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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Expert systems and imaging - NASA's start-up work in intelligent image management

The problem of image management for NASA's Space Shuttle program and the future role of expert systems are considered. The difficulties involved in the storage and retrieval of the estimated 100,000 color photographs used for verification of essential installation, test, and repair procedures for Space Shuttle prelaunch are discussed. It is noted that the collection, classification, storage, and retrieval of high-quality pictoral images is possible through the use of pixels and an expert systems-assisted relational data base management system. The development of a query by pictorial example process is discussed. The NASA Intelligent Interactive Visual Data Base Management Systems project is detailed. It aims to conduct a systems analysis of a large-scale traditional image processing operation, collect data on critical human performance factors in the areas of image creation, processing, classification, storage, and retreival, and validate the attributes identified through the creation and testing of prototype models.

Ragusa, James M.↗
NASA NTRS2020

2SXPS: An Improved and Expanded Swift X-Ray Telescope Point-source Catalog

We present the 2SXPS (Swift-XRT Point Source) catalog, containing 206,335 point sources detected by the Swift X-ray Telescope (XRT) in the 0.3–10 keV energy range. This catalog represents a significant improvement over 1SXPS, with double the sky coverage (now 3790 deg2), and several significant developments in source detection and classification. In particular, we present for the first time techniques to model the effect of stray light—significantly reducing the number of spurious sources detected. These techniques will be very important for future, large effective area X-ray missions, such as the forthcoming Athena X-ray observatory. We also present a new model of the XRT point-spread function and a method for correctly localizing and characterizing piled-up sources. We provide light curves—in four energy bands, two hardness ratios, and two binning timescales—for every source, and from these deduce that over 80,000 of the sources in 2SXPS are variable in at least one band or hardness ratio. The catalog data can be queried or downloaded via a web interface at https://www.swift.ac.uk/2SXPS, via HEASARC, or in Vizier (IX/58).

Catalogs↗
NASA NTRS1972

Design evaluation in technology assessment: Illustrated by auditory impedance and sound distribution problems

Technology is considered as a culture for changing a physical world and technology assessment questions the inherent cultural capability to modify power and material in support of living organisms. A comprehensive goal-parameter-synthesis-criterion specification is presented as a basis for a rational assessment of technology. The thesis queries the purpose of the assessed problems, the factors considered, the relationships between factors, and the values assigned those factors to accomplish the appropriate purpose. Stationary and sequential evaluation of enviro-organismic systems are delegated to the responsible personalities involved in design; from promoter/designer through contractor to occupant. Discussion includes design goals derived from organismic factors, definitions of human responses which establish viable criteria and relevant correlation models, linking stimulus parameters, and parallel problem-discipline centered design organization. A consistent concept of impedance, as a degradation in the performance of a specified parameter, is introduced to overcome the arbitrary inoperative connotations of terms like noise, discomfort, and glare. Applications of the evaluative specification are illustrated through design problems related to auditory impedance and sound distribution.

Halldane, J. F.↗
NASA NTRS2022

Natural Language Processing Techniques for Intelligent Knowledge Management of Safety Reports

Safety, failure, and incident reports are common artifacts across various domains, including aviation and wildfire response. These reports are often mandatory to submit, resulting in the culmination of large repositories of text-based documents. Simultaneously, these reports and corresponding repositories are often only manually analyzed and queried by users via out-of-date search engines. As a consequence, we have been developing the Manager for Intelligent Knowledge Access (MIKA) toolkit, which uses natural language processing to improve information access and reuse. In this presentation, we discuss natural language processing techniques for knowledge discovery and apply these methods to a repository of aerial wildfire mishap reports. Two methods are used for knowledge discovery: topic modeling and named-entity recognition. We use topic modeling to identify hazards and perform a trend analysis to produce a data-driven risk matrix. A custom named-entity recognition model, build from fine tuning a pre-trained language model, is used to identify failure modes, failure causes, failure effects, control processes, and recommendations to aid in failure modes and effects analysis (FMEA). Throughout the presentation, we discuss and apply natural language processing techniques to better leverage the vast amount of information contained in report repositories.

Machine learning↗
NASA NTRS1996

Implementation of a Very Large Atmospheric Correction Lookup Table for ASTER Using a Relational Database Management System

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)is designed to provide a high resolution map of the Earth in both visible, near-infrared, and thermal spectral regions of the electromagnetic spectrum. The ASTER Science Team has developed several standard data product algorithms, but the most complex aod computing-intensive of these is the estimation of surface radiance and reflectance values, which is done by modeling and correcting for the effects of the atmosphere. The algorithm for atmospheric correction in the visible bands sensed by ASTER calls for use of a very large Atmospheric Correction Look Up Table (ACLUT).

