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Geologic and mineral and water resources investigations in western Colorado using ERTS-1 data

The author has identified the following significant results. Geologic interpretation of ERTS-1 imagery is dependent on recognition of the distribution, continuity, trend, and geometry of key surface features. In the examination of ERTS-1 imagery, lithology must be interpreted largely from the geomorphic expression of the terrain. ERTS-1 imagery is extremely useful in detecting local structures. Most mapped structures are topographically-expressed. Consequently, ERTS-1 imagery acquired during mid-winter, when the solar illumination angle is low, provides the largest amount of structural information. Stereoscopic analyses of ERTS-1 images significantly aid geologic interpretation. Positive transparencies of ERTS-1 images (1:1,000,000) commonly contain more geologic information than can be adequately annotated during geologic interpretation.

Knepper, D. H., Jr.↗

Coastal wetlands analysis from ERTS MSS digital data and field spectral measurements

Classification, delineation and evaluation of coastal wetlands can be made on the basis of major vegetative associations. To produce wetland maps, two vegetation-analysis look-up tables were developed for use in the ERTS ANALYSIS System. These look-up tables are based on Earth Resources Technology Satellite (ERTS) digital values in Multispectral Scanner (MSS) bands 4, 5, and 7 and were developed using seasonal spectral reflectance measurements from field observations. Computer-generated maps at an approximate scale of 1:20,000 were produced for the primary test site, Chincoteague Marsh, Virginia. There is a high degree of accuracy in the identification of wetland features and plant associations. The classification was also tested on other Atlantic coast salt marshes and a brackish marsh in the Chesapeake Bay.

Carter, V.↗

ERTS applications in state land use planning

The progress made and limitations encountered in using ERTS-1 data for resource management in Ohio is surveyed. Photo-opto-electronic techniques were used with special facility equipment and resolution to 10-30 meters was required to determine strip mine features. Lake Erie's sediment patterns were detected along with flooding conditions, large scale vegetative damage caused by toxic air pollutants was identified, Ohio land use categories were tabulated and thematic map containing forested areas was derived. The experimental findings regarding utility/relevance assessment were ranked in 4 classes for all the applications involved. Preliminary recommendations for operational satellite earth resources survey data requirements are presented and data analysis and product dissemination are proposed to be centralized in conjunction with thermal IR data and an increased resolution.

Pincura, P. G.↗

An evaluation of Skylab (EREP) remote sensing techniques applied to investigations of crustal structure

The author has identified the following significant results. Film positives (70mm) from all six S190A multispectral photographic camera stations for any one scene can be registered and analyzed in a color additive viewer. Using a multispectral viewer, S190A and B films can be projected directly onto published geologic and topographic maps at scales as large as 1:62,500 and 1:24,000 without significant loss of detail. S190A films and prints permit the detection of faults, fractures, and other linear features not visible in any other space imagery. S192 MSS imagery can be useful for rock-type discrimination studies and delineation of linear patterns and arcuate anomalies. Anomalous color reflectances and arcuate color patterns revealed mineralized zones, copper deposits, vegetation, and volcanic rocks in various locations such as Panamint Range (CA), Greenwater (Death Valley), Lava Mountains (CA), northwestern Arizona, and Coso Hot Springs (CA).

Bechtold, I. C.↗

IAU nomenclature for albedo features on the planet Mercury

The International Astronomical Union has endorsed a nomenclature for the albedo features on Mercury. Designations are based upon the mythological names related to the god Hermes; they are expressed in Latin form. The dark-hued albedo features are associated with the generic term Solitudo. The light-hued areas are designated by a single name without generic term. The 32 names adopted are allocated on the Mercury map.

