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At least 325 records · Page 18

Flight Demonstration of Unmanned Aircraft System (UAS) Traffic Management (UTM) at Technical Capability Level 3

The goal of the Unmanned Aircraft System (UAS) Traffic Management (UTM) effort at NASA is to enable access to low-altitude airspace for small UAS. This goal is being achieved partly through partnerships that NASA has developed with the FAA, other government agencies, the UAS stakeholder community, and the designated FAA UAS Test Sites. This paper reports the technical and operational capabilities demonstrated during the UTM flight demonstration, March 6 through May 30, 2018. The demonstration featured geographically diverse operations, involving FAA UAS Test Sites in Alaska, Nevada, New York, North Dakota, Texas and Virginia. The demonstration leveraged the contributions of 30 partner organizations serving as UAS service suppliers, UAS operators, and/or providers of sensors, surveillance, connectivity, and management roles. Utilizing the UTM architecture developed at NASA, the demonstration explored 11 use cases for small UAS operations to highlight UTM capabilities at what NASA calls “Technical Capability Level (TCL) 3.” TCL 3 is characterized by multiple small UAS safely operating in moderately populated areas and beyond the visual line of sight of their operators. The TCL 3 flights demonstrated the basic feasibility of such operations in the UTM environment, including USS exchanges; communication, navigation and surveillance functions; sense and avoid capabilities; and technologies and procedures to enable them.

Aweiss, Arwa↗

Updates of MERRA-2 Data and Services at NASA GES DISC

Over40 years of NASA climate reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) are available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition to being used in traditional weather and climate research, MERRA-2 is also widely used in application studies of, e.g., wind and solar energy, air quality and health, food and drought, and heat waves. Two new MERRA-2 datasets were recently added at the GES DISC: (1) climate statistics derived fromMERRA-2 daily data to assist in the analysis of extreme temperature and precipitation events and of large-scale meteorological patterns from 1980 to the present and (2) gridded satellite and conventional observations processed in the MERRA-2 system, along with key statistics derived from the data assimilation, to help better understand how the quality of observations directly affect there analysis data. The GES DISC focuses its efforts on continually improving existing data services and to develop new data tools to satisfy various user communities. The newly added features include the following: Time series service: This is a new service for MERRA-2 data, which enables the easy and fast access of long-term hourly or daily time series at a location for popular parameters. The data is saved in a single le in Ascii format with a user- friendly structure. New analytic functions in the subsetter interface: Options for downloading daily minimum and maximum values have been added into the subsetter interface, in addition to the existing daily mean option, for all MERRA-2 and MERRA sub-daily products. Data format conversion to GeoTIFF has been implemented. New variables in Giovanni: Most monthly variables have been integrated into Giovanni, GESDISC’s online visualization and analysis tool. Due to the large data volume, hourly variables were selected based on user requests. More online information: New MERRA-2 documentation has been added: Data How-To, Data in Action, and FAQ. This presentation overviews two new MERRA-2 datasets and illustrates the new features of data services through a number of case studies. MERRA-2 data and services can be found at: https://disc.gsfc.gov/datasets?

Data management↗

Community Coordinated Modeling Center Support of Operations: Real-Time Simulations and V & V.

In support of Operations Community Coordinated Modeling Center (CCMC) performing validation and verification of space weather models. To identify suitable metrics the CCMC focus on parameters most useful to operations that CCMC resident models can provide. The real time simulations carried out at CCMC are an essential tool to test model performance and stability by using input conditions that may occur in nature at any time. Since 2001, the magnetospheric MHD model BATSRUS has been run in real time using ACE real time data. CCMC staff developed an experimental real-time system that controls uploading of the real-time ACE data, monitors continuous model execution, initiates automatic recovery procedure in case of data gaps or hardware failures, synchronizes BATSRUS and FRC runs, and periodically runs IDL based visualization software.

