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NASA NTRS2006

Multiuser Collaboration with Networked Mobile Devices

In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application-independent middleware that maintains the states, sessions, and interactions of individual users of the software applications, (4) an application programming interface to enable tight integration of applications and the middleware. The infrastructure is able to support any software applications running under the Windows or Unix platforms. The resulting technologies not only are applicable to NASA mission operations, but also useful in other situations such as design reviews, brainstorming sessions, and business meetings, as they can benefit from having the participants concurrently interact with the software applications (e.g., presentation applications and CAD design tools) to illustrate their ideas and provide inputs.

ground operations↗

NASA NTRS1981

Positive cloud-to-ground lightning flashes in severe storms

The occurrence of cloud-to-ground flashes that effectively lower positive charge to earth (+CG flash) over flat terrain has been documented in the mature stage of severe thunderstorms. Of the 31 documented +CG flashes, most had only one return stroke. Zero-to-peak rise times for the strokes averaged 7 microsec. The +CG flashes averaged 520 ms in duration, with 25 percent lasting more than 800 ms. Many of these had field changes suggestive of continuing current. Positive flashes have been observed to emanate from several regions of severe storms: high on the back of the main storm tower, through the wall cloud, and from the downshear anvil. Visually most of these positive flashes have emanated from high in the storm, and acoustic mapping of two shows thunder sources to a height of about 15 km.

Rust, W. D.↗

NASA NTRS2007

Processing Satellite Imagery To Detect Waste Tire Piles

A methodology for processing commercially available satellite spectral imagery has been developed to enable identification and mapping of waste tire piles in California. The California Integrated Waste Management Board initiated the project and provided funding for the method s development. The methodology includes the use of a combination of previously commercially available image-processing and georeferencing software used to develop a model that specifically distinguishes between tire piles and other objects. The methodology reduces the time that must be spent to initially survey a region for tire sites, thereby increasing inspectors and managers time available for remediation of the sites. Remediation is needed because millions of used tires are discarded every year, waste tire piles pose fire hazards, and mosquitoes often breed in water trapped in tires. It should be possible to adapt the methodology to regions outside California by modifying some of the algorithms implemented in the software to account for geographic differences in spectral characteristics associated with terrain and climate. The task of identifying tire piles in satellite imagery is uniquely challenging because of their low reflectance levels: Tires tend to be spectrally confused with shadows and deep water, both of which reflect little light to satellite-borne imaging systems. In this methodology, the challenge is met, in part, by use of software that implements the Tire Identification from Reflectance (TIRe) model. The development of the TIRe model included incorporation of lessons learned in previous research on the detection and mapping of tire piles by use of manual/ visual and/or computational analysis of aerial and satellite imagery. The TIRe model is a computational model for identifying tire piles and discriminating between tire piles and other objects. The input to the TIRe model is the georeferenced but otherwise raw satellite spectral images of a geographic region to be surveyed. The TIRe model identifies the darkest objects in the images and, on the basis of spatial and spectral image characteristics, discriminates against other dark objects, which can include vegetation, some bodies of water, and dark soils. The TIRe model can identify piles of as few as 100 tires. The output of the TIRe model is a binary mask showing areas containing suspected tire piles and spectrally similar features. This mask is overlaid on the original satellite imagery and examined by a trained image analyst, who strives to further discriminate against non-tire objects that the TIRe model tentatively identified as tire piles. After the analyst has made adjustments, the mask is used to create a synoptic, geographically accurate tire-pile survey map, which can be overlaid with a road map and/or any other map or set of georeferenced data, according to a customer s preferences.