Dollfus, A.↗

SEASAT views oceans and sea ice with synthetic aperture radar

Fifty-one SEASAT synthetic aperture radar (SAR) images of the oceans and sea ice are presented. Surface and internal waves, the Gulf Stream system and its rings and eddies, the eastern North Pacific, coastal phenomena, bathymetric features, atmospheric phenomena, and ship wakes are represented. Images of arctic pack and shore-fast ice are presented. The characteristics of the SEASAT SAR system and its image are described. Maps showing the area covered, and tables of key orbital information, and listing digitally processed images are provided.

Fu, L. L.↗

Infrared airborne spectroradiometer survey results in the western Nevada area

The Mark II airborne spectroradiometer system was flown over several geologic test sites in western Nevada. The infrared mineral absorption bands were observed and recorded for the first time using an airborne system with high spectral resolution in the 2.0 to 2.5 micron region. The data show that the hydrothermal alteration zone minerals, carbonates, and other minerals are clearly visible in the airborne survey mode. The finer spectral features that distinguish the various minerals with infrared bands are also clearly visible in the airborne survey data. Using specialized computer pattern recognition methods, it is possible to identify mineralogy and map alteration zones and lithologies by airborne spectroradiometer survey techniques.

Collins, W.↗

Perception for rugged terrain

A three-dimensional perception system for building a geometrical description of rugged terrain environments from range image data is presented with reference to the exploration of the rugged terrain of Mars. An intermediate representation consisting of an elevation map that includes an explicit representation of uncertainty and labeling of the occluded regions is proposed. The locus method used to convert range image to an elevation map is introduced, along with an uncertainty model based on this algorithm. Both the elevation map and the locus method are the basis of a terrain matching algorithm which does not assume any correspondences between range images. The two-stage algorithm consists of a feature-based matching algorithm to compute an initial transform and an iconic terrain matching algorithm to merge multiple range images into a uniform representation. Terrain modeling results on real range images of rugged terrain are presented. The algorithms considered are a fundamental part of the perception system for the Ambler, a legged locomotor.

Kweon, In SO↗

The nearby 2-solar mass Bok globule LBN 11 - Sub-sonic molecular clumps in a magnetic environment

A multiwavelength study of the nearby small Bok globule LBN 11 is performed in order to investigate the relationship between embedded magnetic fields, cloud structure, and star formation. Optical polarimetry of background stars is used to characterize and trace the embedded magnetic field direction. High-dispersion CO isotopic mapping is employed to determine the radial density distribution of the gas, measure cloud rotation, and identify individual gas clumps. CS and SO mapping revealed dense cores within the (C-13)O clumps. Analysis of coadded IRAS images reveal the cloud to be free of current or recent star formation: there are no IR point sources of sufficient flux or proper colors to signify young stars associated with the cloud. The molecular line maps show the cloud to be extremely clumpy. Clumps are found to range in size from 0.2 pc for the largest CO clump to about 0.04 pc for the smallest CS feature. It is concluded that, at least in the envelope of the cloud, the magnetic field and the CO clumps are coupled.

Clemens, Dan P.↗

A 70th Degree Lunar Gravity Model (GLGM-2) from Clementine and other tracking data

