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All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Aggregation Tool to Create Curated Data albums to Support Disaster Recovery and Response

Despite advances in science and technology of prediction and simulation of natural hazards, losses incurred due to natural disasters keep growing every year. Natural disasters cause more economic losses as compared to anthropogenic disasters. Economic losses due to natural hazards are estimated to be around $6-$10 billion dollars annually for the U.S. and this number keeps increasing every year. This increase has been attributed to population growth and migration to more hazard prone locations such as coasts. As this trend continues, in concert with shifts in weather patterns caused by climate change, it is anticipated that losses associated with natural disasters will keep growing substantially. One of challenges disaster response and recovery analysts face is to quickly find, access and utilize a vast variety of relevant geospatial data collected by different federal agencies such as DoD, NASA, NOAA, EPA, USGS etc. Some examples of these data sets include high spatio-temporal resolution multi/hyperspectral satellite imagery, model prediction outputs from weather models, latest radar scans, measurements from an array of sensor networks such as Integrated Ocean Observing System etc. More often analysts may be familiar with limited, but specific datasets and are often unaware of or unfamiliar with a large quantity of other useful resources. Finding airborne or satellite data useful to a natural disaster event often requires a time consuming search through web pages and data archives. Additional information related to damages, deaths, and injuries requires extensive online searches for news reports and official report summaries. An analyst must also sift through vast amounts of potentially useful digital information captured by the general public such as geo-tagged photos, videos and real time damage updates within twitter feeds. Collecting and aggregating these information fragments can provide useful information in assessing damage in real time and help direct recovery efforts. The search process for the analyst could be made much more efficient and productive if a tool could go beyond a typical search engine and provide not just links to web sites but actual links to specific data relevant to the natural disaster, parse unstructured reports for useful information nuggets, as well as gather other related reports, summaries, news stories, and images. This presentation will describe a semantic aggregation tool developed to address similar problem for Earth Science researchers. This tool provides automated curation, and creates "Data Albums" to support case studies. The generated "Data Albums" are compiled collections of information related to a specific science topic or event, containing links to relevant data files (granules) from different instruments; tools and services for visualization and analysis; information about the event contained in news reports, and images or videos to supplement research analysis. An ontology-based relevancy-ranking algorithm drives the curation of relevant data sets for a given event. This tool is now being used to generate a catalog of Hurricane Case Studies at Global Hydrology Resource Center (GHRC), one of NASA's Distribute Active Archive Centers. Another instance of the Data Albums tool is currently being created in collaboration with NASA/MSFC's SPoRT Center, which conducts research on unique NASA products and capabilities that can be transitioned to the operational community to solve forecast problems. This new instance focuses on severe weather to support SPoRT researchers in their model evaluation studies

Ramachandran, Rahul↗
NASA NTRS2022

Environmental Justice Needs Assessment for Disasters: Assessing the Landscape and Capacity of Organizations & Communities Working Towards Environmental Justice with Potential to Use NASA Earth Observations to Support Equitable Disaster Management and Risk Reduction

Natural disasters pose an increasing risk to communities worldwide. Marginalized populations, in particular, experience compounding vulnerabilities that contribute to unequal burdens of natural hazards as a result of systemic inequality stemming from historical disenfranchisement, disinvestment, and discriminatory policies such as racial redlining. This project connected with community organizations working at the intersection of environmental justice (EJ) and natural disaster management throughout the United States, to assess how NASA DEVELOP can leverage geospatial science to advance EJ efforts. Our team conducted a landscape analysis, which included a literature review, annotated bibliography, and identification of organizations working in EJ and disasters. We engaged EJ organizations in discussions to understand their current resources, challenges, and geospatial needs to inform how DEVELOP and NASA Applied Sciences can support their EJ and disaster work. Findings were compiled in a synthesis report and visualized in an ArcGIS StoryMap to showcase the work of EJ organizations, provide geospatial resources for them to explore, and provide examples of how remote sensing can be utilized in EJ and disasters work. The knowledge gained and end products created support the integration of EJ in future DEVELOP projects, and the expanded use of Earth observations by communities in support of a more just tomorrow.

