spectrally agile staring sensor system, and acousto-optic tunable filters for high-resolution spectral analysis.
The applicability of ERS-1 wind and wave data for wave models was studied using the WAM third generation wave model and SEASAT altimeter, scatterometer and SAR data. A series of global wave hindcasts is made for the surface stress and surface wind fields by assimilation of scatterometer data for the full 96-day SEASAT and also for two wind field analyses for shorter periods by assimilation with the higher resolution ECMWF T63 model and by subjective analysis methods. It is found that wave models respond very sensitively to inconsistencies in wind field analyses and therefore provide a valuable data validation tool. Comparisons between SEASAT SAR image spectra and theoretical SAR spectra derived from the hindcast wave spectra by Monte Carlo simulations yield good overall agreement for 32 cases representing a wide variety of wave conditions. It is concluded that SAR wave imaging is sufficiently well understood to apply SAR image spectra with confidence for wave studies if supported by realistic wave models and theoretical computations of the strongly nonlinear mapping of the wave spectrum into the SAR image spectrum. A closed nonlinear integral expression for this spectral mapping relation is derived which avoids the inherent statistical errors of Monte Carlo computations and may prove to be more efficient numerically.
The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This project addresses the technical feasibility of augmenting human vision through Sensing Super-position using a Visual Instrument Sensory Organ Replacement (VISOR). The current implementation of the VISOR device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of the human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system.
The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This paper addresses the technical feasibility of augmenting human vision through Sensing Super-position by mixing natural Human sensing. The current implementation of the device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of Lie human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system. The human brain is superior to most existing computer systems in rapidly extracting relevant information from blurred, noisy, and redundant images. From a theoretical viewpoint, this means that the available bandwidth is not exploited in an optimal way. While image-processing techniques can manipulate, condense and focus the information (e.g., Fourier Transforms), keeping the mapping as direct and simple as possible might also reduce the risk of accidentally filtering out important clues. After all, especially a perfect non-redundant sound representation is prone to loss of relevant information in the non-perfect human hearing system. Also, a complicated non-redundant image-to-sound mapping may well be far more difficult to learn and comprehend than a straightforward mapping, while the mapping system would increase in complexity and cost. This work will demonstrate some basic information processing for optimal information capture for headmounted systems.
The diffuse interstellar medium inventory of organic material (Pendleton et al. 1994, Pe 2002) was likely incorporated into the molecular cloud in which the solar nebula condensed. This provided the feedstock for the fo planets, and the smaller icy bodies in the region outside Neptune's orbit (transneptunian objects, or TNOs). Saturn's satellites Phoeb open a window to the composition of one class of TNO as revealed by the near-infrared mapping spectrometer (VIMS) on the Cass Phoebe (mean diameter 213 km) is a former TNO now orbiting Saturn. VIMS spectral maps of Phoebe's surface reveal a complex consisting of prominent aromatic (CH) and aliphatic hydrocarbon (CH2, CH3) absorption bands (3.2-3.6 μm). Phoebe is the source encircling Saturn, and from which particles (~5-20 μm size) spiral inward toward Saturn. They encounter Iapetus and Hyperion wh blanket the native H2O ice of those two bodies. Quantitative analysis of the hydrocarbon bands on Iapetus demonstrates that aroma abundant as aliphatic CH2+CH3, significantly exceeding the strength of the aromatic signature in interplanetary dust particles, com carbonaceous meteorites (Cruikshank et al. 2013). A similar excess of aromatics over aliphatics is seen in the qualitative analysis o itself (Dalle Ore et al. 2012). The Iapetus aliphatic hydrocarbons show CH2/CH3 ~4, which is larger than the value found in the di as Phoebe is a primitive body that formed in the outer regions of the solar nebula and has preserved some of the original nebula inv understanding the content and degree of processing of that nebular material. There are other Phoebe-like TNOs that are presently b in the organic spectral region, but JWST will open that possibility for a number of objects. We now need to explore and understand organic-bearing Solar System material to the solar nebula and the inventory of ISM materials incorporated therein.
The search for potential signs of life on Mars, a primary aim of the Mars 2020 mission, is greatly informed by the detection of organic matter1. The presence of organic matter also provides key information about the habitability and biological potential of the planet throughout its history. The Perseverance rover was designed for in situ science with the ability to collect a suite of promising samples for eventual return to Earth. One of its instruments, Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC), is a deep ultraviolet (DUV) Raman and fluorescence spectrometer designed to map the distribution of organic molecules and minerals on rock surfaces at a resolution of 100 μm2. With its unique spectral mapping capabilities, SHERLOC enables a novel understanding of organic-mineral relationships on Mars to better determine their formation, deposition, and preservation mechanisms. The rover’s landing site within Jezero crater combines a high potential for past habitability as the site of an ancient lake basin with a diverse set of minerals, including carbonates and clays, that may preserve organic materials and potential biosignatures. The Jezero crater floor includes three formations (fm); two of these, Máaz and Séítah, were explored as part of the mission’s first campaign. Here, we report the detection of multiple species of aromatic organic molecules using Raman and fluorescence spectroscopy across ten targets in the two formations. This is the first evidence of organic molecules in Martian materials obtained using Raman spectroscopy, and among the first using fluorescence spectroscopy, beyond Earth3. We report specific spatial patterns and classes of organic molecules in these compositionally distinct formations, potentially indicating different fates of carbon in these environments. Our findings indicate that there is a diversity of aromatic molecules prevalent on the Martian surface and these materials persist despite exposure to surface conditions. These organic molecules are largely found within minerals linked to aqueous processes, suggesting that these processes may have had a key role in organic synthesis, transport from their point of origin, or preservation.
A procedure is outlined for defining spectral classes such that the differences between classes can be quantified. It also facilitates determination of a number of classes such that the classes are spectrally discriminable. This is accomplished by partitioning the data into many classes and then combining similar spectral classes on the basis of appropriate criteria. Multispectral data were collected over a 12-mile flightline in White County, Indiana, in connection with the 1971 Corn Blight Watch Experiment. Data were collected in May by the University of Michigan airborne scanning spectrometer at an altitude of 5000 feet. Spectral maps resulting from the analysis were compared to existing soil surveys of the National Cooperative Soil Survey. The method should help determine the extent to which spectral properties of soil surfaces can be associated with morphologic and topographic differences of interest to soil surveyors engaged in operational soil mapping.
A method of converting polygon map information into a digital form which does not require manual tracing of polygon edges is discussed. The maps must be in color-coded format with a unique color for each category in the map. Color scanning using a microdensitometer is employed and a three-channel color separation digital data set is generated. The digital data are then classified by using a Gaussian maximum likelihood classifier, and the resulting digitized map is evaluated. Very good agreement is observed between the classified and original map.