A spherical harmonic model of the lunar gravity field complete to degree and order 70 has been developed from S band Doppler tracking data from the Clementine mission, as well as historical tracking data from Lunar Orbiters 1-5 and the Apollo 15 and 16 subsatellites. The model combines 361,000 Doppler observations from Clementine with 347,000 historical observations. The historical data consist of mostly 60-s Doppler with a noise of 0.25 to several mm/s. The Clementine data consist of mostly 10-s Doppler data, with a data noise of 0.25 mm/s for the observations from the Deep Space Network, and 2.5 mm/s for the data from a naval tracking station at Pomonkey, Maryland. Observations provided Clementine, provide the strongest satellite constraint on the Moon's low-degree field. In contrast the historical data, collected by spacecraft that had lower periapsis altitudes, provide distributed regions of high-resolution coverage within +/- 29 deg of the nearside lunar equator. To obtain the solution for a high-degree field in the absence of a uniform distribution of observations, we applied an a priori power law constraint of the form 15 x 10(exp -5)/sq l which had the effect of limiting the gravitational power and noise at short wavelengths. Coefficients through degree and order 18 are not significantly affected by the constraint, and so the model permits geophysical analysis of effects of the major basins at degrees 10-12. The GLGM-2 model confirms major features of the lunar gravity field shown in previous gravitational field models but also reveals significantly more detail, particularly at intermediate wavelengths (10(exp 3) km). Free-air gravity anomaly maps derived from the new model show the nearside and farside highlands to be gravitationally smooth, reflecting a state of isostatic compensation. Mascon basins (including Imbrium, Serenitatis, Crisium, Smythii, and Humorum) are denoted by gravity highs first recognized from Lunar Orbiter tracking. All of the major mascons are bounded by annuli of negative anomalies representing significant subsurface mass deficiencies. Mare Orientale appears as a minor mascon surrounded by a horseshoe-shaped gravity low centered on the Inner and Outer Rook rings that is evidence of significant subsurface structural heterogeneity. Although direct tracking is not available over a significant part of the lunar farside, GLGM-2 resolves negative anomalies that correlate with many farside basins, including South Pole-Aitken, Hertzsprung, Korolev, Moscoviense, Tsiolkovsky, and Freundlich-Sharonov.

Lemonie, Frank G. R.↗

Phase Sensitive X-Ray Diffraction Imaging Study of Protein Crystals

The study of defects and growth of protein crystals is of importance in providing a fundamental understanding of this important category of systems and the rationale for crystallization of better ordered crystals for structural determination and drug design. Yet, as a result of the extremely weak scattering power of x-rays in protein and other biological macromolecular crystals, the extinction lengths for those crystals are extremely large and, roughly speaking, of the order of millimeters on average compared to the scale of micrometers for most small molecular crystals. This has significant implication for x-ray diffraction and imaging study of protein crystals, and presents an interesting challenge to currently available x-ray analytical techniques. We proposed that coherence-based phase sensitive x-ray diffraction imaging could provide a way to augment defect contrast in x-ray diffraction images of weakly diffracting biological macromolecular crystals. I shall examine the principles and ideas behind this approach and compare it to other available x-ray topography and diffraction methods. I shall then present some recent experimental results in two model protein systems-cubic apofemtin and tetragonal lysozyme crystals to demonstrate the capability of the coherence-based imaging method in mapping point defects, dislocations, and the degree of perfection of biological macromolecular crystals with extreme sensitivity. While further work is under way, it is intended to show that the observed new features have yielded important information on protein crystal perfection and nucleation and growth mechanism otherwise unobtainable.

Hu, Z. W.↗

WISE J233237.05-505643.5: A Double-Peaked Broad-Lined AGN with Spiral-Shaped Radio Morphology

We present radio continuum mapping, optical imaging and spectroscopy of the newly discovered double-peaked broad-lined AGN WISE J233237.05-505643.5 at redshift z = 0.3447. This source exhibits an FR-I and FR-II hybrid-morphology, characterized by bright core, jet, and Doppler-boosted lobe structures in ATCA continuum maps at 1.5, 5.6, and 9 GHz. Unlike most FR-II objects, W2332-5056 is hosted by a disk-like galaxy. The core has a projected 5" linear radio feature that is perpendicular to the curved primary jet, hinting at unusual and complex activity within the inner 25 kpc. The multi-epoch optical-near-IR photometric measurements indicate significant variability over a 3-20 year baseline from the AGN component. Gemini-South optical data shows an unusual double-peaked emission-line features: the centroids of the broad-lined components of H-alpha and H-beta are blueshifted with respect to the narrow lines and host galaxy by approximately 3800 km/s. We examine possible cases which involve single or double supermassive black holes in the system, and discuss required future investigations to disentangle the mystery nature of this system.

