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NASA NTRS1983

Space safety and rescue 1979-1981: Worldwide disaster response, rescue and safety employing space-borne systems

Selected papers from the 1979, 1980, and 1981 IAA symposia on space safety and rescue and on worldwide disaster response, safety, and rescue employing spaceborne systems are presented. Available papers published elsewhere and those presented at the 1976, 1977, and 1978 symposia are presented in abstract form. Subjects discussed include man-made space debris, nuclear-waste disposal in space, space-station safety design, psychological training, the introduction of female crewmembers, analysis of the November 23, 1980 earthquake as a design basis for satellite emergency communication, disaster warning using the GOES satellite, and satellite communications for disaster relief operations. Three reviews of the application of space technology to emergency and disaster relief and prevention, given at other symposia in 1981, are presented in an appendix. No individual items are abstracted in this volume

Brown, J. W.↗
NASA NTRS2012

Disaster Response Modeling Through Discrete-Event Simulation

Organizations today are required to plan against a rapidly changing, high-cost environment. This is especially true for first responders to disasters and other incidents, where critical decisions must be made in a timely manner to save lives and resources. Discrete-event simulations enable organizations to make better decisions by visualizing complex processes and the impact of proposed changes before they are implemented. A discrete-event simulation using Simio software has been developed to effectively analyze and quantify the imagery capabilities of domestic aviation resources conducting relief missions. This approach has helped synthesize large amounts of data to better visualize process flows, manage resources, and pinpoint capability gaps and shortfalls in disaster response scenarios. Simulation outputs and results have supported decision makers in the understanding of high risk locations, key resource placement, and the effectiveness of proposed improvements.

Wang, Jeffrey↗
NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

The Runtime for Airspace Concept Evaluation (RACE) is an open-source software architecture and framework to build configurable, highly concurrent and distributed message-based systems that offer scalable, low-latency performance on commodity hardware. RACE was used in commercial aviation applications to rapidly build systems that span several machines (including synchronized displays), interface existing hardware simulators and other live data feeds, and incorporate sophisticated visualization components such as NASA WorldWind. These RACE applications validated elements of the FAA’s System Wide Information Management (SWIM) Program, handling up to 1000 messages/sec from diverse sources (SFDPS, TFM-DATA, TAIS, ASDE-X, ITWS and local ADS) for 4,500 simultaneous flights tracked in the next-generation air transportation system’s digital backbone. We have since generalized RACE to support Open Data Integration (ODIN) applications outside aviation. Systems built with RACE/ODIN can be deployed in the field, on commodity hardware, and operate with limited or intermittent connectivity to the outside world. Our primary use case is a web-server with local/persistent data storage that runs within and only serves the stakeholder network (e.g. an incident command post). We are tailoring the RACE/ODIN system to support wildland fire management for the upcoming NASA Wildland Fire Safety Demonstration Series. RACE-ODIN is under consideration for application in the Scalable Traffic Management for Emergency Response Operations project, or STEReO, which aims to create a system that can be deployed during emergencies, to coordinate multiple elements of disaster response. Such data sources predominantly come from existing services on the internet (e.g. weather and satellite data, imported from so called "edge servers") but can also include dynamic (real-time) data from computer simulations and within the stakeholder network (such as aircraft and personnel tracking information). We will present the architecture and ODIN system demonstration incorporating local data from instrumented power-line towers, interpolated weather data and geospatial data from space-based platforms.