Skiles, Joseph↗

DOE OSTI2019

Radiological Verification for the Remediation of LLRW at the Port Granby Project - 19210

The Port Granby Project is part of the Port Hope Area Initiative (PHAI) that Canadian Nuclear Laboratory (CNL) is using to manage long-term historic low level radioactive waste (LLRW) resulting from 60 years of uranium and radium processing operations in the urban setting of Port Hope, Ontario. Port Granby remediation scope includes constructing a new, secure long-term waste management facility (LTWMF) and supporting infrastructure and excavating and relocating LLRW and marginally contaminated soil from the Port Granby Waste Management Facility (PGWMF) which accepted waste until the 1980's to the newly constructed LTWMF. The PGWMF contains an estimated 450,000 cubic meters of LLRW deposited in unmarked and unlined trenches throughout the southern portion of the site that borders Lake Ontario. Project requirements include excavating contaminated material, verifying that the trench bottoms are below action levels using Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance, and final restoration. This paper describes challenges of meeting remediation verification requirements using traditional field and laboratory confirmation methods in areas of deep trench areas located in rugged terrain with ponded water and mud and presents a process that has expedited the traditional MARSSIM method for verification with greater productivity, and with enhanced safety and reliability as compared to the use of traditional methods alone. This enhanced process has been successfully employed for in-situ verification so that the excavated area can be backfilled and returned to a vegetative state. This enhanced process has been examined by federal regulatory staff through the course of their onsite audits and outcomes from these examinations have all been positive. The method involves a visual inspection and traditional walkover of the area to identify any areas with radiation measurements above the region's background followed by a full area survey performed using Wood's proprietary Orion ScanPlotSM system. The ScanPlotSM data is evaluated, mapped and overlaid on top of an aerial image of the surveyed area allowing remaining radiological material at surface or near surface to be quickly and easily identified for removal. Field staff then collect soil samples from evenly distributed points within the surveyed area and field screen the samples using an X-ray fluorescence (XRF) analysis for the three primary contaminates of potential concern (CoPCs) (arsenic, uranium and lead) that are indicative of the historical contamination. Samples passing XRF field screening are packaged and sent to a local laboratory for a full suite of analyses and checked against the CoPC list to assess whether the soil matches the profile for nearby native soils and passes the remediation goals. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2018

Assessing C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration's (NASA) Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude UAS operations. Currently there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. The UTM technical challenge will develop comprehensive and validated airspace operations and integration requirements to safely enable large-scale persistent access to visual line of sight and autonomous beyond visual line of sight small UAS in low-altitude airspace. Within the UTM project, a number of communications technologies to support UTM command and control (C2) are under investigation. In particular, commercial networked cellular systems are being tested and assessed for their ability to meet the reliability, scalability, cybersecurity and redundancy required. NASA Glenn Research Center is studying some of the aspects of employing such networks for UTM C2 communications. This includes the development of a test platform for sensing and characterizing the airborne C2 communications environment at various altitudes and in various terrains and topologies, measuring such aspects as received signal strength and interference. System performance aspects such as latency in the link, handover performance, packet error loss rate, drop outs, coverage gaps and other aspects impacting UTM operation will also be assessed. In this paper we explore some of the C2 approaches being proposed and demonstrated in the UTM project, the reliability, availability and other general C2 performance requirements, and approaches to evaluating and analyzing UTM C2 links based on commercial cellular networks.

air traffic control↗

NASA NTRS2018

Assessing C2 Communications

aircraft communications↗

NASA NTRS1985

Characterization of LANDSAT-4 TM and MSS Image Quality for the Interpretation of California's Agricultural Resources

The quality of LANDSAT-4 MSS and TM data was determined by analyzing TM spectral and spatial performance in terms of spectral variability of natural targets and the TM-ground instantaneous field-of-view (IFOV) variability in level and mountainous terrain; and by assessing the suitability of TM and MSS image products for characterizing renewable resourse features. The TM data should be extremelly valuable for crop type and area proportion estimation; undating agricultural land use survey maps at 1:24,000 scale and smaller, field boundary definition; and determining the size and location of individual farmsteads. Ongoing research activities are focused on making spectral and spatial analyses of both MSS and TM analytical film products. The improved spectral, spatial, and radiometric quality of the TM data, should promote a renewed emphasis and interest in direct visual interpretation of these image products, both for updating and improving land stratification in support of resource inventory and for enhancing the image analyst's contribution to computer-assisted analysis procedures.

