Visualization, analysis and understanding of MOC and THEMIS images
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In this paper, we will describe out methods for the prioritization of geologic data acquired by an in-situ rover. Our techniques are applicable to a wide range of data modalites, however out initial demonstration is focused on image analysis, as images consume a large volume of the downlink bandwidth for such missions.
Evaluation of interferometrically measured mirror metrology data and characterization of a telescope wavefront can be powerful tools in understanding of image characteristics of an x-ray optical system. In the development of soft x-ray telescope for the International X-Ray Observatory (IXO), we have developed new approaches to support the telescope development process. Interferometrically measuring the optical components over all relevant spatial frequencies can be used to evaluate and predict the performance of an x-ray telescope. Typically, the mirrors are measured using a mount that minimizes the mount and gravity induced errors. In the assembly and mounting process the shape of the mirror segments can dramatically change. We have developed wavefront sensing techniques suitable for the x-ray optical components to aid us in the characterization and evaluation of these changes. Hartmann sensing of a telescope and its components is a simple method that can be used to evaluate low order mirror surface errors and alignment errors. Phase retrieval techniques can also be used to assess and estimate the low order axial errors of the primary and secondary mirror segments. In this paper we describe the mathematical foundation of our Hartmann and phase retrieval sensing techniques. We show how these techniques can be used in the evaluation and performance prediction process of x-ray telescopes.
Mangrove forests are found in intertidal zones of tropical regions around the world and provide important ecological and economic benefits – they are considered carbon sequesters, habitats for flora and fauna, and natural barriers to hurricanes and tsunamis. Wood from mangrove forests are used as fuel and building materials in surrounding coastal communities, therefore promoting local livelihoods. Despite the importance of these ecosystems, mangrove forests have historically been degraded in natural processes such as severe weather, and anthropogenic factors like conversion to agriculture and aquaculture. This study assesses change in mangrove forests in Nigeria and Mozambique from 2015 to 2018 using SAR and optical data fusion. Due to frequent cloud cover over the study area, SAR and optical data is fused to obtain gap-free imagery without clouds. Landsat-8 OLI and Sentinel-1 imagery is fused with TensorFlow, an open source platform used in developing machine learning models. The resulting images are classified to discriminate mangrove forest cover from other land cover types, and change is estimated using image differencing. Understanding the rates and magnitude of mangrove change across space and time can aid in identifying priority areas for forest regeneration, and can help construct sustainable management practices for the future.
Here, using a thick NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 ) electrode as an example, we present a macro- to nanoscale 2D and 3D imaging analysis approach coupled with 4D (space + time) computational modeling to probe its degradation mechanism in a lithium-ion battery cell. Particle cracking increases and contact loss between particles and carbon-binder domain are observed to correlate with the cell degradation. This study unravels that the reaction heterogeneity within the thick cathode caused by the unbalanced electron conduction is the main cause of the battery degradation over cycling. The increased heterogeneity in the system will entail more cathode regions where the degree of active material utilization is uneven, leading to higher probabilities of particle cracking. These findings shed light on the crucial role of the electronic and ionic transportation networks in the performance deterioration of the thick cathode. They also provide guidance for cathode architecture optimization and performance improvement.
Detailed understanding of the properties of the point-spread function (PSF) of Space Telescope Imaging Spectrograph (STIS) imaging modes is necessary to separate real effects of geometrically complex astronomical sources, such as protoplanetary disks surrounding bright stars, from instrumental effects, such as scattering and diffraction. In order to investigate STIS imaging properties we have numerically simulated broadband stellar PSFs generated by STIS in CCD clear imaging mode, including the effects of the Lyot stop and the coronagraphic wedges. The input spectrum is a stellar model atmosphere of the appropriate spectral type, convolved with the pre-flight STIS CCD response function. The PSF modeler generates broadband PSFs by co-adding weighted monochromatic PSFs across the waveband.