Joseph C Coughlan↗
NASA NTRSDate not supplied

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

The Runtime for Airspace Concept Evaluation (RACE) is an open-source software architecture and framework to build configurable, highly concurrent and distributed message-based systems that offer scalable, low-latency performance on commodity hardware. RACE was used in commercial aviation applications to rapidly build systems that span several machines (including synchronized displays), interface existing hardware simulators and other live data feeds, and incorporate sophisticated visualization components such as NASA WorldWind. These RACE applications validated elements of the FAA’s System Wide Information Management (SWIM) Program, handling up to 1000 messages/sec from diverse sources (SFDPS, TFM-DATA, TAIS, ASDE-X, ITWS and local ADS) for 4,500 simultaneous flights tracked in the next-generation air transportation system’s digital backbone. We have since generalized RACE to support Open Data Integration (ODIN) applications outside aviation. Systems built with RACE/ODIN can be deployed in the field, on commodity hardware, and operate with limited or intermittent connectivity to the outside world. Our primary use case is a web-server with local/persistent data storage that runs within and only serves the stakeholder network (e.g. an incident command post). We are tailoring the RACE/ODIN system to support wildland fire management for the upcoming NASA Wildland Fire Safety Demonstration Series. RACE-ODIN is under consideration for application in the Scalable Traffic Management for Emergency Response Operations project, or STEReO, which aims to create a system that can be deployed during emergencies, to coordinate multiple elements of disaster response. Such data sources predominantly come from existing services on the internet (e.g. weather and satellite data, imported from so called "edge servers") but can also include dynamic (real-time) data from computer simulations and within the stakeholder network (such as aircraft and personnel tracking information). We will present the architecture and ODIN system demonstration incorporating local data from instrumented power-line towers, interpolated weather data and geospatial data from space-based platforms.

Guillaume P Brat↗
NASA NTRS2015

International Space Station Data Collection for Disaster Response

Remotely sensed data acquired by orbital sensor systems has emerged as a vital tool to identify the extent of damage resulting from a natural disaster, as well as providing near-real time mapping support to response efforts on the ground and humanitarian aid efforts. The International Space Station (ISS) is a unique terrestrial remote sensing platform for acquiring disaster response imagery. Unlike automated remote-sensing platforms it has a human crew; is equipped with both internal and externally-mounted remote sensing instruments; and has an inclined, low-Earth orbit that provides variable views and lighting (day and night) over 95 percent of the inhabited surface of the Earth. As such, it provides a useful complement to autonomous sensor systems in higher altitude polar orbits. NASA remote sensing assets on the station began collecting International Disaster Charter (IDC) response data in May 2012. The initial NASA ISS sensor systems responding to IDC activations included the ISS Agricultural Camera (ISSAC), mounted in the Window Observational Research Facility (WORF); the Crew Earth Observations (CEO) Facility, where the crew collects imagery using off-the-shelf handheld digital cameras; and the Hyperspectral Imager for the Coastal Ocean (HICO), a visible to near-infrared system mounted externally on the Japan Experiment Module Exposed Facility. The ISSAC completed its primary mission in January 2013. It was replaced by the very high resolution ISS SERVIR Environmental Research and Visualization System (ISERV) Pathfinder, a visible-wavelength digital camera, telescope, and pointing system. Since the start of IDC response in 2012 there have been 108 IDC activations; NASA sensor systems have collected data for thirty-two of these events. Of the successful data collections, eight involved two or more ISS sensor systems responding to the same event. Data has also been collected by International Partners in response to natural disasters, most notably JAXA and Roscosmos/Energia through the Urugan program.

Stefanov, William L.↗
NASA NTRS2019

NASA Disasters Program: A Partner for Coastal Disaster Response, Resiliency, and Risk Reduction

Summary: The NASA Applied Sciences: Disasters Program has kicked off a pilot project as “Mid-Atlantic Resiliency Demonstration Study, Communities at Intensive Risk” in FY17 and FY18; Efforts focus on a holistic, interdisciplinary approach to integrate a full suite of capabilities from numerical weather prediction, tide and surge modeling at high spatial resolution and urban/neighborhood scales, and remote sensing capabilities for water detection and depth estimation; Future efforts - Partner with Federal Agencies, academia professional societies to complement and augment ongoing work using Earth observations unique to NASA - Translate hazards to risk in order to understand local and regional impacts and minimize vulnerability.

