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NASA NTRS2022

Chile Disasters: Automating Wildfire Risk and Occurrence Mapping in Google Earth Engine to Improve Wildfire Detection and Response Time Efforts

Wildfires in Chile in the last decade were the worst on record, destroying homes and livelihoods, polluting the air, and displacing whole towns. To predict locations where wildfires were likely to start, the Corporación Nacional Forestal (CONAF) created a wildfire risk model within ArcGIS Pro and Google Earth Engine (GEE) that utilized the NOAA Global Forecast System (GFS) and the NASA Shuttle Radar Topography Mission (STRM) 90-meter datasets. The previous CONAF model was very resource-heavy and time-intensive to run. NASA DEVELOP, in partnership with CONAF, automated the previous model and transferred it fully into GEE where all Earth observation datasets could be used without downloading. The new model substantially reduced the runtime. The final model was used to create a near real-time wildfire monitoring application as well as fire severity maps. The end products will be used by CONAF for wildfire prediction and management to prevent more destruction in the future.

Maria De Los Santos↗

NASA NTRS2022

Chile Disasters: Automating Wildfire Risk and Occurrence Mapping in Google Earth Engine to Improve Wildfire Detection and Response Time Efforts

The purpose of this document is to outline the steps the NASA DEVELOP team took to complete wildfire risk and occurrence mapping for our partners at Chile’s Corporación Nacional Forestal and the Embassy of Chile in the United States. The instructions are intended for individuals already knowledgeable in coding to recreate our methodology.

Maria De Los Santos↗

NASA NTRSDate not supplied

Developing an Unmanned Aircraft System Pilot (UASP-kit) for Wildland Fire UAS Operators

The use of unmanned aircraft systems (UAS) to support disaster management is becoming more widespread. Uninhibited by many of the operational constraints imposed on crewed aircraft, UAS have the potential to augment the aerial response in a number of ways, including supporting situation awareness, thereby accelerating disaster management efforts. The intent of the Scalable Traffic management for Emergency Response Operations (STEReO) activity is to build an ecosystem that will allow small UAS (sUAS) operations to fly safely in the airspace during disaster management events. The first step toward this goal is to develop a small, single-user tool (the UASP-kit) that will enhance an sUAS pilot’s situation awareness of the airspace. User needs for the functions and features of this tool were collected during a walkthrough over multiple days with subject matter experts from the US Forest Service. A prototype of the UASP-kit was then taken on an extended demonstration to multiple users, who were able to interact with it. User feedback was largely positive and users discussed the information they needed to support situation awareness in context. The demonstration also highlighted features that were unintuitive to use, and functions that need to be modified to make the kit more user-friendly and robust.

STEReO↗

NASA NTRSDate not supplied

Developing an Unmanned Aircraft System Pilot Kit (UASP-kit) for Wildland Fire UAS Operators

STEReO↗

DOE OSTI2020

Next-generation geospatial-temporal information technologies for disaster management

Traditional geographic information systems (GIS) have been disrupted by the emergence of Big Data in the form of geo-coded raster, vector, and time-series Internet-of-Things data. This article discusses the application of new scalable technologies that go far beyond relational databases and file-based storage on spinning disk or tape to incorporate both storage and processing data in the same platform. The roles of the Apache Hadoop Distributed File Systems and NoSQL key-value stores such as the Apache Hbase are discussed, along with indexing schemes that optimally support geospatial-temporal use. Here, we highlight how this new approach can rapidly search multiple GIS data layers to obtain insights in the context of early warning, impact evaluation, response, and recovery to earthquake and wildfire disasters.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2024

Search Technology for Optimal Rescue Missions (STORM)

Natural disasters, such as earthquakes, hurricanes, and wildfires are responsible for the deaths of 60,000 to 90,000 people per year. Today, search and rescue (SAR) operations heavily rely on humans to find and deliver life-saving supplies to those affected by these disasters. However, these operations have limits in visibility, navigation, communication systems, and data availability in the area affected, as well as endangering the SAR personnel. Search Technology for Optimal Rescue Missions (STORM) discusses a new system for SAR teams using autonomous drones able to find and deliver supplies to people, without risking more lives in the process. The concept includes the use of two drone types, STORM Search and STORM Rescue, which will survey and locate survivors and be able to drop equipment to the survivors identified, respectively. These two types of drones were optimized in drone design and durability (such as the use of dihedral wings and a toroidal propeller), detection and navigation systems (sturdy thermal and Light Detection and Ranging [LiDAR] cameras), automation and system design (Machine Learning and Computer Vision), server-drone communication (Meshnets), weight, and cost. Once implemented, the STORM concept is expected to improve, ease, and speed up SAR operations, and most important of all, rescue lives that would have never been currently possible to find.