Degloria, S. D.↗

NASA NTRS1998

Real-Time Lunar Prospector Data Visualization Using Web-Based Java

The Lunar Prospector was co-developed by NASA Ames Research Center and Lockheed Martin, and was launched on January 6th, 1998. Its mission is to search for water ice and various elements in the Moon's surface, map its magnetic and gravity fields, and detect volcanic activity. For the first time, the World Wide Web is being used to graphically display near-real-time data from a planetary exploration mission to the global public. Science data from the craft's instruments, as well as engineering data for the spacecraft subsystems, are continuously displayed in time-varying XY plots. The craft's current location is displayed relative to the whole Moon, and as an off-craft observer would see in the reference frame of the craft, with the lunar terrain scrolling underneath. These features are implemented as Java applets. Analyzed data (element and mass distribution) is presented as 3D lunar maps using VRML and Javascript. During the development phase, implementations of the Java Virtual Machine were just beginning to mature enough to adequately accommodate our target featureset; incomplete and varying implementations were the biggest bottleneck to our ideal of ubiquitous browser access. Bottlenecks notwithstanding, the reaction from the Internet community was overwhelmingly enthusiastic.

Deardorff, D. Glenn↗

NASA NTRS2007

Intelligent Entity Behavior Within Synthetic Environments

This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance characteristics (e.g. visual acuity) included in the system behavioral specification. As well, performance affecting human parameters such as experience level, fatigue and stress are coming into wider use (via AI approaches) to incorporate more uncertainty as to response type as well as performance (e.g. Where an opposing entity might go and what it might do, as well as how well it might perform).

Kruk, R. V.↗

NASA NTRS2015

Continental Spatio-Temporal Data Analysis with Linear Spectral Mixture Model Using FOSS

This work demonstrates the development and implementation of a Fully Constrained Least Squares (FCLS) unmixing model developed in C++ programming language with OpenCV package and boost C++ libraries in the NASA Earth Exchange (NEX). Visualization of the results is supported by GRASS GIS and statistical analysis is carried in R in a Linux system environment. FCLS was first tested on computer simulated data with Gaussian noise of various signal-to-noise ratio, and Landsat data of an agricultural scenario and an urban environment using a set of global end members of substrate (soils, sediments, rocks, and non-photosynthetic vegetation), vegetation that includes green photosynthetic plants and dark objects which encompasses absorptive substrate materials, clear water, deep shadows, etc. For the agricultural scenario, a spectrally diverse collection of 11 scenes of Level 1 terrain corrected, cloud free Landsat-5 TM data of Fresno, California, USA were unmixed and the results were validated with the corresponding ground data. To study an urbanized landscape, a clear sky Landsat-5 TM data were unmixed and validated with coincident World View-2 abundance maps (of 2 m spatial resolution) for an area of San Francisco, California, USA. The results were evaluated using descriptive statistics, correlation coefficient, RMSE, probability of success, boxplot and bivariate distribution function. Finally, FCLS was used for sub-pixel land cover analysis of the monthly WELD (Wen-enabled Landsat data) repository from 2008 to 2011 of North America. The abundance maps in conjunction with DMSP-OLS nighttime lights data were used to extract the urban land cover features and analyze their spatial-temporal growth.