galaxies: individual↗

Interactive Visualization of High-Dimensional Petascale Ocean Data

We describe an application for interactive visualization of 5 petabytes of time-varying multivariate data from a high-resolution global ocean circulation model. The input data are 10311 hourly (ocean time) time steps of various 2D and 3D fields from a 22-billion point 1/48- degree “lat-lon cap” configuration of the MIT General Circulation Model (MITgcm). We map the global horizontal model domain onto our 128-screen (8x16) tiled display wall to produce a canonical tiling with approximately one MITgcm grid point per display pixel, and using this tiling we encode the entire time series for multiple native and computed scalar quantities at a collection of ocean depths. We reduce disk bandwidth requirements by converting the model’s floating point data to 16-bit fixed point values, and compressing those values with a lossless video encoder, which together allow synchronized playback at 24 time steps per second across all 128 displays. The application allows dynamic assignment of any two encoded tiles to any display, and has multiple interfaces for quickly specifying various orderly arrangements of tiles. All subsequent rendering is done on the fly, with run time control of colormaps, transfer functions, histogram equalization, and labeling. The two data streams on each screen can be rendered independently and combined in various ways, including blending, differencing, horizontal/ vertical wipes, and checkerboarding. The two data streams on any screen can optionally be displayed as a scatterplot in their joint attribute space. All scatterplots and map-view plots from the same x/y location and depth are linked so they all show the current brushable selection. Ocean scientists have used the system, and have found previously unidentified features in the data.

Interactive↗

Microbial Pigments and Their Degradation Products as Biosignatures

Carotenoids are a class of vibrant biological pigments that have a characteristic chemical structure centered around a polyene core (Lu et al. 2018). Carotenoids and their derivatives are candidate biosignatures because they can persist in the terrestrial geologic record for up to 1.73 billion years (Vinnichenko et al. 2020), have specific structures that are likely the result of complex pathways, mediate the survival of many microorganisms in Mars and Ocean Worlds analog environments, and are detectable with multiple techniques, including Raman spectroscopy. In this project, we aim to investigate the detectability of carotenoid pigments with different spectroscopic methods to inform future instrument selection. We compare the spectra of five unaltered carotenoids, two model compounds, and carotenoid-forming archaeon with visible and deep UV Raman spectroscopy and UVVis absorption spectrophotometry. We then use one model pigment, beta-carotene, to evaluate the likelihood that unique spectral properties of carotenoids, or their refractory byproducts, would be preserved and detectable on a remote planetary surface by exposing it to simulated conditions for Mars. Sample Acquisition. Pigments betacarotene, lutein, zeaxanthin, astaxanthin, and lycopene were purchased from Sigma Aldrich. Halobacterium salinarum NRC-1 was acquired from Carlina Biological and grown in Halobacterium media. Mineral salts including sodium sulfate, sodium carbonate, and halite were used to form matrices in which the beta-carotene was embedded before exposure. Pigment-mineral mixes were at a 1:10 ratio in water. Analytical Techniques. Deep UV Raman data were collected on a custom laboratory mapping spectrometer called MOBIUS (Mineral and Organic Based Investigations using Ultraviolet Spectroscopy), which is an analog to the SHERLOC instrument on the Mars 2020 Perseverance rover (Bhartia et al. 2021). It features a 248.56 nm NeCu pulsed laser, liquid nitrogen-cooled detector, and tunable optical setup. Visible Raman data were collected using a Horiba Jobin Yvon LabRam HR spectrometer with a frequencydoubled Nd:YAG laser (532 nm) and a HeNe laser (633 nm). A VWR 6300 PC UV/Visible Spectrophotometer was used to collect absorption data for carotenoid solutions, model compounds, and solvents in UVpermissible capped cuvettes. Data were collected from 190-1100 nm at 1 nm increments. All spectral data were analyzed using Igor Pro 9 (Wavemetrics). Irradiation. We used a vacuum chamber equipped with a cryostat and a flood electron gun to simulate Martian surface temperatures, low pressures, and ionizing radiation (10keV, 10μA for 6h at 200K for our initial tests). The samples were prepared by drying the pigment-mineral mix onto polished metal tabs, then mounted on the cryostat for processing. Samples were then analyzed directly on the tabs after exposure. Results: In comparing the visible and deep UV Raman spectra of unaltered pigments, we found that they differed drastically. Carotenoids are often studied with visible Raman and typically have peaks at 1525 cm-1 and 1157 cm-1, due to the stretching of the C=C and C-C bonds in the polyene structure. However, in deep UV, the strongest feature is at ~1630 cm-1 and is broad, possibly indicating that multiple peaks are forming this feature. This stark difference is likely due to different preresonant enhancement effects. The UV-Vis results show that there is an absorption band in the deep UV <300 nm, which supports the hypothesis that the 248.6 nm excitation is interrogating another aspect of carotenoids than visible Raman. Our preliminary exposure tests indicated that pigments – even without minerals present - were largely unaltered in the applied conditions, with only a slight broadening in the primary polyene peaks apparent in the visible Raman data. Figure 1. A) Visible vs. deep UV Raman spectra of unaltered beta carotene. B) Schematic of exposure. Conclusions: Our results to date indicate that deep UV and visible Raman spectroscopy, both techniques with planetary mission heritage from Mars 2020 (Wiens et al. 2021, Bhartia et al. 2021), may be used in a complementary manner to observe carotenoids. In addition, we find that beta-carotene is largely resistant to our current exposure conditions, though there may be some amount of amorphization of the material which could cause the broadening of the peaks at 1525 and 1157 cm-1. As a next step, we aim to increase the dosage and duration of exposure to observe degradation of the parent pigment, possibly add UV as a factor via an Ar mini-arc UV lamp and use GC-MS to characterize possible degradation products.