Kuznetsova, M.↗

Urban Environment Initiative

The Urban Environment Initiative (UEI), has been established as part of a Cooperative Agreement with the National Aeronautics and Space Administration (NASA). The UEI is part of NASA's overall High Performance Computing and Communications (HPCC) and the Information Infrastructure Technology Applications (IITA) programs. The goal of the UEI is to provide public access to Earth Science information and promote its use with a focus on the environment of urban areas. This goal will be accomplished through collaborative efforts of the UEI team with both community-based and local/regional governmental organizations. The UEI team is comprised of four organizations representing private industry, NASA, and universities: Prime Technologies Service Corporation, NASA's Minority University Space Interdisciplinary Network (MU-SPIN) California State University, at Los Angeles, and Central State University (Wilberforce, OH). "Urban Environment" refers to the web of environmental, economic, and social factors that combine to create the urban world in which we live. Examples of these factors are population distribution, neighborhood demographic profiles, economic resources, business activities, location and concentration of environmental hazards and various pollutants, proximity and level of urban services, which form the basis of the urban environment and ultimately affect our lives and experiences. The use of Geographic Information Systems (GIS) and remote sensing allows data to be visualized in the forms of maps and spatial images. The use of these tools allow analysis of information about urban environments. Also included are descriptions of the four query types which will assist in understanding the maps.

Source record↗

Ocean Data from MODIS at the NASA Goddard DAAC

Terra satellite carrying the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully launched on December 18, 1999. Some of the 36 different wavelengths that MODIS samples have never before been measured from space. New ocean data products, which have not been derived on a global scale before, are made available for research to the scientific community. For example, MODIS uses a new split window in the four-micron region for the better measurement of Sea Surface Temperature (SST), and provides the unprecedented ability (683 nm band) to measure chlorophyll fluorescence. At full ocean production, more than a thousand different ocean products in three major categories (ocean color, sea surface temperature, and ocean primary production) are archived at the NASA Goddard Earth Sciences (GES) Distributed Active Archive Center (DAAC) at the rate of approx. 230GB/day. The challenge is to distribute such large volumes of data to the ocean community. It is achieved through a combination of public and restricted EOS Data Gateways, the GES DAAC Search and Order WWW interface, and an FTP site that contains samples of MODIS data. A new Search and Order WWW interface at http://acdisx.gsfc.nasa.gov/data/ developed at the GES DAAC is based on a hierarchical organization of data, will always return non-zero results. It has a very convenient geographical representation of five-minute data granule coverage for each day MODIS Data Support Team (MDST) continues the tradition of quality support at the GES DAAC for the ocean color data from the Coastal Zone Color Scanner (CZCS) and the Sea Viewing Wide Field-of-View Sensor (SeaWiFS) by providing expert assistance to users in accessing data products, information on visualization tools, documentation for data products and formats (Hierarchical Data Format-Earth Observing System (HDF-EOS)), information on the scientific content of products and metadata. Visit the MDST website at http://daac.gsfc.nasa.gov/CAMPAIGN DOCS/MODIS/index.html