This software consists of a set of application programs that support ground-based image processing for in situ missions. These programs represent a collection of utility routines that perform miscellaneous functions in the context of the ground data system. Each one fulfills some specific need as determined via operational experience. The most unique aspect to these programs is that they are integrated into the large, in situ image processing system via the PIG (Planetary Image Geometry) library. They work directly with space in situ data, understanding the appropriate image meta-data fields and updating them properly. The programs themselves are completely multimission; all mission dependencies are handled by PIG. This suite of programs consists of: (1)marscahv: Generates a linearized, epi-polar aligned image given a stereo pair of images. These images are optimized for 1-D stereo correlations, (2) marscheckcm: Compares the camera model in an image label with one derived via kinematics modeling on the ground, (3) marschkovl: Checks the overlaps between a list of images in order to determine which might be stereo pairs. This is useful for non-traditional stereo images like long-baseline or those from an articulating arm camera, (4) marscoordtrans: Translates mosaic coordinates from one form into another, (5) marsdispcompare: Checks a Left Right stereo disparity image against a Right Left disparity image to ensure they are consistent with each other, (6) marsdispwarp: Takes one image of a stereo pair and warps it through a disparity map to create a synthetic opposite- eye image. For example, a right eye image could be transformed to look like it was taken from the left eye via this program, (7) marsfidfinder: Finds fiducial markers in an image by projecting their approximate location and then using correlation to locate the markers to subpixel accuracy. These fiducial markets are small targets attached to the spacecraft surface. This helps verify, or improve, the pointing of in situ cameras, (8) marsinvrange: Inverse of marsrange . given a range file, re-computes an XYZ file that closely matches the original. . marsproj: Projects an XYZ coordinate through the camera model, and reports the line/sample coordinates of the point in the image, (9) marsprojfid: Given the output of marsfidfinder, projects the XYZ locations and compares them to the found locations, creating a report showing the fiducial errors in each image. marsrad: Radiometrically corrects an image, (10) marsrelabel: Updates coordinate system or camera model labels in an image, (11) marstiexyz: Given a stereo pair, allows the user to interactively pick a point in each image and reports the XYZ value corresponding to that pair of locations. marsunmosaic: Extracts a single frame from a mosaic, which will be created such that it could have been an input to the original mosaic. Useful for creating simulated input frames using different camera models than the original mosaic used, and (12) merinverter: Uses an inverse lookup table to convert 8-bit telemetered data to its 12-bit original form. Can be used in other missions despite the name.
Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. The stratigraphic reservoir in northern Steptoe Valley was previously discovered during oil and gas exploration. Subsequent studies, such as the Nevada Play Fairway Analysis, included data which further highlighted potential resource targets in the basin. Geophysical surveys, complemented with refined geologic mapping and geochemical sampling, were deployed to further characterize the resource. The resulting 3D geologic interpretation, conceptual model refinements, and reservoir simulations suggest that a >100MWe power-capable reservoir is likely economically accessible using conventional well placement and stimulation techniques in the Paleozoic carbonates of the deep/central basin of northern Steptoe Valley. Additional geophysical characterization and exploration drilling efforts are recommended to calibrate interpretation and determine where/how to potentially develop the northern Steptoe resource. The geophysical tools, interpretations, lessons learned, and public data generated by this study establish an exploration methodology to inform decisions for characterization and development of northern Steptoe Valley and other stratigraphic geothermal reservoirs in the western U.S.
The focus of recent work in robotic vision for application in intelligent space robots such as the Extravehicular Activity (EVA) Retriever is in visual function, that is, how information about the space world is derived and then conveyed to cognition. The goal of this work in visual function is first to understand how the relevant structure of the surrounding world is evidenced by regularities among the pixels of images, then to understand how these regularities are mapped on the premises that form the primitive elements of cognition, and then to apply these understandings with the elements of visual processing (algorithms) and visual mechanism (machine organization) to intelligent space robot simulations and test beds. Since visual perception is the process of recognizing regularities in images that are known on the basis of a model of the world to be reliable related to causal structure in the environment (because perception attaches meaning to the link between a conception of the environment and the objective environment), the work involves understanding generic, generally applicable models of world structure (not merely objects) and how that structure evidences itself in images.
We have assembled all currently processed radar data from 1989 to 1998 into crude images covering the Kuiper (H6) region on Mercury. The data used were taken to support the ephemeris improvement and gravitational physics programs; however, the resolution is good enough in some cases to make north/south ambiguous images that show some features that can be identified with the Mariner 10 features. Topography profiles along the apparent equator are also available; some of these profiles show ridges and rills as well as crater depths and diameters. The combination of the optical imaging and the radar imaging can be helpful in understanding similar features in radar images of the optically unimaged hemisphere.