Julianne Liu↗
NASA NTRS2018

UTM and D-NET: NASA and JAXA's Collaborative Research on Integrating Small UAS with Disaster Response Efforts

Natural disasters, such as flooding, wildfire, hurricane, tornadoes, earthquakes and tsunamis, pose challenges in preserving human life and minimizing the damages to a region. During catastrophic events, timely response of disaster relief personnel, an efficient deployment of resources in the recovery effort, and coordinated information sharing amongst different relief agencies can make a substantial difference in responding to those impacted by the disaster. Many relief activities currently utilize both ground personnel and manned airborne assets during different phases of the disaster response. Typically, multiple organizations support relief activities and this often creates logistics coordination challenges between agencies which can result in wasted time or resources. The Japan Aerospace Exploration Agency (JAXA) has been developing an "Integrated aircraft operation system for disaster relief (D-NET)", which assists collection and sharing of disaster information through the integrated operation of aircraft such as helicopters, aircraft, and satellites, for efficient and safe rescue operations by disaster relief aircraft. Due to the advancement in unmanned aircraft systems (UAS) technologies, public safety organizations have started incorporating small UAS (sUAS) as an asset in their disasters response activities. To address the airspace integration challenges of the influx of sUAS in the United States the National Aeronautics and Space Administration (NASA), under the UAS Traffic Management (UTM) project, has been engaged in research to enable large-scale commercial applications of sUAS operating in low altitude airspace. This paper presents the integration of D-NET, which incorporate sUAS in the planning, information sharing, and operation support of disasters response activities, and UTM, which provides airspace management to enable large scale high density operations. The integration of the DNET and UTM systems enables coordination, data sharing, and airspace management to improve the timeliness of the disaster response, enable relief organization to reduce cost and overhead by using UAS assets and still maintain airspace safety during the relief activities.

UTM↗
NASA NTRS2024

ENLIGHTEN: Electrical Network Line Inspection Guided by High-Speed Technology & Electromagnetic Navigation

Natural disasters are a major cause of power outages, primarily due to their damage to power line infrastructure. As a result, the current state of power maintenance, with a heavy reliance on manual labor, is in trouble. Its lack of speed and autonomy must be addressed to ensure power security for households and institutions worldwide. This innovative approach explores how High-Speed Unmanned Aerial Vehicle (HSUAV) technology can inspect power line infrastructure rapidly in response to natural disaster scenarios. The HSUAV technology will be accompanied by enhanced sensory equipment including light detection and ranging (LiDAR), thermal imaging, and electromagnetic field (EMF) navigation. It would also be supplemented by innovative forms of machine learning models and recharging systems to efficiently detect anomalies in power line infrastructure. The proposed system, ENLIGHTEN, can help restore power in affected communities after a devastating natural disaster, greatly improving relief efforts. In the future, ENLIGHTEN can be expanded beyond the United States and shared worldwide, effectively mitigating the consequences on a larger scale.

UAV systems, Power line management, Natural disast↗
NASA NTRS2017

Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors

On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.

SERVIR↗
NASA NTRS1975

Remote sensing utility in a disaster struck urban environment

Standard operating procedures, utilizing remote sensing, are outlined for public health assistance during natural disaster relief operations. A manual to aid decision making for public health authorities is included. Flow charts which show the procedures that need to be implemented during a natural disaster are also included. Emphasis is placed on a preventive approach to the effects of disasters, and specifically to post-disaster problems that relate to public health concerns during the emergency phase of relief.