pigments↗

Modeling the Salar de Uyuni, Bolivia as an Equipotential Surface of Earth's Gravity Field

The salar de Uyuni is a massive dry salt lake that lies at the lowest point of an internal/drainage basin in the Bolivian Altiplano. Its topography is remarkable for its extraordinary flatness over almost a full degree of latitude and longitude. We surveyed a 54 x 45 km region of the salar with kinematic GPS in September, 2002 and found a topographic range of only 80 cm over the entire surveyed area. Furthermore, the survey revealed distinct surface features with several dominant wavelengths and orientations. Some of these appear to be aligned with orographic features that intersect the salar, leading us to conjecture that they are the surface expression of high-density mountains that have been buried by low-density basin sediments. Over the oceans, a similar correspondence between basin bathymetry and surface topography is exploited to map the seafloor using sea-surface satellite altimetry measurements, with the sea surface following geoid undulations due to the underwater mass distribution. On the salar, annual flooding creates a shallow lake whose surface also lies on a equipotential surface shaped by the distribution of underlying mass. The link to the actual salar surface is via the dissolution and redeposition of salt by the lake waters, which appears to push the system to an equilibrium of constant water depth and the coincidence of the shapes of the lake surface and bottom. To test our hypothesis about the origin of the surface features on the salar, we compare our GPS survey elevations with the equipotential surface generated from local gravity measurements in conjunction with gravity and potential values from the EGM96 global geopotential model. 50% of the variance of the GPS elevations can be explained by equipotential surface undulations from the EGM96 model alone, and an additional 40% is explained by the shorter-wavelength equipotential surface derived from local gravity. We examine the unexplained 10% of elevation variance from the standpoint of errors in the equipotential surface calculation and possible unmodelled surface processes.