Astha Ingole↗

DOE OSTI2020

Multiperiod Distribution System Restoration With Routing Repair Crews, Mobile Electric Vehicles, and Soft-Open-Point Networked Microgrids

This paper proposes a distribution system restoration model which is in response to multiple outages caused by natural disasters. The proposed restoration model includes the coordination of routing repair crews (RRCs), mobile batterycarried vehicles (MBCVs), and networked microgrids (NMGs) formed by soft open points (SOPs). The travel and repair time constraints are modeled for each RRC; travel path and charging strategy are modeled for each MBCV; and the network reconfiguration is developed considering the optimal operation of SOP-based NMGs. Furthermore, the proposed model is presented as a mixedinteger linear program which is solved by an auxiliary induce function based algorithm to reduce the computational complexity. The modified IEEE 33-bus and 69-bus distribution systems are tested with multiple outages. The presented results demonstrate the effectiveness of the proposed model

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Summary of Factory Fueling and Testing Risks to Support the Transformation of Regulatory Requirements for Microreactors

Microreactors have the potential to open new markets and applications for nuclear energy. New manufacturing and operational regimes, such as factory fueling and testing prior to site installation, are being proposed to meet these new markets. The radiological hazards associated with traditional commercial power reactors are not the same as the hazards of a reactor being constructed in a factory. Currently, a reactor operating license specified under 10 CFR Part 50, Part 52, or (in the near future) Part 53 is required prior to loading fuel in the reactor. This is logical for plants that are immediately to begin full-power operations soon after fuel loading. However, for microreactors, this may not be the case. Some deployment concepts may stage reactors as “ready to go” in a factory prior to site installation and startup. This approach is being considered in the case of diesel generator replacements, mobile or roaming mining operations, and emergency response situations, such as after a major disaster event. Therefore, it is necessary to evaluate hazards assuming low power operation for a short irradiation time. This report investigates the primary hazards unique to microreactors associated with low power reactor and physics tests necessary to confirm core safety assumptions, neutronic and core design performance parameters, and other assumptions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2015

Intelligent Observation Strategies for Geosynchronous Remote Sensing for Natural Hazards

Geosynchronous satellites offer a unique perspective for monitoring environmental factors important to understanding natural hazards and supporting the disasters management life cycle, namely forecast, detection, response, recovery and mitigation. In the NASA decadal survey for Earth science, the GEO-CAPE mission was proposed to address coastal and air pollution events in geosynchronous orbit, complementing similar initiatives in Asia by the South Koreans and by ESA in Europe, thereby covering the northern hemisphere. In addition to analyzing the challenges of identifying instrument capabilities to meet the science requirements, and the implications of hosting the instrument payloads on commercial geosynchronous satellites, the GEO-CAPE mission design team conducted a short study to explore strategies to optimize the science return for the coastal imaging instrument. The study focused on intelligent scheduling strategies that took into account cloud avoidance techniques as well as onboard processing methods to reduce the data storage and transmission loads. This paper expands the findings of that study to address the use of intelligent scheduling techniques and near-real time data product acquisition of both the coastal water and air pollution events. The topics include the use of onboard processing to refine and execute schedules, to detect cloud contamination in observations, and to reduce data handling operations. Analysis of state of the art flight computing capabilities will be presented, along with an assessment of cloud detection algorithms and their performance characteristics. Tools developed to illustrate operational concepts will be described, including their applicability to environmental monitoring domains with an eye to the future. In the geostationary configuration, the payload becomes a networked thing with enough connectivity to exchange data seamlessly with users. This allows the full field of view to be sensed at very high rate under the control of ground infrastructure, resulting in improved efficiencies, accuracy and science benefits. Hence a remote sensing payload and its data may become one of millions of connected objects in the emerging Internet of Things (IoT), and be as easily accessible by a users smart phone as any other smart appliance.