Rush, M.↗
NASA NTRSDate not supplied

Evaluating Machine Learning Approaches to Plume Tracking

On July 15, 2022, the Hunga Tonga-Hunga Ha’apai (HTHH) submarine volcano erupted, propelling trace gasses and ash through the troposphere and up into the stratosphere. Previous studies manually tracked the aerosol and trace gas plumes over time across different positions in the southern hemisphere. Using imagery from NASA’s Earth Observing System, including MODIS aerosol products and OMI sulfur dioxide products, this research demonstrates how open-source machine learning (ML) models, like Meta’s Segment Anything Model (SAM), can perform automatic plume tracking following the Hunga Tonga eruption. This extensible methodology, and modular data processing and modeling pipeline, establishes a framework for systematically and rapidly studying natural disasters, including additional volcanic eruptions and large-scale wildfires. By combining advanced machine learning techniques, such as SAM’s zero-shot learning, with large volumes of NASA’s Earth Observation and remote sensing data, this work shows how AI and open science can accelerate research and generate actionable results, even for unprecedented events. The tools and technologies presented here can help translate earth science to action from NASA’s current and future Earth observing satellite missions, and assist researchers and stakeholders in understanding, mapping, and responding to natural disasters in a changing world.

machine learning↗
NASA NTRS2004

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica, composed of the seven Central American countries and the five southernmost states of Mexico, make up only a small fraction of the world's land surface. However, the region is home to seven to eight percent of the planet's biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica's biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, D. E.↗
NASA NTRS2005

SIAM-SERVIR: An Environmental Monitoring and Decision Support System for Mesoamerica

In 2002/2003 NASA, the World Bank and the United States Agency for International Development (USAID) joined with the Central American Commission for Environment and Development (CCAD) to develop an advanced decision support system for Mesoamerica (named SERVIR) as part of the Mesoamerican Environmental Information System (SIAM). Mesoamerica - composed of the seven Central American countries and the five southernmost states of Mexico - make up only a small fraction of the world s land surface. However, the region is home to seven to eight percent of the planet s biodiversity (14 biosphere reserves, 31 Ramsar sites, 8 world heritage sites, 589 protected areas) and 45 million people including more than 50 different ethnic groups. Today Mesoamerica s biological and cultural diversity is severely threatened by extensive deforestation, illegal logging, water pollution, and uncontrolled slash and burn agriculture. Additionally, Mesoamerica's distinct geology and geography result in disproportionate vulnerability to natural disasters such as earthquakes, hurricanes, drought, and volcanic eruptions. NASA Marshall Space Flight Center, together with the University of Alabama in Huntsville (UAH) and the SIAM-SERVIR partners are developing state-of-the-art decision support tools for environmental monitoring as well as disaster prevention and mitigation in Mesoamerica. These partners are contributing expertise in space-based observation with information management technologies and intimate knowledge of local ecosystems to create a system that is being used by scientists, educators, and policy makers to monitor and forecast ecological changes, respond to natural disasters and better understand both natural and human induced effects. In its first year of development and operation, the SIAM-SERVIR project has already yielded valuable information on Central American fires, weather conditions, and the first ever real-time data on red tides. This paper presents the progress thus far in the development of SIAM-SERVIR and the plans for the future.