Leptoukh, Gregory G.↗

Bird's Eye View - A 3-D Situational Awareness Tool for the Space Station

Even as space-qualified computer hardware lags well behind the latest home computers, the possibility of using high-fidelity interactive 3-D graphics for displaying important on board information has finally arrived, and is being used on board the International Space Station (ISS). With the quantity and complexity of space-flight telemetry, 3-D displays can greatly enhance the ability of users, both onboard and on the ground, to interpret data quickly and accurately. This is particularly true for data related to vehicle attitude, position, configuration, and relation to other objects on the ground or in-orbit Bird's Eye View (BEV) is a 3-D real-time application that provides a high degree of Situational Awareness for the crew. Its purpose is to instantly convey important motion-related parameters to the crew and mission controllers by presenting 3-D simulated camera views of the International Space Station (ISS) in its actual environment Driven by actual telemetry, and running on board, as well as on the ground, the user can visualize the Space Station relative to the Earth, Sun, stars, various reference frames, and selected targets, such as ground-sites or communication satellites. Since the actual ISS configuration (geometry) is also modeled accurately, everything from the alignment of the solar panels to the expected view from a selected window can be visualized accurately. A virtual representation of the Space Station in real time has many useful applications. By selecting different cameras, the crew or mission control can monitor the station's orientation in space, position over the Earth, transition from day to night, direction to the Sun, the view from a particular window, or the motion of the robotic arm. By viewing the vehicle attitude and solar panel orientations relative to the Sun, the power status of the ISS can be easily visualized and understood. Similarly, the thermal impacts of vehicle attitude can be analyzed and visually confirmed. Communication opportunities can be displayed, and line-of-sight blockage due to interference by the vehicle structure (or the Earth) can be seen easily. Additional features in BEV display targets on the ground and in-orbit, including cities, communication sites, landmarks, satellites, and special sites of scientific interest for Earth observation and photography. Any target can be selected and tracked. This gives the user a continual line-of-sight to the target of current interest, and real-time knowledge about its visibility. Similarly, the vehicle ground-track, and an option to show "visibility circles" around displayed ground sites, provide continuous insight regarding current and future visibility to any target BEV was designed with inputs from many disciplines in the flight control and operations community both at NASA and from the International Partners. As such, BEV is setting the standards for interactive 3-D graphics for spacecraft applications. One important contribution of BEV is a generic graphical interface for camera control that can be used for any 3-D applications. This interface has become part of the International Display and Graphics Standards for the 16-nation ISS partnership. Many other standards related to camera properties, and the display of 3-D data, also have been defined by BEV. Future enhancements to BEV will include capabilities related to simulating ahead of the current time. This will give the user tools for analyzing off-nominal and future scenarios, as well as for planning future operations.

Dershowitz, Adam↗

An approach for relating the results of quantitative nondestructive evaluation to intrinsic properties of high-performance materials

One of the most difficult problems the manufacturing community has faced during recent years has been to accurately assess the physical state of anisotropic high-performance materials by nondestructive means. In order to advance the design of ultrasonic nondestructive testing systems, a more fundamental understanding of how ultrasonic waves travel and interact within the anisotropic material is needed. The relationship between the ultrasonic and engineering parameters needs to be explored to understand their mutual dependence. One common denominator is provided by the elastic constants. The preparation of specific graphite/epoxy samples to be used in the experimental investigation of the anisotropic properties (through the measurement of the elastic stiffness constants) is discussed. Accurate measurements of these constants will depend upon knowledge of refraction effects as well as the direction of group velocity propagation. The continuing effort for the development of improved visualization techniques for physical parameters is discussed. Group velocity images are presented and discussed. In order to fully understand the relationship between the ultrasonic and the common engineering parameters, the physical interpretation of the linear elastic coefficients (the quantities that relate applied stresses to resulting strains) are discussed. This discussion builds a more intuitional understanding of how the ultrasonic parameters are related to the traditional engineering parameters.

Miller, James G.↗

Towards a New Generation of Agricultural System Data, Models and Knowledge Products: Design and Improvement

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. We propose an implementation strategy that would link a "pre-competitive" space for model development to a "competitive space" for knowledge product development and through private-public partnerships for new data infrastructure. Specific model improvements would be based on further testing and evaluation of existing models, the development and testing of modular model components and integration, and linkages of model integration platforms to new data management and visualization tools.