Bell, Jordan↗
NASA NTRS2003

Disaster Response and Preparedness Application: Emergency Environmental Response Tool (EERT)

In 2000, the National Aeronautics and Space Administration (NASA) Environmental Office at the John C. Stennis Space Center (SSC) developed an Environmental Geographic Information Systems (EGIS) database. NASA had previously developed a GIS database at SSC to assist in the NASA Environmental Office's management of the Center. This GIS became the basis for the NASA-wide EGIS project, which was proposed after the applicability of the SSC database was demonstrated. Since its completion, the SSC EGIS has aided the Environmental Office with noise pollution modeling, land cover assessment, wetlands delineation, environmental hazards mapping, and critical habitat delineation for protected species. At SSC, facility management and safety officers are responsible for ensuring the physical security of the facilities, staff, and equipment as well as for responding to environmental emergencies, such as accidental releases of hazardous materials. All phases of emergency management (planning, mitigation, preparedness, and response) depend on data reliability and system interoperability from a variety of sources to determine the size and scope of the emergency operation. Because geospatial data are now available for all NASA facilities, it was suggested that this data could be incorporated into a computerized management information program to assist facility managers. The idea was that the information system could improve both the effectiveness and the efficiency of managing and controlling actions associated with disaster, homeland security, and other activities. It was decided to use SSC as a pilot site to demonstrate the efficacy of having a baseline, computerized management information system that ultimately was referred to as the Emergency Environmental Response Tool (EERT).

Smoot, James↗
NASA NTRS2021

Satellites Support Disaster Response to Storm-Driven Landslides

High winds and flooding storm surges driven by tropical cyclones cause some of the deadliest and most damaging weather-related conditions around the world. The rainfall that cyclones bring compounds these conditions and, in hilly or mountainous areas, can trigger landslides that cause even more widespread and devastating impacts. When extreme precipitation occurs over short time frames, hillslopes may become saturated and critically unstable. The most intense storms can trigger thousands of landslides in mountainous areas, as was dramatically illustrated in Puerto Rico in September 2017, when Hurricane Maria’s rains left the landscape scarred by roughly 40,000 landslides. Before and during a major cyclone, disaster responders need information about where landslides are likely to occur. In the aftermath, locating landslides quickly helps authorities direct resources to where they are most needed to save people and critical infrastructure. However, this information is often unavailable during an event response or is presented only for small regions, constraining the effectiveness of response efforts.

Robert Emberson↗
NASA NTRS2015

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

Cloud computing capabilities have rapidly expanded within the private sector, offering new opportunities for meteorological applications. Collaborations between NASA Marshall, NASA Ames, and contractor partners led to evaluations of private (NASA) and public (Amazon) resources for executing short-term NWP systems. Activities helped the Marshall team further understand cloud capabilities, and benchmark use of cloud resources for NWP and other applications

Disasters↗
NASA NTRS1991

Telemedicine and international disaster response: Medical consultation to Armenia and Russia via a telemedicine spacebridge

The Telemedicine Spacebridge, a satellite mediated audio-video-fax link between four U.S. and two Armenian and Russian medical centers, permitted remote American consultants to assist Armenian and Russian physicians in the management of medical problems following the December 1988 earthquake in Armenia and the June 1989 gas explosion near Ufa. During 12 weeks of operations, 247 Armenian and Russian and 175 American medical professionals participated in 34 half-day clinical conferences. 209 patients were discussed, requiring expertise in 20 specialty areas. Telemedicine consultations resulted in altered diagnoses for 54, new diagnostic studies for 70, altered diagnostic processes for 47, and modified treatment plans for 47 of 185 Armenian patients presented. Simultaneous participation of several U.S. medical centers was judged beneficial; quality of data transmission was judged excellent. These results suggest that interactive consultation by remote specialists can provide valuable assistance to onsite physicians and favorably influence clinical decisions in the aftermath of major disasters.

Houtchens, Bruce A.↗
NASA NTRS2015

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud‐computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high‐performance computing environments, supporting multi‐node systems required for near real‐time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on‐demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on‐demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre‐compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF‐EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher‐resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short‐term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity‐building applications that extend numerical weather prediction to developing countries are intended to provide near real‐time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather‐related hazards, or impacts that local weather events may have during the recovery phase.

Molthan, Andrew↗