Landsat Satellites↗

DOE OSTI2024

In situ tumor model for longitudinal in silico imaging trials

Abstract Objective.In this article, we introduce a computational model for simulating the growth of breast cancer lesions accounting for the stiffness of surrounding anatomical structures.Approach.In our model, ligaments are classified as the most rigid structures while the softer parts of the breast are occupied by fat and glandular tissues As a result of these variations in tissue elasticity, the rapidly proliferating tumor cells are met with differential resistance. It is found that these cells are likely to circumvent stiffer terrains such as ligaments, instead electing to proliferate preferentially within the more yielding confines of the breast’s soft topography. By manipulating the interstitial tumor pressure in direct proportion to the elastic constants of the tissues surrounding the tumor, this model thus creates the potential for realizing a database of unique lesion morphology sculpted by the distinctive topography of each local anatomical infrastructure. We modeled the growth of simulated lesions within volumes extracted from fatty breast models, developed by Graffet alwith a resolution of 50μm generated with the open-source and readily available Virtual Imaging Clinical Trials for Regulatory Evaluation (VICTRE) imaging pipeline. To visualize and validate the realism of the lesion models, we leveraged the imaging component of the VICTRE pipeline, which replicates the siemens mammomat inspiration mammography system in a digital format. This system was instrumental in generating digital mammogram (DM) images for each breast model containing the simulated lesions.Results.By utilizing the DM images, we were able to effectively illustrate the imaging characteristics of the lesions as they integrated with the anatomical backgrounds. Our research also involved a reader study that compared 25 simulated DM regions of interest (ROIs) with inserted lesions from our models with DM ROIs from the DDSM dataset containing real manifestations of breast cancer. In general the simulation time for the lesions was approximately 2.5 hours, but it varied depending on the lesion’s local environment.Significance.The lesion growth model will facilitate and enhance longitudinal in silico trials investigating the progression of breast cancer.

Engineering↗

NASA NTRSDate not supplied

DLES Unreal Simulation Tool (DUST)

NASA’s future Artemis missions to the Moon seek to explore areas around the Lunar South Pole. Though humans have previously set foot on the lunar surface, the proposed region provides unique and challenging environments that require insight and investigation prior to arrival. Several teams throughout the agency are performing this site and mission planning, design, and analysis to support areas like the Human Landing System (HLS), surface mobility, habitation elements, and scientific exploration. The NASA Exploration Systems Simulation (NExSyS) team at Johnson Space Center is developing a graphical environment of the Lunar South Pole region. Lunar terrain information collected from the Lunar Reconnaissance Orbiter (LRO) is compiled and made available through Johnson Space Center’s Digital Lunar Exploration Sites (DLES) data sets. The DLES data is used to build this graphic environment. The process of ingesting and accurately modeling this information in a meaningful way for analysis creates its own challenges such as generating a performant model from the source data and the application of curvature. Additionally, the area around the Lunar South Pole experiences different lighting conditions than those observed from the Apollo missions. The need to use the lunar environmental data products provided by DLES combined with the capability to calculate date specific ephemerides in real-time has given rise to the development of the DLES Unreal Simulation Tool (DUST). DUST incorporates augmented terrain from the DLES product into a desktop application that allows exploration of the Lunar South Pole region and its complex lighting conditions. DUST leverages advanced capabilities in the recently released Unreal Engine 5 renderer by Epic Games such as double precision for positioning of planetary bodies and surface elements, multiple infinite light sources to represent the Sun and eventually Earthshine, high resolution shadow maps for dynamic shadow accuracy, real-time software ray-tracing for multi-surface bounce lighting to render sunlight reflected off surface elements and terrain features, and performance optimized level of detail shifting as the eyepoint changes in a scene. This paper details the DUST application, the technologies of the engine platform that enable scientific and engineering analysis, the unique techniques and processes developed to consume the DLES data sets, and how the tool is being used to support the Artemis program.