0↗

NASA NTRSDate not supplied

Using Landsat 8 Satellite Imagery to Analyze Biogeochemical Constituents in the Waters of the San Francisco Bay Area and Beyond

The ocean's coastal zones play a key role in our planet's health and mitigate the adverse effects of climate change. Building on the success of NASA satellite imagery in mapping land cover changes around the globe in response to climate change, deforestation, and natural disasters, I have worked to determine how aquatic reflectance images from the Landsat 8 sensor could be correlated with biogeochemical constituents within the waters of the San Francisco Bay Area and California coastline. By analyzing Landsat 8 satellite imagery from the years 2013-2020 in collaboration with data from the United States Geological Survey (USGS), San Francisco Estuary Institute (SFEI), and universities involved with the Harmful Algal Bloom Monitoring and Alert Program (HABMAP), I investigated which areas of the San Francisco Bay and California coastline demonstrated significant correlations with values extracted from the satellite imagery. Using a Chlorophyll Index (CI) ratio calculated from two Landsat 8 satellite reflectance bands, it was found that there is a positive correlation between the CI and calculated oxygen, suspended particulate matter, and silicate from several USGS sampling points. In contrast, there is a significant negative correlation between the CI and salinity, nitrite, and phosphate at those same locations. Moreover, large suspected harmful algal blooms (HABs) along the California coastline seen in the Landsat 8 imagery were corroborated with HAB data from various institutions. Understanding the effectiveness of Landsat 8 aquatic reflectance images will allow scientists to predict HABs and other nutrient cycling that may be harmful to aquatic ecosystems around the world.

Landsat↗

NASA NTRS2010

NASA DEVELOP Students Rev Up Response to Gulf Oil Spill

After the April 20th explosion aboard the Deepwater Horizon drilling rig in the Gulf of Mexico, the world witnessed one of the worst oil spill catastrophes in global history. In an effort to mitigate the disaster, the U.S. government moved quickly to establish a unified command for responding to the spill. Some of the command's most immediate needs were to track the movement of the surface oil slick, establish a baseline measurement of pre-oil coastal ecosystem conditions, and assess potential air quality and water hazards related to the spill. To help address these needs and assist the Federal response to the disaster, NASA deployed several of its airborne and satellite research sensors to collect an unprecedented amount of remotely-sensed data over the Gulf of Mexico region. Although some of these data were shared with the public via the media, much of the NASA data on the disaster was not well known to the Gulf Coast community. The need existed to inform the general public about these datasets and help improve understanding about how NASA's science research was contributing to oil spill response and recovery. With its extensive experience conducting community-oriented remote sensing projects and close ties to organizations around Gulf of Mexico, the NASA DEVELOP National Program stood in a unique position to meet this need.

Jones, Jason B.↗

NASA NTRS2011

Onboard Radar Processing Development for Rapid Response Applications

We are developing onboard processor (OBP) technology to streamline data acquisition on-demand and explore the potential of the L-band SAR instrument onboard the proposed DESDynI mission and UAVSAR for rapid response applications. The technology would enable the observation and use of surface change data over rapidly evolving natural hazards, both as an aid to scientific understanding and to provide timely data to agencies responsible for the management and mitigation of natural disasters. We are adapting complex science algorithms for surface water extent to detect flooding, snow/water/ice classification to assist in transportation/ shipping forecasts, and repeat-pass change detection to detect disturbances. We are near completion of the development of a custom FPGA board to meet the specific memory and processing needs of L-band SAR processor algorithms and high speed interfaces to reformat and route raw radar data to/from the FPGA processor board. We have also developed a high fidelity Matlab model of the SAR processor that is modularized and parameterized for ease to prototype various SAR processor algorithms targeted for the FPGA. We will be testing the OBP and rapid response algorithms with UAVSAR data to determine the fidelity of the products.

dual polarized data↗

DOE OSTI2020

Defense & Disaster Deployable Turbine Fact Sheet

The U.S. Department of Energy’s (DOE’s) Defense and Disaster Deployable Turbine (D3T) project is evaluating the market potential for rapidly deployable wind energy technologies. The D3T fact sheet outlines the work with military and wind industry stakeholders to develop deployable wind energy technologies that can meet the unique energy needs of defense operations and responses to humanitarian crises.

