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At least 505 records · Page 28

Application of the Hilbert-Huang Transform to the Search for Gravitational Waves

We present the application of a novel method of time-series analysis, the Hilbert-Huang Transform, to the search for gravitational waves. This algorithm is adaptive and does not impose a basis set on the data, and thus the time-frequency decomposition it provides is not limited by time-frequency uncertainty spreading. Because of its high time-frequency resolution it has important applications to both signal detection and instrumental characterization. Applications to the data analysis of the ground and space based gravitational wave detectors, LIGO and LISA, are described.

Camp, Jordan B.↗

Quantifying Surface Water Dynamics at 30 Meter Spatial Resolution in the North American High Northern Latitudes 1991-2011

The availability of a dense time series of satellite observations at moderate (30 m) spatial resolution is enabling unprecedented opportunities for understanding ecosystems around the world. A time series of data from Landsat was used to generate a series of three maps at decadal time step to show how surface water has changed from 1991 to 2011 in the high northern latitudes of North America. Previous attempts to characterize the change in surface water in this region have been limited in either spatial or temporal resolution, or both. This series of maps was generated for the NASA Arctic and Boreal Vulnerability Experiment (ABoVE), which began in fall 2015. These maps show a nominal extent of surface water by using multiple observations to make a single map for each time step. This increases the confidence that any detected changes are related to climate or ecosystem changes not simply caused by short duration weather events such as flood or drought. The methods and comparison to other contemporary maps of the region are presented here. Initial verification results indicate 96% producer accuracy and 54% user accuracy when compared to 2-m resolution World View-2 data. All water bodies that were omitted were one Landsat pixel or smaller, hence below detection limits of the instrument.

Carroll, Mark↗

Subdaily Earth rotation during the Epoch '92 campaign

Global Positioning System (GPS) data were used to estimate Earth rotation variations over an 11-day period during the Epoch '92 campaign in the summer of 1992. Earth orientation was measured simultaneously by several very long baseline interferometry (VLBI) networks. GPS and VLBI estimates of UT1 with 3-hour time resolution were then compared and analyzed. The high frequency behavior of both data sets is similar, although drifts between the two series of approximately 0.1 ms over 2-5 days are evident. The geodetic results were also compared with models for UT1 fluctuations at tidal periods and with estimates of atmospheric angular momentum made at 6-hour intervals. Most of the geodetic signal in the diurnal and semidiurnal frequency bands can be attributed to tidal processes, whereas UT1 variations over a few days are mostly atmospheric in origin.

Freedman, A. P.↗

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗

Determining True Sensor Spatial Resolution of Very High Resolution Optical Imagery

Some satellite data is delivered in images with gridded pixels. This gridded pixel size is often assumed to be the spatial resolution of the satellite sensor; however, this is not always the case. An image can be grided to any arbitrary pixel size, but the sensor resolution will remain constant. For example, an image with a pixel grid size much smaller than the sensor resolution will appear blurry along what should be sharp transitions. This discrepancy between an image’s pixel size and true sensor spatial resolution can be the source of much confusion and even misinformation among data users, which may lead them to waste time and resources on using images that do not suit their spatial resolution needs. This presentation will highlight our evaluation of the true spatial resolution of various government and commercial images in the pixel size range of 0.3 m to 60 m. Images evaluated include ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels). Our evaluation of true sensor spatial resolution, or ‘footprint size’ is based on the sensor’s line spread function (LSF). We calculate the width at half the height of the LSF to find the full width at half maximum (FWHM). The FWHM is how we report sensor spatial resolution. Different objects are examined for constructing the LSF depending on the sensor spatial resolution. Coarser resolution sensors in this evaluation such as Sentinel-2 and Landsat 8/9 are examined at bridges over a dark water background. The bright bridge acts as a line impulse, giving a sensor’s line spread function (LSF) in one direction. Additionally, we simulate the impacts of bridge width on the apparent LSF to obtain a true LSF without the effects of bridge width for these sensors. Finer resolution sensors will image the irregularities in bridges such as trusses, sidewalks, and in some cases painted lines, interfering with the LSF construction. Instead, these sensors are evaluated at large (60 m – 140 m) black and white checkerboards known as Cal/Val sites. At these locations, the image’s transition from black to white is extracted as an edge spread function (ESF). We calculate the derivative of this ESF to obtain the sensor’s LSF. From there, we find the FWHM as we do for the coarser resolution images. With the FWHM and pixel size, we determine how over- or under-sampled the images are. When the ratio of a sensor’s spatial resolution and the gridded image’s pixel size is less than 1, the image is considered under-sampled. In this case, each pixel’s information is unique but only a portion of that pixel’s ground area has been measured. On the other side, if the ratio is greater than 1, the image is considered over-sampled. That is, each pixel’s information is sourced from within the ground extent of the pixel and some extent outside additionally. We will show the true spatial resolution and the extent of over-/under-sampling in the imagery from ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels).