Borsa, Adrian↗

Advances in Hyperspectral Image Classification Methods for Vegetation and Agricultural Cropland Studies

Hyperspectral data are becoming more widely available via sensors on airborne and unmanned aerial vehicle (UAV) platforms, as well as proximal platforms. While space-based hyperspectral data continue to be limited in availability, multiple spaceborne Earth-observing missions on traditional platforms are scheduled for launch, and companies are experimenting with small satellites for constellations to observe the Earth, as well as for planetary missions. Land cover mapping via classification is one of the most important applications of hyperspectral remote sensing and will increase in significance as time series of imagery are more readily available. However, while the narrow bands of hyperspectral data provide new opportunities for chemistry-based modeling and mapping, challenges remain. Hyperspectral data are high dimensional, and many bands are highly correlated or irrelevant for a given classification problem. For supervised classification methods, the quantity of training data is typically limited relative to the dimension of the input space. The resulting Hughes phenomenon, often referred to as the curse of dimensionality, increases potential for unstable parameter estimates, overfitting, and poor generalization of classifiers. This is particularly problematic for parametric approaches such as Gaussian maximum likelihood–based classifiers that have been the backbone of pixel-based multispectral classification methods. This issue has motivated investigation of alternatives, including regularization of the class covariance matrices, ensembles of weak classifiers, development of feature selection and extraction methods, adoption of nonparametric classifiers, and exploration of methods to exploit unlabeled samples via semi-supervised and active learning. Data sets are also quite large, motivating computationally efficient algorithms and implementations. This chapter provides an overview of the recent advances in classification methods for mapping vegetation using hyperspectral data. Three data sets that are used in the hyperspectral classification literature (e.g., Botswana Hyperion satellite data and AVIRIS airborne data over both Kennedy Space Center and Indian Pines) are described in Section 3.2 and used to illustrate methods described in the chapter. An additional high-resolution hyperspectral data set acquired by a SpecTIR sensor on an airborne platform over the Indian Pines area is included to exemplify the use of new deep learning approaches, and a multiplatform example of airborne hyperspectral data is provided to demonstrate transfer learning in hyperspectral image classification. Classical approaches for supervised and unsupervised feature selection and extraction are reviewed in Section 3.3. In particular, nonlinearities exhibited in hyperspectral imagery have motivated development of nonlinear feature extraction methods in manifold learning, which are outlined in Section 3.3.1.4. Spatial context is also important in classification of both natural vegetation with complex textural patterns and large agricultural fields with significant local variability within fields. Approaches to exploit spatial features at both the pixel level (e.g., co-occurrence–based texture and extended morphological attribute profiles [EMAPs]) and integration of segmentation approaches (e.g., HSeg) are discussed in this context in Section 3.3.2. Recently, classification methods that leverage nonparametric methods originating in the machine learning community have grown in popularity. An overview of both widely used and newly emerging approaches, including support vector machines (SVMs), Gaussian mixture models, and deep learning based on convolutional neural networks is provided in Section 3.4. Strategies to exploit unlabeled samples, including active learning and metric learning, which combine feature extraction and augmentation of the pool of training samples in an active learning framework, are outlined in Section 3.5. Integration of image segmentation with classification to accommodate spatial coherence typically observed in vegetation is also explored, including as an integrated active learning system. Exploitation of multisensor strategies for augmenting the pool of training samples is investigated via a transfer learning framework in Section 3.5.1.2. Finally, we look to the future, considering opportunities soon to be provided by new paradigms, as hyperspectral sensing is becoming common at multiple scales from ground-based and airborne autonomous vehicles to manned aircraft and space-based platforms.

Pasolli, Edoardo↗

Crop, soil, and geological mapping from digitized multispectral satellite photography.

An experimental study was conducted of digitized multispectral satellite photography to seek answers to the following two questions: what are the data handling problems and requirements of converting photographic density measurements to a usable digital form, and what surface features can be distinguished using multispectral data taken at satellite altitudes. Results include the digitization of three multiband black and white photographs and a color infrared photograph, the conversion of the results of digitization to a useful digital form, and several data analysis experiments. As a whole, they encourage the use of multiband photography as a multispectral data collection instrument.

Anuta, P. E.↗