The goal of this project was to develop tools for studying plant processes in living tissues. We wanted a method for introducing probes for studying plant processes such that plants could remain intact and imaged iteratively. Towards this end, we successfully optimized carbon nanofibers that we showed could deliver non-permeable signaling probes/biomolecules to plant cells. These were created on a rigid backing and also successfully transferred to a flexible backing to use with curved plant structures. We also built fiber optic microscopes that permit iterative non-destructive fluorescence or light micrographs and created protocols and devices to stabilize plant organs during imaging. These tools were developed in conjunction with research aimed understanding receptor-mediated peptide trafficking and responses relevant to plant cell growth and defense tradeoff. During this project, we designed and built two fiberoptic fluorescence microscopes; (b) designed, fabricated and validated different nanospike designs for delivering probes to plants, including the feasibility of delivering DNA constructs for expression studies; (c) developed fluorescent peptide probes (active and inactive versions of a secreted receptor ligand called phytosulfokine or PSK) and performed mobility tests after application to plants using microscopy; (d) used appropriate genetic plant backgrounds to facilitate PSK trafficking and response mechanisms; (e) determined the transcriptional changes due to PSK-induced signaling related to growth/defense tradeoff; (f) performed experiments showing the growth/defense tradeoff involves repression of specific defense components in response to PSK. This project also involved the training of two PhD students and five Masters students.
To fully understand the radar signature of different surface features and covers, observations must be made in a variety of sensor parameters (that is, frequency, polarization, and incidence angle). This makes it possible to choose those sensor parameters that will provide the greatest amount of information about the surface. The Shuttle Imaging Radar (SIR) will be able to obtain surface images at two frequencies (L-band and C-band), at multiple polarizations, and at all incidence angles from near vertical to near grazing. The SIR will operate in the synthetic aperture imaging mode and provide digital images of the surfaces with a resolution of approximately 20 m. As part of the SIR flights, a number of planned large-scale experiments will be carried out in the fields of geologic mapping, vegetation classification, land cover mapping, surface moisture measurements, and ocean surface observation.
Background: Salinity is a major abiotic stress that negatively affects nearly all plant species at all stages of growth. Drought and poor-quality irrigation cause high soil salinity and salt accumulation via evaporation, reducing crop productivity. Despite its critical importance, the spatial localization of salt ions and associated biochemical changes within plants experiencing high salinity remains largely unknown. In this study, we developed a multimodal imaging pipeline to understand the impact of salinity on the pistachio rootstock UCB-1 (Pistacia atlantica x Pistacia integerrima). We directly link biochemical fingerprints in stem tissue architecture with salt ion localization to provide insights into the strategies pistachio uses to tolerate salinity. Results: We observed that Pistacia spp. exposed to high salt conditions accumulated Ca, Si, Cl, Al and Mg as hotspots within the pith, compared to the control (of which only Ca and Al co-locate). In contrast, there was a decrease in K between the control and salinity treatment. Hotspots of amide I and II were present in the cortex and pith of the salinity treated sample. Additionally, the salinity treatment resulted in an increased abundance of pectin and carbohydrates within the pith compared to the control, and the abundance of esters/carboxylic acid was greater in the salinity treatment. Conclusions: We determined that Cl and K, S and P, and biochemical components polysaccharide and pectin, esters and carboxylic acid, amide I and cellulose are the strongest drivers of salinity- treatment induced variability. In the cortex and phloem/xylem, a negative K-Ca correlation decreases in the salinity treatment. Several hotspots of elements and amide I (proteins) appear under salinity treatment, particularly in the cortex, suggesting an increase in the production of stress-related proteins (in response to high Cl) and/or structural proteins (i.e. Ca). Together, these results indicate that pistachio responds to salinity through ion compartmentalization coupled with a targeted biochemical adjustment, rather than a broadscale tissue-wide response. Overall, these novel, spatially resolved pixel-registered multimodal imaging data provide an enabling platform to understand the mechanisms of salinity tolerance in Pistacia spp and can be broadly applied to studying stress-related phenotype response in various plant tissues.