Lunar Visualization↗

NASA NTRS2007

NASA Tech Briefs, October 2007

Topics covered include; Wirelessly Interrogated Position or Displacement Sensors; Ka-Band Radar Terminal Descent Sensor; Metal/Metal Oxide Differential Electrode pH Sensors; Improved Sensing Coils for SQUIDs; Inductive Linear-Position Sensor/Limit-Sensor Units; Hilbert-Curve Fractal Antenna With Radiation- Pattern Diversity; Single-Camera Panoramic-Imaging Systems; Interface Electronic Circuitry for an Electronic Tongue; Inexpensive Clock for Displaying Planetary or Sidereal Time; Efficient Switching Arrangement for (N + 1)/N Redundancy; Lightweight Reflectarray Antenna for 7.115 and 32 GHz; Opto-Electronic Oscillator Using Suppressed Phase Modulation; Alternative Controller for a Fiber-Optic Switch; Strong, Lightweight, Porous Materials; Nanowicks; Lightweight Thermal Protection System for Atmospheric Entry; Rapid and Quiet Drill; Hydrogen Peroxide Concentrator; MMIC Amplifiers for 90 to 130 GHz; Robot Would Climb Steep Terrain; Measuring Dynamic Transfer Functions of Cavitating Pumps; Advanced Resistive Exercise Device; Rapid Engineering of Three-Dimensional, Multicellular Tissues With Polymeric Scaffolds; Resonant Tunneling Spin Pump; Enhancing Spin Filters by Use of Bulk Inversion Asymmetry; Optical Magnetometer Incorporating Photonic Crystals; WGM-Resonator/Tapered-Waveguide White-Light Sensor Optics; Raman-Suppressing Coupling for Optical Parametric Oscillator; CO2-Reduction Primary Cell for Use on Venus; Cold Atom Source Containing Multiple Magneto- Optical Traps; POD Model Reconstruction for Gray-Box Fault Detection; System for Estimating Horizontal Velocity During Descent; Software Framework for Peer Data-Management Services; Autogen Version 2.0; Tracking-Data-Conversion Tool; NASA Enterprise Visual Analysis; Advanced Reference Counting Pointers for Better Performance; C Namelist Facility; and Efficient Mosaicking of Spitzer Space Telescope Images.

Source record↗

NASA NTRS2009

Lunar Mapping and Modeling Project

The Lunar Mapping and Modeling Project (LMMP) has been created to manage the development of a suite of lunar mapping and modeling products that support the Constellation Program (CxP) and other lunar exploration activities, including the planning, design, development, test and operations associated with lunar sortie missions, crewed and robotic operations on the surface, and the establishment of a lunar outpost. The information provided through LMMP will assist CxP in: planning tasks in the areas of landing site evaluation and selection, design and placement of landers and other stationary assets, design of rovers and other mobile assets, developing terrain-relative navigation (TRN) capabilities, and assessment and planning of science traverses. The project draws on expertise from several NASA and non-NASA organizations (MSFC, ARC, GSFC, JPL, CRREL US Army Cold Regions Research and Engineering Laboratory, and the USGS). LMMP will utilize data predominately from the Lunar Reconnaissance Orbiter, but also historical and international lunar mission data (e.g. Apollo, Lunar Orbiter, Kaguya, Chandrayaan-1), as available and appropriate, to meet Constellation s data needs. LMMP will provide access to this data through a single intuitive and easy to use NASA portal that transparently accesses appropriately sanctioned portions of the widely dispersed and distributed collections of lunar data, products and tools. Two visualization systems are being developed, a web-based system called Lunar Mapper, and a desktop client, ILIADS, which will be downloadable from the LMMP portal. LMMP will provide such products as local and regional imagery and DEMs, hazard assessment maps, lighting and gravity models, and resource maps. We are working closely with the LRO team to prevent duplication of efforts and to ensure the highest quality data products. While Constellation is our primary customer, LMMP is striving to be as useful as possible to the lunar science community, the lunar commercial community, the lunar education and public outreach (E/PO) community, and anyone else interested in accessing or utilizing lunar data. A beta version of the portal and visualization systems is expected to be released in late 2009, with a version 1 release planned for early 2011.

Noble, Sarah K.↗

NASA NTRS2000

Simulators for the X-38/CRV Parafoil and Re-Entry Phases

The X38/CRV is unique in several aspects: it does not afford the pilot a forward view through a window and it utilizes a parafoil in the final landing flight phase. As a result of some of these unique attributes the prototype on-board displays will need to provide enhanced situation awareness to aid a crew member in supervising the onboard GNC software to select a landing site, and possible obstacle avoidance during the final flight phase. In the ESA/ESTEC visualization prototype system the scene is visualized using MultiGen OpenFlight models on high-end SGI machines. The Parafoil Guidance Navigation and Control (PGNC) algorithms are being developed as a joint NASA/ESA venture. These algorithms will be used onboard the vehicle to create nominal flight trajectories for the vehicle to follow. These same algorithms are also used as parafoil simulators in our augmented situation awareness system we are developing. The output of the parafoil simulator is displayed on a Windows-based computer running the LandForm FlightVision software. The FlightVision software is used to create the synthetic environment displays and all the necessary HUD symbology. Maps, such as aeronautical charts, as well as satellite imagery are optionally overlaid on the 3D-terrain model to provide additional situation awareness for the crew.