Alana Semple↗

Auto covariance computer

A laser velocimeter covariance processor which calculates the auto covariance and cross covariance functions for a turbulent flow field based on Poisson sampled measurements in time from a laser velocimeter is described. The device will process a block of data that is up to 4096 data points in length and return a 512 point covariance function with 48-bit resolution along with a 512 point histogram of the interarrival times which is used to normalize the covariance function. The device is designed to interface and be controlled by a minicomputer from which the data is received and the results returned. A typical 4096 point computation takes approximately 1.5 seconds to receive the data, compute the covariance function, and return the results to the computer.

Hepner, T. E.↗

The Cooling Loop A Anomaly of 2013: A Case Study in Human-Systems Resilience

Throughout the history of human spaceflight, NASA has employed an operational paradigm of 24/7 dependence on experts in Mission Control Center (MCC). In addition to nominal flight control and mission operations, these 85+ experts per shift manage anomaly detection, diagnosis, and response, and support the crew in real-time in performing maintenance and repair, procedure execution, and other complex mission operations. Future long-duration exploration missions (LDEMs) beyond low-Earth orbit (LEO) will not operate successfully using this same Human-Systems Integration Architecture (HSIA) where crew rely on ground controllers, have ready access to resupply, and have a fallback plan of evacuation. As distance from Earth increases and the communication delay grows, crews will need to respond independently and adequately to time-critical vehicle malfunctions. It will not always be sufficient or even possible to ‘safe the system’ and then wait upon ground intervention. A new and radically different HSIA is needed to accommodate the paradigm shift of deep-space travel. Historical International Space Station (ISS) data show that for a 30-day mission, the likelihood of a high-consequence vehicle anomaly of uncertain origin that requires rapid response is greater than 10%. The likelihood of such an event is 50% by the fourth month of the mission, and it grows exponentially with time. Our team has conducted in-depth investigations into these events and their corresponding anomaly resolution activities. Using MCC and Mission Evaluation Room (MER) anomaly resolution artifacts (including meeting summaries, caution and warning data, and ISS daily summaries), we created timelines detailing ground actions and in-orbit events for two significant anomalies. We then mapped these timelines onto Mars transit conditions, introducing a ground-crew communications time delay and shifting immediate response, time-critical task execution, and vehicle commanding to the crew. In detailing successful anomaly resolution in transit to Mars, the timelines highlight where effective resolution requires drastically evolved onboard capabilities. Though this research has yielded a rich data set based on ground response in past missions, there is still insufficient knowledge to assess the potential impact of inflight anomalies on a small autonomous crew on future LDEMs beyond LEO. To begin building an evidence base that will inform future HSIA standards and requirements, we are developing an approach to systematically capture crew anomaly response and procedure execution during early Artemis missions. Being the first human spaceflight beyond LEO since Apollo, early Artemis missions provide a rare and unique opportunity to serve as a testbed for Mars missions. Our work aims to capitalize on planned data collection to derive crew operational responses to anomalous events in real-time. Our team is also researching the level of simulation fidelity required for empirically validating proposed HSIA standards and evaluating HSIA implementations for LDEMs beyond LEO. This work will produce a trade space study of HSIA simulation objectives and fidelity requirements. Ultimately, these research efforts will assist in developing the standards and technologies needed to build a next-generation HSIA for LDEMs beyond LEO.