A number of instruments exist to measure the size, shape and orientation angle of precipitation particles near the surface; this study will specifically focus on three of them: the precipitation imaging package (PIP), the multi-angle snowflake camera (MASC), and the two-dimensional video distrometer (2DVD). The measurements of particular interest for developing precipitation microphysical retrievals from polarimetric radar and satellite-based microwave data are of the particle size, aspect ratio, and orientation angle. Due to differences in instrument design and processing software, however, the measurements made by PIP, MASC, and 2DVD are not in agreement on these key measurements. The aim of the present study is to understand how the differences between these three instruments impact their measurements of the size, aspect ratio, and orientation angle of winter precipitation particles. To this end, we have reprocessed the video files produced by PIP in a manner that replicates how the MASC and 2DVD instruments operate and process their respective data. Our findings suggest that the MASC processing software results in superior particle characteristic measurements in comparison to the other instruments, although a cursory comparison of measurements from the actual instruments suggests the PIP captures the largest number of particles of the three instruments, making PIP potentially better for computing distributions.
High-contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure planet radius or mass. Our future understanding of directly imaged exoplanets will therefore rely on extrapolated models of planetary atmospheres and bulk composition, which need robust calibration. We estimate the population of extrasolar planets that could serve as calibrators for these models. Critically, this population of “standard planets” must be accessible to both direct imaging and the transit method, allowing for radius measurement. We show that the search volume of a direct imaging mission eventually overcomes the transit probability falloff with semimajor axis, so that as long as cold planets are not exceedingly rare, the population of transiting planets and directly imageable planets overlaps. Using current extrapolations of Kepler occurrence rates, we estimate that ∼8 standard planets could be characterized shortward of 800 nm with an ambitious future direct imaging mission like LUVOIR-A and several dozen could be detected at the V band. We show the design space that would expand the sample size and discuss the extent to which ground- and space-based surveys could detect this small but crucial population of planets.
High-contrast direct imaging of exoplanets can provide many important observables, including measurements of the orbit, spectra that probe the lower layers of the atmosphere, and phase variations of the planet, but cannot directly measure planet radius or mass. Our future understanding of directly imaged exoplanets will therefore rely on extrapolated models of planetary atmospheres and bulk composition, which need robust calibration. We estimate the population of extrasolar planets that could serve as calibrators for these models. Critically, this population of "standard planets" must be accessible to both direct imaging and the transit method, allowing for radius measurement. We show that the search volume of a direct imaging mission eventually overcomes the transit probability falloff with semimajor axis, so that as long as cold planets are not exceedingly rare, the population of transiting planets and directly imageable planets overlaps. Using current extrapolations of Kepler occurrence rates, we estimate that ~8 standard planets could be characterized shortward of 800 nm with an ambitious future direct imaging mission like LUVOIR-A and several dozen could be detected at the V band. We show the design space that would expand the sample size and discuss the extent to which ground- and space-based surveys could detect this small but crucial population of planets.
Sandia National Laboratories partnered with a multi-disciplinary group of subject matter experts to evaluate a stratigraphic geothermal resource in Steptoe Valley, Nevada using both established and novel geophysical imaging techniques. Provided here are a compilation of newly acquired data over the area and select modeling efforts. This encompasses a 3D geological model (inclusive of full Leapfrog files, Leapfrog viewer files, and XYZ data for faults and stratigraphy) with embedded geophysical modeling, controlled-source electromagnetic (CSEM) and magnetotelluric (MT) data packages, aqueous spring geochemistry data, seismic reflection interpretations, and a gravity data package. The stratigraphic reservoir in Steptoe Valley was previously discovered during oil and gas exploration. Subsequent studies, such as the Nevada Play Fairway Analysis, added data which further highlighted potential resource targets in the basin. Geophysical surveys, complimented with refined geologic mapping and geochemical sampling, were deployed to further characterize the resource. The resulting 3D geologic interpretation, conceptual model refinements, and reservoir simulations suggest that a power-capable reservoir is economically accessible in the Paleozoic carbonates of the deep/central basin. Additional geophysical characterization and exploration drilling efforts are recommended to calibrate interpretation and determine where/how to potentially develop the Steptoe resource. The geophysical tools, interpretations, lessons learned, and publicly available data generated by this study establish an exploration methodology to inform decisions for successful development of stratigraphic reservoirs.
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