SITUATIONAL AWARENESS↗

NASA NTRS2011

Radar and Lidar Radar DEM

Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

remote sensing↗

NASA NTRS2016

Evaluation of Synthetic Vision Display Concepts for Improved Awareness in Unusual Attitude Recovery Scenarios

A recent study conducted by the Commercial Aviation Safety Team (CAST) determined 40 percent of all fixed-wing fatal accidents, between 2001 and 2011, were caused by Loss-of-Control (LOC) in flight (National Transportation Safety Board, 2015). Based on their findings, CAST recommended manufacturers develop and implement virtual day-visual meteorological conditions (VMC) display systems, such as synthetic vision or equivalent systems (CAST, 2016). In a 2015 simulation study conducted at NASA Langley Research Center (LaRC), researchers gathered to test and evaluate virtual day-VMC displays under realistic flight operation scenarios capable of inducing reduced attention states in pilots. Each display concept was evaluated to determine its efficacy to improve attitude awareness. During the experiment, Evaluation Pilots (EPs) were shown the following three display concepts on the Primary Flight Display (PFD): Baseline, Synthetic Vision (SV) with color gradient, and SV with texture. The baseline configuration was a standard, conventional 'blue over brown' display. Experiment scenarios were simulated over water to evaluate Unusual Attitude (UA) recovery over 'featureless terrain' environments. Thus, the SV with color gradient configuration presented a 'blue over blue' display with a linear blue color progression, to differentiate attitude changes between sky and ocean. The SV with texture configuration presented a 'blue over blue' display with a black checkerboard texture atop a synthetic ocean. These displays were paired with a Background Attitude Indicator (BAI) concept. The BAI was presented across all four Head-Down Displays (HDDs), displaying a wide field-of-view blue-over-blue attitude indicator. The BAI aligned with the PFD and showed through the background of the navigation displays with opaque transparency. Each EP participated in a two-part experiment series with a total seventy-five trial runs: Part I included a set of twenty-five Unusual Attitude Recovery (UAR) scenarios; Part II included a set of fifty Attitude Memory Recall Tasks (AMRT). At the conclusion of each trial, EPs were asked to complete a set post-run questionnaires. Quantitative results showed that there were no significant statistical effects on UA recovery times when utilizing SV with or without the presence of a BAI. Qualitative results show the SV displays (color, texture) with BAI On are most preferred for both UA recognition and recovery when compared with the baseline display. When only comparing SV display concepts, EPs performed better when using the SV with texture, BAI On, than any other display configuration. This is an interesting find considering most EPs noted their preference towards the SV with color gradient when the BAI was on.

Nicholas, Stephanie↗

DOE OSTI2019

Camp Fire processed Landsat 8 images, pre-fire, during-fire, post-fire

The Camp Fire rapidly spread across a landscape in Butte County, California, toward the city of Paradise in the early morning hours of 8 November 2018. GEE acquires L8 data products from USGS that include Real-Time Tier 1 DN values, representing scaled, calibrated at-sensor radiance, and Level-1 Precision Terrain (L1TP) processing. We carried out additional processing on the pre- and post-fire images, including an illumination correction to account for effects of steep topography, and radiometric normalization to ensure homogeneity between images. We also identified and processed high-quality images for both the pre-fire condition(25 Oct 2013), and the post-fire burn scar (26 Dec 2018). Using the tools we provided in the paper, we estimate that, over the first hour, the Camp Fire was consuming ~200 ha/minute of vegetation with a linear spread rate of 14 km over the fire’s first 25 minutes, or ~33km/hr. We briefly discuss broader use of remote sensing and geospatial analysis for fire research and risk management. A visualization app (sliderApp) that includes pre-fire, active fire, and post-fire images: https://caralyngorman.users.earthengine.app/view/camp-fire-sliding-map-3-9-19

54 ENVIRONMENTAL SCIENCES↗