Agricultural systems↗

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗

The microbial community of Ophrydium versatile colonies: endosymbionts, residents, and tenants

Ophrydium versatile is a sessile peritrichous ciliate (Kingdom Protoctista, class Oligohymenophora, order Peritrichida, suborder Sessilina) that forms green, gelatinous colonies. Chlorophyll a and b impart a green color to Ophrydium masses due to 400-500 Chlorella-like endosymbionts in each peritrich. Ophrydium colonies, collected from two bog wetlands (Hawley and Leverett, Massachusetts) were analyzed for their gel inhabitants. Other protists include ciliates, mastigotes, euglenids, chlorophytes, and heliozoa. Routine constituents include from 50-100,000 Nitzschia per ml of gel and at least four other diatom genera (Navicula, Pinnularia, Gyrosigma, Cymbella) that may participate in synthesis of the gel matrix. Among the prokaryotes are filamentous and coccoid cyanobacteria, large rod-shaped bacteria, at least three types of spirochetes and one unidentified Saprospira-like organism. Endosymbiotic methanogenic bacteria, observed using fluorescence microscopy, were present in unidentified hypotrichous ciliates. Animals found inside the gel include rotifers, nematodes, and occasional copepods. The latter were observed in the water reservoir of larger Ophrydium masses. From 30-46% of incident visible radiation could be attenuated by Ophrydium green jelly masses in laboratory observations. Protargol staining was used to visualize the elongate macronuclei and small micronucleus of O. versatile zooids and symbiotic algal nuclei. Electron microscopic analysis of the wall of the Chlorella-like symbiont suggests that although the Ophrydium zooids from British Columbia harbor Chlorella vulgaris, those from Hawley Bog contain Graesiella sp. The growth habit in the photic zone and loose level of individuation of macroscopic Ophrydium masses are interpretable as extant analogs of certain Ediacaran biota: colonial protists in the Vendian fossil record.

Non-NASA Center↗

Tensoral for post-processing users and simulation authors

The CTR post-processing effort aims to make turbulence simulations and data more readily and usefully available to the research and industrial communities. The Tensoral language, which provides the foundation for this effort, is introduced here in the form of a user's guide. The Tensoral user's guide is presented in two main sections. Section one acts as a general introduction and guides database users who wish to post-process simulation databases. Section two gives a brief description of how database authors and other advanced users can make simulation codes and/or the databases they generate available to the user community via Tensoral database back ends. The two-part structure of this document conforms to the two-level design structure of the Tensoral language. Tensoral has been designed to be a general computer language for performing tensor calculus and statistics on numerical data. Tensoral's generality allows it to be used for stand-alone native coding of high-level post-processing tasks (as described in section one of this guide). At the same time, Tensoral's specialization to a minute task (namely, to numerical tensor calculus and statistics) allows it to be easily embedded into applications written partly in Tensoral and partly in other computer languages (here, C and Vectoral). Embedded Tensoral, aimed at advanced users for more general coding (e.g. of efficient simulations, for interfacing with pre-existing software, for visualization, etc.), is described in section two of this guide.

Dresselhaus, Eliot↗

Making NASA GES DISC Level 2 Data GIS Analysis Ready

There are many valuable data hosted by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for GIS applications in the areas of extreme weather events, climatic anomaly, and public health. However, using NASA Earth Science Data poses some challenges for GIS users. Many of these users are not experts in Earth Observation and have little knowledge about NASA's Earth science data. In the GIS community, GeoTiff is the most widely used raster format, whereas NASA's data is primarily in complex multidimensional netCDF and HDF formats. This complexity makes it difficult for GIS users, especially those who are unfamiliar with these formats. Although GIS software like ArcGIS has made progress in processing multidimensional netCDF data, certain issues still remain, particularly with level 2 data. In this study, we use TROPSpheric Monitoring instrument (TROPOMI) level 2 data as an example to demonstrate how to make such data GIS analysis ready. The process involves: 1. Creating a feature layer from the TROPOMI level 2 data. 2. Converting the feature layer to a gridded raster dataset. 3. Mosaicking gridded raster datasets into a raster dataset covering the entire desired extent. 4. Generating a symbology with a GIBS-specific style that aligns with the visual standards and requirements of GIBS. 5. Publishing image services. By performing these preprocessing and transformation steps, NASA level 2 data can be made compatible and ready for use within GIS software for various spatial analysis and visualization tasks.