human-systems integration architecture↗

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗

Lateral and Vertical Heterogeneity of Thorium in the Procellarum KREEP Terrane: As Reflected in the Ejecta Deposits of Post-Imbrium Craters

The Procellarum KREEP Terrane displays the highest concentrations of Th on the Moon. However, locations of elevated Th in this region appear to be random. As observed in the 5 deg per pixel equal-area Th data, and made more evident in the preliminary 2 deg data, Th is enhanced around the craters Aristillus, Aristarchus, Kepler, Mairan, the Apennine Bench formation, and the Fra Mauro region, while noticeably and unexpectedly lower in other locations (e.g., Archimedes, Copernicus, Eratosthenes, and Plato). We have examined the composition of the materials present in these regions with the goal of understanding the patchy nature to the distribution of Th and ultimately to decipher the geologic processes that have concentrated the Th. At present time, the published resolution of the Lunar Prospector Th gamma-ray data is low (5 deg per pixel), but this will soon be superceded by significantly higher-resolution data (2 deg per pixel). Even at this improved resolution, however, it is difficult to resolve the units that are the major source of Th. In an attempt to circumvent this problem, we employ the higher-resolution Clementine multispectral data for those regions mentioned above. We use the UV-VIS-derived compositional information and the spectral properties of craters, and their ejecta as drill holes through the mare-basalt surface to investigate the thickness and composition of underlying material. With this information we attempt to piece together the stratigraphy and geologic history of the Imbrium-Procellanim region. We processed the five-band multispectral data from the Clementine Mission (415, 750,900,950, and 1000nm) using ISIS software and calibration parameters developed by the USGS, Flagstaff, Arizona. Final image mosaics are in equal-area sinusoidal projection, and have a resolution of 250 m/pixel. Using the method of we produced maps of FeO and Ti02 composition. Here we examine the Th, FeO, and Ti02 composition and spectral properties of the craters discussed above and their ejecta, with the goal of describing the materials they excavate. One interpretation for the origin of the high-Th material is that subsurface KREEPy materials have been excavated by impact craters. The material excavated may be either volcanic KREEP (e,g., Apennine Bench Formation), KREEPy impact-melt breccia formed by the Imbrium impact (e.g., Fra Mauro Formation), or other KREEP-rich crustal material. Determining which type of material is responsible for the elevated Th and its extent is important to understanding the premare and possibly the prebasin stratigraphy of the Imbrium-Procellarum Region. Merging the 5 deg. Th data with the shaded relief map, we observe that the highest Th concentrations are not related to pre-Imbrium upper crustal materials. The Apennines, Alpes, and Caucasus Mountains represent the pre-Imbrian highlands material and do not express concentrations of Th, FeO, and TiO2 as high as the most Th-fich materials exposed within the Procellarum KREEP Terrane. We observe that, in general, these massifs contain 10-14 wt% FeO and 4-7 ppm Th. Determining whether the Th signal is from KREEP basalts or KREEPy impact-melt breccias cannot be done with the Clementine data because the two rock types are compositionally and mineralogically too similar (e.g., the Th-rich, mafic impact-melt breccias in the Apollo sample collection are dominated by a KREEP-basalt like component. Mapping-the distribution and sizes of craters and whether they display elevated Th concentrations or not, should reveal the depth and thickness of the KREEP-rich materials, and whether they are ubiquitous (i.e., impact-melt breccia) or more randomly distributed; this might be taken as an indicator of localized KREEP-basalt flows. Within the southeastern region of the Imbrium basin, there are two Th hot spots. The first is associated with the crater Aristillus, and the latter with the Apennine Bench Formation. Adjacent to these two hot spots are craters with a lower Th signature: Archimedes and Autolycus. We observe in the ejecta of Aristillus, a region of significantly lower FeO (10-14 wt%) relative to the surrounding mare basalt. The crater Autolycus, 50 km to the south, did not excavate similar low-FeO material. We suggest that the lower-FeO material in the ejecta of Aristillus corresponds to Th-rich material; the FeO content observed in Aristillus ejecta is comparable to that of KREEP basalt or mafic impact melt breccia (10-12 wt% FeO). We determine that this low FeO, Th-rich material is volcanic KREEP, as opposed to Imbrium impact melt, on the basis that the low-Fe material is exposed more prominently in ejecta in the northern portion of Aristillus. Our assumption is that if the layer underlying Aristillus was continuous, a more widespread and uniform low-Fe signature wouldbe observed in the ejecta deposit. Archimedes, 110 km southwest of Aristillus, impacted the northern portion of the Apennine Bench prior to the eruption of KREEP basalt. Archimedes rim material is not as enriched in Th as the Apennine Bench, and there are differences between the two in FeO concentration and in their continuum slope. Archimedes exhibits a much steeperor "redder" continuum slope than the Apennine Bench. This steepslope suggests the presence of glassy material. The glassy material is concentrated around an unnamed crater on the southern rim of Archimedes (4.5W, 28.2N) and along the northern rim of Archimedes. We suggest two possibilities, or a combination of the two, to explain the low-Th signal from Archimedes: (1) The Apennine Bench prior to KREEP basalt eruption was lower in Th (4-7 ppm, e.g., similar to the Apennine massifs) and KREEP basalts are absent in the rim of Archimedes; or (2) the glassy (possibly pyroclastic) material layering the rim of the Archimedes, dilutes any high-Th material present with low-Th material. (Additional information is contained in the original)