Irwin, Daniel E.↗
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 NTRS2020

Planetary Defence Activities Beyond NASA and ESA

The collision of a significant asteroid or comet with Earth represents a singular natural disaster for a myriad of reasons, including: its extraterrestrial origin; the fact that it is perhaps the only natural disaster that is preventable in many cases, given sufficient preparation and warning; its scope, which ranges from damaging a city to an extinction-level event; and the duality of asteroids and comets themselves---they are grave potential threats, but are also tantalising scientific clues to our ancient past and resources with which we may one day build a prosperous spacefaring future. Accordingly, the problems of developing the means to interact with asteroids and comets for purposes of defence, scientific study, exploration, and resource utilisation have grown in importance over the past several decades. Since the 1980s, more and more asteroids and comets (especially the former) have been discovered, radically changing our picture of the solar system. At the beginning of the year 1980, approximately 9,000 asteroids were known to exist. By the beginning of 2001, that number had risen to approximately 125,000 thanks to the Earth-based telescopic survey efforts of the era, particularly the emergence of modern automated telescopic search systems, pioneered by the Massachusetts Institute of Technology’s (MIT’s) LINEAR system in the mid-to-late 1990s. Today, in late 2019, about 840,000 asteroids have been discovered, with more and more being found every week, month, and year. Of those, approximately 21,400 are categorised as near-Earth asteroids (NEAs), 2,000 of which are categorised as Potentially Hazardous Asteroids (PHAs) and 2,749 of which are categorised as potentially accessible. The hazards posed to us by asteroids affect people everywhere around the world. As well, the opportunities presented by asteroids may benefit our entire species. Thus, with such a large number of currently known asteroids and so many yet to be discovered, it is not surprising that individuals, organisations, institutions, and governments all around the world have become interested in the study of asteroids. Indeed, a variety of government space agencies, private organisations, and individuals have worked on developing the means by which to observe, study, and even interact with asteroids and comets for purposes including science, exploration, pioneering, commerce, and planetary defence. This includes significant individual contributions by amateur asteroid astronomers all over the world. International cooperation in planetary defence within the contexts of the United Nations and the International Asteroid Warning Network (IAWN) are discussed in Chapter 2, and the activities undertaken by the world’s larger space agencies, ESA and NASA, are discussed in Chapters 3 and 4. But, what of the other agencies and institutions around the world who are also working on the problem of defence against hazardous asteroids and comets, or related topics? In this chapter we provide an overview, in alphabetical order, of some of the planetary defence related efforts that have been undertaken around the world beyond the activities at the United Nations, NASA, and ESA.

Barbee, Brent W.↗
DOE OSTI2025

LandScan Mosaic Rapid Population Update: Jamaica After Hurricane Melissa (V1)

During a natural disaster such as Hurricane Melissa, understanding where people are located is critical for situational awareness, operational planning and humanitarian support and consequence assessment. Traditional population datasets focus on mapping populations based on residential, or "business-as-usual" scenarios. However, natural disasters can create disruptions in daily routines of population in addition to the magnitude of the population displacement, depending on the type, duration, context, and location of the event. The Geospatial Science and Human Security Division at Oak Ridge National Laboratory (ORNL) produced this latest LandScan Mosaic Rapid Population Update for Jamaica following Hurricane Melissa, a category 5 hurricane that made landfall on Jamaica on October 28 2025. This Rapid Population Update captures the immediate population displacement following the hurricane using a combination of open-source building damage assessment data from Microsoft, flood exposure data from the Global Flood Monitoring service, reported population displacement information, and humanitarian shelter locations from the Jamaican Office of Disaster Preparedness and Emergency Management and the underlying LandScan Mosaic Jamaica as a base population.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Introduction to Microgrids

A microgrid is simply a typical power system that has distributed energy resources (DERs), like small diesel generators, with loads in the network. The resiliency offered by microgrids to retain service during system events makes them a suitable support for the electric grid during natural disasters. One key factor that differentiates microgrids from a typical distribution grid is its ability to disconnect itself in the event of a blackout and sustain its loads through DERs. Microgrid systems will reconnect to the main grid when the grid comes back up. The resiliency offered by microgrids to retain service during system events makes them a suitable support for the electric grid during natural disasters. This presentation discusses the typical key steps involved in microgrid planning, installation, operation in a interoperable and interconnectable fashion.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2014

Using ISERV and Commercial Satellite Imagery to Assess and Monitor Recovery Efforts in Urban Damaged Areas