Geographic Information System↗

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Barghouty, Nasser↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

The Challenge of Planning and Execution for Spacecraft Mobile Robots

The need for spacecraft mobile robots continues to grow. These robots offer the potential to increase the capability, productivity, and duration of space missions while decreasing mission risk and cost. Spacecraft Mobile Robots (SMRs) can serve a number of functions inside and outside of spacecraft from simpler tasks, such as performing visual diagnostics and crew support, to more complex tasks, such as performing maintenance and in-situ construction. One of the predominant challenges to deploying SMRs is to reduce the need for direct operator interaction. Teleoperation is often not practical due to the communication latencies incurred because of the distances involved and in many cases a crewmember would directly perform a task rather than teleoperate a robot to do it. By integrating a mixed-initiative constraint-based planner with an executive that supports adjustably autonomous control, we intend to demonstrate the feasibility of autonomous SMRs by deploying one inside the International Space Station (ISS) and demonstrate in simulation one that operates outside of the ISS. This paper discusses the progress made at NASA towards this end, the challenges ahead, and concludes with an invitation to the research community to participate.

Dorais, Gregory A.↗

Exploring Innovative Methods for Earth Science Communication Through NASA’s Earth Information Center

Environmental challenges stemming from unprecedented changes in our planet have increased the need to communicate our understanding of Earth as a connected system. In June 2023, NASA unveiled the Earth Information Center (EIC), part of NASA’s Earth Action Strategy aimed at amplifying NASA’s Earth science impact by engaging decision-makers beyond the scientific community. Existing in both physical and virtual space, the EIC provides critical information on how the planet is changing and affecting livelihoods across the globe. For over fifty years, NASA has utilized the unique vantage point space offers to monitor Earth in collaboration with Federal partners. Through an expanding fleet of Earth observing satellites and sensors, NASA informs local to global decision making within nine thematic areas: agriculture, biodiversity, disasters, greenhouse gases, health and air quality, sea level rise and coastal impacts, sustainable energy, water resources, and wildfires. Visitors to the inaugural location of the EIC at NASA Headquarters in Washington D.C., can interact with Earth observation data and models through innovative exhibits and storytelling. Designed by an interdisciplinary team, the EIC is designed for multiple modality learning to reach a wide base of end-users. Data driven visualizations, near real-time information, and curated stories highlight the applications of Earth observations to address environmental challenges. Complementary exhibits and immersive storytelling allow visitors to physically step inside environmental data and connect with information on an emotional level. Taken together, the collective EIC provides scientists and non-scientists alike with the ability to see our home planet as NASA sees it, as a system of systems, while delivering easily accessible information to those who need it most.

Earth Information Center↗

Airport Surface Movement Technologies: Atlanta Demonstrations Overview

A flight demonstration was conducted in August 1997 at the Hartsfield Atlanta (ATL) International Airport as part of low visibility landing and surface operations (LVLASO) research activities. This research was aimed at investigating technology to improve the safety and efficiency of aircraft movements on the surface during the operational phases of roll-out, turnoff, and taxi in any weather condition down to a runway visual range of 300 feet. The system tested at ATL was composed of airborne and ground-based components that were integrated to provide both the flight crew and controllers with supplemental information to enable safe, expedient surface operations. Experimental displays were installed on a Boeing 757-200 research aircraft in both headup and head-down formats. On the ground, an integrated system maintained surveillance of the airport surface and a controller interface provided routing and control instructions. While at ATL, the research aircraft performed a series of flight and taxi operations to show the validity of the operational concept at a major airport facility, to validate simulation findings, and to assess each of the individual technologies performance in an airport environment. The concept was demonstrated to over 100 visitors from the Federal Aviation Administration (FAA) and the aviation community. This paper gives an overview of the LVLASO system and ATL test activities.

Jones, Denise R.↗