Gillis, J. J.↗

Historical spatiotemporal changes in fire danger potential across biomes

This study 1) identifies the seasons and biomes that exhibit significant (1980–2019) changes in fire danger potential, as quantified by the Canadian Fire Weather Index (FWI); 2) explores what types of fire behavior potentials may be contributing to changes in fire danger potential, as quantified by the United States Energy Release Component (ERC) and the Ignition Component (IC); 3) provides spatiotemporal insight on how fire danger potential and fire behavior potential are responding in relation to changes in seasonal precipitation totals and seasonal mean air temperature across biomes. Time series of these fire potentials, as well as seasonal mean temperature, and seasonal precipitation totals are generated using data from the 0.25° ECMWF spatial resolution Reanalysis 5th Generation (ERA5) and the Climatic Research Unit gridded Time Series (CRU TS). The Mann-Kendall test is then applied to identify significant spatiotemporal trends across each biome. Results indicate that the September–November season (SON) exhibits the greatest rate of increase in fire danger potential, followed by the June–August season (JJA), December, January–February season (DJF), and March–May season (MAM), and this is predominant over the Tropical and Subtropical Moist Broadleaf Forest Biome, as well as all vegetation types of the temperate biomes. Similarly, the temperate biomes experience the greatest rate of increase in fire intensity potential and ignition potential, but prevalent during the DJF and MAM seasons. Furthermore, there is a significant positive correlation between fire danger potential and seasonal mean air temperature during JJA in the Northern Hemisphere for the temperate biomes in North America and Europe, as well as the Tropical and Subtropical biomes in Africa. Our analysis provides quantitative insight as to how fire danger potential and fire behavior potential have been responding to changes in seasonal mean temperature and seasonal precipitation totals across different ecoregions around the world.

54 ENVIRONMENTAL SCIENCES↗

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗

High-Resolution Mesoscale Model Setup for the Eastern Range and Wallops Flight Facility