ASTER↗
NASA NTRSDate not supplied

Data Sharing in Radiobiology; Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally „Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
NASA NTRS2023

Data Sharing in Radiation Biology: Towards FAIR

The value of scientific data depends on their findability, accessibility, integrability and reusability according to the FAIR principles. Together with the sustainability of data preservation and access, these principles underpin the long term benefits of scientific research. Within the domain of radiobiology we have a huge array of data types, themes and complexities which make standardisation of metadata, data structure and data integration very challenging. Moreover, it is clear that, for example, in the area of disaster preparedness, the ready discovery and availability of multiple types of data, for example on biological effects of exposure, climatology, ecology, human behavioural and attitudinal studies, is important for an integrated scientific approach. Because these data are spread over many databases, journal supplementary information resources and even the computers of the investigators, their discovery and reuse can be challenging. Despite exhortations from funding agencies and scientific institutions over the past two decades there is still a serious deficit in the willingness and in some cases the ability of investigators to share data, and although much may not be formally "Public domain“, information about the existence of the data, their metadata, and how to obtain them should always be available. We report the progress of work on three databases, the STORE and the NASA GeneLab and LSDA repositories to leverage the Radiation Biology Ontology (RBO), a structured terminology for metadata that can be used by all radiation biology-relevant databases to unite federated and automated data searches across multiple databases, for example using web services, and through semantic web technologies supporting data discovery. The initial primary use-cases for RBO were archiving data in the STORE database (https://www.storedb.org/), the repository used for the RadoNorm and Pianoforte Projects among others, and in the NASA Open Science Data Repository (https://osdr.nasa.gov/bio). The scope of radiobiology research ranges from basic physics to radiation oncology to sociolegal studies; no existing ontology had the necessary breadth or depth to fulfill this need. In addition, a formal ontology has the advantage of being usable for machine learning and, importantly, for tasks like data integration, knowledge extraction from the scientific literature and for query extension and data classification. Standardisation of metadata is one of the primary objectives of the FAIR principles for open data; RBO is an important landmark for FAIR-compliant radiation biology data sharing. The RBO is developed using the open-source tools of GitHub and the OBO Foundry-led Ontology Development Kit, and published through GitHub and the NIH/NCBI BioPortal website. This initial phase of concept modeling has yielded an ontology that has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies with relevance to radiation biology (for example, concepts from the ISO standard Basic Formal Ontology, the Environment Ontology and the Gene Ontology). We welcome input into the development of RBO and encourage its adoption.

ontologies↗
NASA NTRS2003

Development of a Dynamically Configurable, Object-Oriented Framework for Distributed, Multi-modal Computational Aerospace Systems Simulation: Second Year Progress Report

Mesh generation has long been recognized as a bottleneck in the CFD process. While much research on automating the volume mesh generation process have been relatively successful,these methods rely on appropriate initial surface triangulation to work properly. Surface discretization has been one of the least automated steps in computational simulation due to its dependence on implicitly defined CAD surfaces and curves. Differences in CAD peometry engines manifest themselves in discrepancies in their interpretation of the same entities. This lack of "good" geometry causes significant problems for mesh generators, requiring users to "repair" the CAD geometry before mesh generation. The problem is exacerbated when CAD geometry is translated to other forms (e.g., IGES )which do not include important topological and construction information in addition to entity geometry. One technique to avoid these problems is to access the CAD geometry directly from the mesh generating software, rather than through files. By accessing the geometry model (not a discretized version) in its native environment, t h s a proach avoids translation to a format which can deplete the model of topological information. Our approach to enable models developed in the Denali software environment to directly access CAD geometry and functions is through an Application Programming Interface (API) known as CAPRI. CAPRI provides a layer of indirection through which CAD-specific data may be accessed by an application program using CAD-system neutral C and FORTRAN language function calls. CAPRI supports a general set of CAD operations such as truth testing, geometry construction and entity queries.

Afjeh, Abdollah A.↗
NASA NTRS2005

The Virtual Solar Observatory: Still a Small Box

Two and a half years after a design study began, and a year and a half after development commenced, version 1.0 of the Virtual Solar Observatory (VSO) was released at the 2004 Fall AGU meeting. Although internal elements of the VSO have changed, the basic design has remained the same, reflecting the team's belief in the importance of a simple, robust mechanism for registering data provider holdings, initiating queries at the appropriate provider sites, aggregating the responses, allowing the user to iterate before making a final selection, and enabling the delivery of data directly from the providers. In order to make the VSO transparent, lightweight, and portable, the developers employed XML for the registry, SOAP for communication between a VSO instance and data services, and HTML for the graphic user interface (GUI's). We discuss the internal data model, the API, and user responses to various trial GUI's as typical design issues for any virtual observatory. We also discuss the role of the "small box" of data search, identification, and delivery services provided by the VSO in the larger, Sun-Solar System Connection virtual observatory (VxO) scheme.