wind, defense, disaster, deployable, turbine, ener↗

DOE OSTI2024

Optimizing the location and configuration of disaster resilience hubs under transportation and electric power network failures

Natural disasters often result in failures of transportation network components and blackouts that imperil the wellbeing of vulnerable populations. In response to these events, resilience hubs have been proposed as a pre-disaster planning strategy to improve access to critical services. This paper introduces an optimization-based approach to locate and configure electric power-generating resilience hubs considering the possibility of failures in transportation and electric power systems. The model's objective is to identify hub locations and configurations that maximize transportation accessibility to the hubs and maximize the satisfaction of basic energy needs through hub-generated electric power. Besides a budget constraint, the model accounts for limits on the levels of hub energy generation vis-à-vis community energy demands, and on the transportation network distance of communities to hubs. Three heuristics are presented for the proposed planning problem. The first heuristic is a genetic algorithm (GA) with problem-specific solution generation procedures. The other two heuristics implement greedy search techniques. Numerical experiments were conducted, using data from rural Puerto Rico, to illustrate the application of the proposed model and heuristics, and examine their performance. In the numerical experiments, the GA heuristic found better solutions than the greedy heuristics. Additionally, design solutions consisting of spatially dispersed hubs with low energy generation capacity were better than solutions with spatially concentrated high-capacity hubs. Lastly, across a wide range of hub demand scenarios, only a small number of candidate hub locations consistently ranked among the best locations for establishing a hub.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2004

On-board processor for direct distribution of change detection data products

We are developing an on-board imagin radar data processor for repeat-pass change detection and hazards management. This is the enabling technology for NASA ESE to utilize imaging radars. This processor will enable the observation and use of surface deformation data over rapidly evolving natural hazards, both as an aid to scientific understanding ad to provide timely data to agencies responsible for the management and mitigation of natural disasters.

InSAR↗

NASA NTRS2019

UAVSAR real-time embedded GPU processor

Synthetic aperture radar (SAR) can provide high-resolution imagery regardless of cloud cover or lighting conditions. These qualities make SAR potentially well-suited for informing response efforts to natural and man-made disasters, but such applications require data products with minimal latency. To meet this challenge, we implemented a real-time SAR processor capable of producing 10 m imagery using an NVIDIA Jetson TX2 embedded GPU module. With its low mass (87 g module) and power consumption under 8 W, the system also holds promise for spaceborne applications.

Tung, Wayne↗

NASA NTRS2005

Water and Air Measures That Make 'PureSense'

Each day, we read about mounting global concerns regarding the ability to sustain supplies of clean water and to reduce air contamination. With water and air serving as life s most vital elements, it is important to know when these environmental necessities may be contaminated, in order to eliminate exposure immediately. The ability to respond requires an understanding of the conditions impacting safety and quality, from source to tap for water, and from outdoor to indoor environments for air. Unfortunately, the "time-to-know" is not immediate with many current technologies, which is a major problem, given the greater likelihood of risky situations in today s world. Accelerating alert and response times requires new tools, methods, and technologies. New solutions are needed to engage in more rapid detection, analysis, and response. This is the focus of a company called PureSense Environmental, Inc., which evolved out of a unique relationship with NASA. The need for real-time management and operations over the quality of water and air, and the urgency to provide new solutions, were reinforced by the events of September 11, 2001. This, and subsequent events, exposed many of the vulnerabilities facing the multiple agencies tasked with working in tandem to protect communities from harmful disaster. Much has been done since September 11 to accelerate responses to environmental contamination. Partnerships were forged across the public and private sectors to explore, test, and use new tools. Methods and technologies were adopted to move more astutely from proof-of-concept to working solutions.

Source record↗

NASA NTRS1991

National Aeronautics and Space Administration's (NASA) Automated Information Security Handbook

The NASA Automated Information Security Handbook provides NASA's overall approach to automated information systems security including discussions of such aspects as: program goals and objectives, assignment of responsibilities, risk assessment, foreign national access, contingency planning and disaster recovery, awareness training, procurement, certification, planning, and special considerations for microcomputers.

Roback, E.↗