Mesoscale weather conditions can have an adverse effect on space launch, landing, ground processing, and weather advisories, watches, and warnings at the Eastern Range (ER) in Florida and Wallops Flight Facility (WFF) in Virginia. During summer, land-sea interactions across Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) lead to sea breeze front formation, which can spawn deep convection that can hinder operations and endanger personnel and resources. Many other weak locally-driven low-level boundaries and their interactions with the sea breeze front and each other can also initiate deep convection in the KSC/CCAFS area. These convective processes often last 60 minutes or less and pose a significant challenge to the local forecasters. Surface winds during the transition seasons (spring and fall) pose the most difficulties for the forecasters at WFF. They also encounter problems forecasting convective activity and temperature during those seasons. Therefore, accurate mesoscale model forecasts are needed to better forecast a variety of unique weather phenomena. Global and national scale models cannot properly resolve important local-scale weather features at each location due to their horizontal resolutions being much too coarse. Therefore, a properly tuned local data assimilation (DA) and forecast model at a high resolution is needed to provide improved capability. To accomplish this, a number of sensitivity tests were performed using the Weather Research and Forecasting (WRF) model in order to determine the best DA/model configuration for operational use at each of the space launch ranges to best predict winds, precipitation, and temperature. A set of Perl scripts to run the Gridpoint Statistical Interpolation (GSI)/WRF in real-time were provided by NASA's Short-term Prediction Research and Transition Center (SPoRT). The GSI can analyze many types of observational data including satellite, radar, and conventional data. The GSI/WRF scripts use a cycled GSI system similar to the operational North American Mesoscale (NAM) model. The scripts run a 12-hour pre-cycle in which data are assimilated from 12 hours prior up to the model initialization time. A number of different model configurations were tested for both the ER and WFF by varying the horizontal resolution on which the data assimilation was done. Three different grid configurations were run for the ER and two configurations were run for WFF for archive cases from 27 Aug 2013 through 10 Nov 2013. To quantify model performance, standard model output will be compared to the Meteorological Assimilation Data Ingest System (MADIS) data. The MADIS observation data will be compared to the WRF forecasts using the Model Evaluation Tools (MET) verification package. In addition, the National Centers for Environmental Prediction's Stage IV precipitation data will be used to validate the WRF precipitation forecasts. The author will summarize the relative skill of the various WRF configurations and how each configuration behaves relative to the others, as well as determine the best model configuration for each space launch range.

Watson, Leela R.↗

Empirical Study of Focus-Plus-Context and Aggregation Techniques for the Visualization of Streaming Data

Analysis of streaming data often involves both real-time monitoring of incoming data as well as contextual awareness of data history. A focus-plus-context approach can support both goals, with variable levels of visual aggregation making it possible to provide a high level of detail for incoming and recent data while providing contextual information about recent history. Visual aggregation reduces data resolution in order to show the context of data over large periods of time within a limited display space. With a controlled experiment, we evaluated the effectiveness of different types of aggregation for four types of stream-analysis tasks. Overall, the results show that a focus-plus-context design has little negative impact on the ability to successfully monitor and analyze streaming data, making it possible to show longer periods of time than other approaches. However, visual aggregation can be problematic for trend recognition tasks. This research demonstrates how the effectiveness of the visualization depends on the specifics of the analysis task.

Ragan, Eric↗

Production of long-term global water vapor and liquid water data set using ultra-fast methods to assimilate multi-satellite and radiosonde observations

During the next decade, many programs and experiments under the Global Energy and Water Cycle Experiment (GEWEX) will utilize present day and future data sets to improve our understanding of the role of moisture in climate, and its interaction with other variables such as clouds and radiation. An important element of GEWEX will be the GEWEX Water Vapor Project (GVaP), which will eventually initiate a routine, real-time assimilation of the highest quality, global water vapor data sets including information gained from future data collection systems, both ground and space based. The comprehensive global water vapor data set being produced by METSAT Inc. uses a combination of ground-based radiosonde data, and infrared and microwave satellite retrievals. This data is needed to provide the desired foundation from which future GEWEX-related research, such as GVaP, can build. The first year of this project was designed to use a combination of the best available atmospheric moisture data including: radiosonde (balloon/acft/rocket), HIRS/MSU (TOVS) retrievals, and SSM/I retrievals, to produce a one-year, global, high resolution data set of integrated column water vapor (precipitable water) with a horizontal resolution of 1 degree, and a temporal resolution of one day. The time period of this pilot product was to be det3ermined by the availability of all the input data sets. January 1988 through December 1988 were selected. In addition, a sample of vertically integrated liquid water content (LWC) was to be produced with the same temporal and spatial parameters. This sample was to be produced over ocean areas only. Three main steps are followed to produce a merged water vapor and liquid water product. Input data from Radiosondes, TOVS, and SSMI/I is quality checked in steps one and two. Processing is done in step two to generate individual total column water vapor and liquid water data sets. The third step, and final processing task, involves merging the individual output products to produce the integrated water vapor product. A final quality control is applied to the merged data sets.