Gurman, J. B.↗
NASA NTRS1992

Modelling global methane emissions from livestock: Biological and nutritional controls

The available observations of methane production from the literature have been compiled into a ruminant methane data base. This data base includes 400 treatment mean observations of methane losses from cattle and sheep, and minor numbers of measurements from other species. Methane loss varied from 2.0 to 11.6 percent of dietary gross energy. Measurements included describe the many different weights and physiological states of the animals fed and diets ranging from all forage to all concentrate diets or mixtures. An auxiliary spreadsheet lists approximately 1000 individual animal observations. Many important concepts have emerged from our query and analysis of this data set. The majority of the world's cattle, sheep, and goats under normal husbandry circumstances likely produce methane very close to 6 percent of their daily diets gross energy (2 percent of the diet by weight). Although individual animals or losses from specific dietary research circumstances can vary considerably, the average for the vast majority of groups of ruminant livestock are likely to fall between 5.5 to 6.5 percent. We must caution, however, that little experimental data is available for two-thirds of the world's ruminants in developing countries. Available evidence suggests similar percentage of emissions, but this supposition needs confirmation. More importantly, data is skimpy or unavailable to describe diet consumption, animal weight, and class distribution.

Johnson, Donald E.↗
NASA NTRS2016

Climate Analytics as a Service

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

big data↗
NASA NTRS2019

Partition-based Feasible Integer Solution Pre-computation for Hybrid Model Predictive Control

For multiparametric mixed-integer convex programming problems such as those encountered in hybrid model predictive control, we propose an algorithm for generating a feasible partition of a subset of the parameter space. The result is a static map from the current parameter to a suboptimal integer solution such that the remaining convex program is feasible. Convergence is proved with a new insight that the overlap among the feasible parameter sets of each integer solution governs the partition complexity. The partition is stored as a tree which makes querying the feasible solution efficient. The algorithm can be used to warm start a mixed integer solver with a real-time guarantee or to provide a reference integer solution in several suboptimal MPC schemes. The algorithm is tested on randomly generated systems with up to six states, demonstrating the effectiveness of the approach.

Bayard, David S.↗
NASA NTRS2016

Deep Space Optical Link ARQ Performance Analysis

Substantial advancements have been made toward the use of optical communications for deep space exploration missions, promising a much higher volume of data to be communicated in comparison with present-day Radio Frequency (RF) based systems. One or more ground-based optical terminals are assumed to communicate with the spacecraft. Both short-term and long-term link outages will arise due to weather at the ground station(s), space platform pointing stability, and other effects. To mitigate these outages, an Automatic Repeat Query (ARQ) retransmission method is assumed, together with a reliable back channel for acknowledgement traffic. Specifically, the Licklider Transmission Protocol (LTP) is used, which is a component of the Disruption-Tolerant Networking (DTN) protocol suite that is well suited for high bandwidth-delay product links subject to disruptions. We provide an analysis of envisioned deep space mission scenarios and quantify buffering, latency and throughput performance, using a simulation in which longterm weather effects are modeled with a Gilbert-Elliot Markov chain, short-term outages occur as a Bernoulli process, and scheduled outages arising from geometric visibility or operational constraints are represented. We find that both short- and long-term effects impact throughput, but long-term weather effects dominate buffer sizing and overflow losses as well as latency performance.