NASA's Short-term Prediction, Research, and Transition (SPoRT) Center uses a wide array of satellites to monitor and assess the impacts of natural disasters, with support from NASA's Applied Sciences Program. One of the newest sensors SPoRT is utilizing in these activities is the International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. ISERV provides a unique view of the areas impacted and will play a big role in monitoring the recovery these areas. High‐resolution commercial satellite data is also used to monitor urban areas that have been impacted by natural disasters. SPoRT is developing techniques to measure the extent of these disasters and to monitor recovery. Several of these techniques include semi‐automatic feature detection and change as well as developing an experimental damage assessment based upon the visible damage observed by the satellites. Furthermore, throughout these activities SPoRT hopes to provide additional data to the NOAA National Weather Service Damage Assessment Toolkit, which will help to supplement those activities being performed in the field.

Bell, Jordan R.↗
NASA NTRS2024

SupportU: Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused

Global warming, challenging economic conditions, the opioid epidemic, and other widespread problems, have impacted people globally, particularly over the past several years. Preventable diseases like the common cold and the effects of heat stroke have become increasingly prevalent due to these issues. It is estimated that 150 million people of the world’s population are unhoused globally, with many dwelling in unsafe and unsanitary conditions while lacking access to basic hygienic items and other essentials. Unsanitary conditions coupled with this lack of access exacerbates and prolongs health problems and harms quality of life. Traditional methods of aid, such as homeless shelters and meal programs, face numerous challenges such as having limited reach and resources. To address these problems, the Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused (SUPPORT U) utilizes Uncrewed Aircraft Systems (UAS) to deliver resources to the unhoused and those in need of basic aid, prior to and during extreme temperature conditions, and after natural disasters in rural, suburban, and urban areas. The UA is envisioned to be an autonomous aircraft capable of efficiently distributing essential supplies, including blankets, water, food, and medicine. The UAS fleet relies on advanced navigation and communication technologies to accurately identify unhoused people and efficiently and safely distribute materials to them. This will be done through a machine learning algorithm. By focusing on identified “homeless clusters”, places where unhoused individuals are concentrated, the UAS network increases access to critical resources, thereby helping to mitigate some of the external risks to the health of unhoused individuals. The UA can also be used during crises, such as by transporting supplies to medical tents that are stationed in difficult-to-reach areas suffering from natural disasters.

Samuel Beard↗
NASA NTRS2024

Downscaled and Bias-Adjusted Climate Projections for Afghanistan

Climate change is already having devastating impacts on human communities and natural landscapes, from increasing severity and frequency of natural disasters to drought and desertification that degrade both natural ecosystems and human livelihoods. However, the impacts of climate change are not evenly distributed across the world—some places are at far greater risk than others. These highly vulnerable places should be a higher priority for investments and interventions to help people and nature adapt to changing climatic conditions. Afghanistan is one of the most at-risk countries from climate change. Within the country, the river basins are particularly sensitive as climate change will dramatically alter their water regimes upon which ecosystems and a vast proportion of the Afghan population and millions of people in neighbouring countries rely. As part of an EU-funded project implemented by the Wildlife Conservation Society (WCS), WCS conducted a vulnerability assessment for the Amu Darya River Basin that drains c. 14% of Afghanistan’s land area and is critically important for supporting both people and sensitive biodiversity (Elsen et al., 2023). Central to the vulnerability assessment was the development of downscaled and bias-adjusted climate projections, produced by the Center for Climate Systems Research (CCSR)1. The climate projections were produced at a much higher resolution (1 km2) than were otherwise available and were tailored to the local environment.

climate projections↗
NASA NTRS1976

Remote sensing utility in a disaster struck urban environment

Six major public health areas which might be affected by a natural disaster were identified. The functions and tasks associated with each area following a disaster, potential ways remote sensing could aid these functions, and the baseline data which would expedite problem solving associated with these functions are discussed.

Rush, M.↗
NASA NTRSDate not supplied

Informing New Concepts for UAS and Autonomous System Safety Management using Disaster Management and First Responder Scenarios

As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.

In Time Aviation Safety Management System↗