Vonderhaar, T. H.↗

FRAM Isotopic Analysis of High-Resolution CZT Data [Slides]

Abstract: H3D Inc. introduced a new type of CZT detectors with resolution several times better than that of a typical CZT; The current FRAM v.6.1 can analyze uranium spectra with minimal modification of the parameter sets and get acceptable results; The exceptionally large high-energy tail of the peaks makes it difficult to achieve good uranium results and impossible to successfully analyze plutonium spectra; The FRAM code needed to be modified to better fit the high-energy tail of the peaks to analyze plutonium data and to get better uranium analysis results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Earth resources data systems design: S192 instrument measurements and characteristics

The design, development, and characteristics of the S192 instrument for use with the earth resources data systems are discussed. Subjects presented are: (1) multispectral scanner measurements, (2) measurement characteristics, (3) calibration and aligment, (4) operating modes, and (5) time tagging and references. The S192 will obtain high spatial resolution, quantitative line scan imagery data of the radiation reflected and emitted by selected test sites in up to 13 spectral bands of visible, near infrared, and thermal infrared regions of the electromagnetic spectrum.

Goldstein, A. S.↗

A Super-Resolution Algorithm for Enhancement of FLASH LIDAR Data: Flight Test Results

This paper describes the results of a 3D super-resolution algorithm applied to the range data obtained from a recent Flash Lidar helicopter flight test. The flight test was conducted by the NASA's Autonomous Landing and Hazard Avoidance Technology (ALHAT) project over a simulated lunar terrain facility at NASA Kennedy Space Center. ALHAT is developing the technology for safe autonomous landing on the surface of celestial bodies: Moon, Mars, asteroids. One of the test objectives was to verify the ability of 3D super-resolution technique to generate high resolution digital elevation models (DEMs) and to determine time resolved relative positions and orientations of the vehicle. 3D super-resolution algorithm was developed earlier and tested in computational modeling, and laboratory experiments, and in a few dynamic experiments using a moving truck. Prior to the helicopter flight test campaign, a 100mX100m hazard field was constructed having most of the relevant extraterrestrial hazard: slopes, rocks, and craters with different sizes. Data were collected during the flight and then processed by the super-resolution code. The detailed DEM of the hazard field was constructed using independent measurement to be used for comparison. ALHAT navigation system data were used to verify abilities of super-resolution method to provide accurate relative navigation information. Namely, the 6 degree of freedom state vector of the instrument as a function of time was restored from super-resolution data. The results of comparisons show that the super-resolution method can construct high quality DEMs and allows for identifying hazards like rocks and craters within the accordance of ALHAT requirements.

Bulyshev, Alexander↗

Blood flow imaging by optimal matching of computational fluid dynamics to 4D-flow data

Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit computational fluid dynamics solutions to 4D-flow data. Synthetic tests were performed in 2D, and phantom validation was performed with pulsatile flow. Reference velocity data were acquired using particle imaging velocimetry, and 4D-flow data were acquired at 1.5 T. In vivo testing was performed on intracranial arteries in a healthy volunteer at 7 T, with 2D flow as the reference. Results Synthetic tests showed low error (0.4%-0.7%). Phantom validation showed improved agreement with laser particle imaging velocimetry compared with input 4D-flow in the horizontal (mean -0.05 vs -1.11 cm/s, P < .001; SD 1.86 vs 4.26 cm/s, P < .001) and vertical directions (mean 0.05 vs -0.04 cm/s, P = .29; SD 1.36 vs 3.95 cm/s, P < .001). In vivo data show a reduction in flow rate error from 14% to 3.5%. Phantom and in vivo results from 4D-flow HIKING show promise for future applications with higher resolution, shorter scan times, and accurate quantification of physiological parameters.

4D-flow MRI↗