buffer analysis↗
NASA NTRS2011

Network-Capable Application Process and Wireless Intelligent Sensors for ISHM

Intelligent sensor technology and systems are increasingly becoming attractive means to serve as frameworks for intelligent rocket test facilities with embedded intelligent sensor elements, distributed data acquisition elements, and onboard data acquisition elements. Networked intelligent processors enable users and systems integrators to automatically configure their measurement automation systems for analog sensors. NASA and leading sensor vendors are working together to apply the IEEE 1451 standard for adding plug-and-play capabilities for wireless analog transducers through the use of a Transducer Electronic Data Sheet (TEDS) in order to simplify sensor setup, use, and maintenance, to automatically obtain calibration data, and to eliminate manual data entry and error. A TEDS contains the critical information needed by an instrument or measurement system to identify, characterize, interface, and properly use the signal from an analog sensor. A TEDS is deployed for a sensor in one of two ways. First, the TEDS can reside in embedded, nonvolatile memory (typically flash memory) within the intelligent processor. Second, a virtual TEDS can exist as a separate file, downloadable from the Internet. This concept of virtual TEDS extends the benefits of the standardized TEDS to legacy sensors and applications where the embedded memory is not available. An HTML-based user interface provides a visual tool to interface with those distributed sensors that a TEDS is associated with, to automate the sensor management process. Implementing and deploying the IEEE 1451.1-based Network-Capable Application Process (NCAP) can achieve support for intelligent process in Integrated Systems Health Management (ISHM) for the purpose of monitoring, detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, mitigation to maintain operability, and integrated awareness of system health by the operator. It can also support local data collection and storage. This invention enables wide-area sensing and employs numerous globally distributed sensing devices that observe the physical world through the existing sensor network. This innovation enables distributed storage, distributed processing, distributed intelligence, and the availability of DiaK (Data, Information, and Knowledge) to any element as needed. It also enables the simultaneous execution of multiple processes, and represents models that contribute to the determination of the condition and health of each element in the system. The NCAP (intelligent process) can configure data-collection and filtering processes in reaction to sensed data, allowing it to decide when and how to adapt collection and processing with regard to sophisticated analysis of data derived from multiple sensors. The user will be able to view the sensing device network as a single unit that supports a high-level query language. Each query would be able to operate over data collected from across the global sensor network just as a search query encompasses millions of Web pages. The sensor web can preserve ubiquitous information access between the querier and the queried data. Pervasive monitoring of the physical world raises significant data and privacy concerns. This innovation enables different authorities to control portions of the sensing infrastructure, and sensor service authors may wish to compose services across authority boundaries.

Figueroa, Fernando↗
NASA NTRS2016

Deep Space Optical Link ARQ Performance Analysis

Substantial advancements have been made toward the use of optical communications for deep space exploration missions, promising a much higher volume of data to be communicated in comparison with present -day Radio Frequency (RF) based systems. One or more ground-based optical terminals are assumed to communicate with the spacecraft. Both short-term and long-term link outages will arise due to weather at the ground station(s), space platform pointing stability, and other effects. To mitigate these outages, an Automatic Repeat Query (ARQ) retransmission method is assumed, together with a reliable back channel for acknowledgement traffic. Specifically, the Licklider Transmission Protocol (LTP) is used, which is a component of the Disruption-Tolerant Networking (DTN) protocol suite that is well suited for high bandwidth-delay product links subject to disruptions. We provide an analysis of envisioned deep space mission scenarios and quantify buffering, latency and throughput performance, using a simulation in which long-term weather effects are modeled with a Gilbert -Elliot Markov chain, short-term outages occur as a Bernoulli process, and scheduled outages arising from geometric visibility or operational constraints are represented. We find that both short- and long-term effects impact throughput, but long-term weather effects dominate buffer sizing and overflow losses as well as latency performance.

optical space communications↗
NASA NTRS2005

Exploring Diverse Data Sets and Developing New Theories and Ideas With Project Integration Architecture

The development of new ideas is the essence of scientific research. This is frequently done by developing models of physical processes and comparing model predictions with results from experiments. With models becoming ever more complex and data acquisition systems becoming more powerful, the researcher is burdened with wading through data ranging in volume up to a level of many terabytes and beyond. These data often come from multiple, heterogeneous sources and usually the methods for searching through it are at or near the manual level. In addition, current documentation methods are generally limited to researchers pen-and-paper style notebooks. Researchers may want to form constraint-based queries on a body of existing knowledge that is, itself, distributed over many different machines and environments and from the results of such queries then spawn additional queries, simulations, and data analyses in order to discover new insights into the problem being investigated. Currently, researchers are restricted to working within the boundaries of tools that are inefficient at probing current and legacy data to extend the knowledge of the problem at hand and reveal innovative and efficient solutions. A framework called the Project Integration Architecture is discussed that can address these desired functionalities.

Benyo, Theresa L.↗
NASA NTRS2017

The NASA Air Traffic Management Ontology: Technical Documentation

This document is intended to serve as comprehensive documentation for the NASA Air Traffic Management (ATM) Ontology. The ATM Ontology is a conceptual model that defines key classes of entities and relationships pertaining to the US National Airspace System (NAS) and the management of air traffic through that system. A wide variety of classes are represented in the ATM Ontology, including classes corresponding to flights, aircraft, manufacturers, airports, airlines, air routes, NAS facilities, air traffic control advisories, weather phenomena, and many others. The Ontology can be useful in the context of a variety of information management tasks relevant to NAS, including information exchange, data query and search, information organization, information integration, and terminology standardization.

information management↗
NASA NTRSDate not supplied

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