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At least 181 records · Page 10

Defining A Modelling Language to Support Functional Hazard Assessment

Functional Hazard Assessment (FHA) is a key early-stage engineering process that supports the incorporation of safety in design by identifying the high-level functional hazards the system may encounter. While many FHA-like methodologies have been proposed in the design engineering literature, many of these methodologies have had difficulty becoming accepted industry practice. Industry standards, on the other hand, either provide little recommendation on how to represent the function of the system to perform FHA, or rely on readily-available models with little justification in design theory. This paper presents some of the problems with current modelling languages used for FHA which limit the scope, expressiveness, flexibility, and precision of the analysis, as well as desirable principles an FHA-supporting analysis language should embody. It further introduces the Functional Reasoning Design Language (FRDL), a formal modelling language for describing the functional behaviors of a system and their interactions which satisfies these principles. To demonstrate the use of this language, the modelling and hazard analysis of a disaster response drone is presented.

safety analysis↗

NAS Exploratory Concepts & Technologies (NExCT) Upper Class E Traffic Management (ETM) Collaborative Evaluation #1 (CE-1)

NASA, in partnership with AeroVironment and Aerostar, recently demonstrated a first-of-its-kind air traffic management concept that could pave the way for aircraft to safely operate at higher altitudes. This work seeks to open the door for increased internet coverage, improved disaster response, expanded scientific missions, and even supersonic flight. The concept is referred to as an Upper-Class E traffic management, or ETM. NASA and its partners have developed an ETM traffic management system that allows aircraft to autonomously share location and flight plans, enabling aircraft to stay safely separated. This concept was demonstrated during the recent traffic management simulation in the Airspace Operations Laboratory at Ames, data from multiple air vehicles was displayed across dozens of traffic control monitors and shared with partner computers off site. The study details and the initial results are presented at a regular, informal ETM industry meetings held virtually.

Upper Class E Traffic Management (ETM)↗

Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications

This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA’s Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models incorporate temporal and location embeddings for enhanced performance across various geospatial tasks. Through extensive benchmarking with GEOBench, the 600M version outperforms the previous Prithvi-EO model by 8% across a range of tasks. It also outperforms six other geospatial foundation models when benchmarked on remote sensing tasks from different domains and resolutions (i.e. from 0.1m to 15m). The results demonstrate the versatility of the model in both classical earth observation and high-resolution applications. Early involvement of end-users and subject matter experts (SMEs) are among the key factors that contributed to the project’s success. In particular, SME involvement allowed for constant feedback on model and dataset design, as well as successful customization for diverse SME-led applications in disaster response, land use and crop mapping, and ecosystem dynamics monitoring. Prithvi-EO-2.0 is available on Hugging Face and IBM terratorch, with additional resources on GitHub. The project exemplifies the Trusted Open Science approach embraced by all involved organizations.

Daniela Szwarcman↗

Severe droughts reduce river navigability and isolate communities in the Brazilian Amazon

The Amazon basin is experiencing severe droughts that are expected to worsen with climate change. Riverine communities are especially vulnerable to these extreme events. This study investigates the experiences of Brazilian Amazonian communities during droughts occurring from 2000-2020. We assess the distribution of settlements at risk of prolonged isolation during extreme low-water periods, along with impacts reported in digital news outlets. Using historic time series of river levels from 90 gauges, we look at how long droughts lasted in regions with reported impacts. Results indicate that the droughts in 2005, 2010, and 2016 were the most severe, with over an additional month of low water levels in those years. Such drought events routinely disrupt inland water transport and isolate local populations, limiting access to essential goods (food, fuel, medicine) and basic services (healthcare, education). Given this new reality, Amazon countries must develop long-term strategies for mitigation, adaptation, and disaster response.

Geography↗

Applications of Earth Remote Sensing in Response to Meteorological Disasters

NASA's Short-­‐term Predic1on Research and Transi1on (SPoRT) Center supports the transi1on of unique NASA and NOAA research activities to the operational weather forecasing community. Our primary partners are NOAA's National Weather Service, their Weather Forecast Offices (WFOs), and National Centers. These organizations predict natural hazards and also assist in the disaster assessment process, benefiting from remotely sensed data. In 2013, SPoRT continued to transition high resolution satellite imagery, derived products, and value-­‐added analysis to WFO partners and NASA's Applied Sciences Program.

Molthan, Andrew L.↗

USA Structures Phase 2 Technical Report

Spatially accurate data of critical infrastructures are essential to effective disaster preparedness, response, and recovery. Precise location and building outlines provide the most accurate data for characterizing impacts of hazards and effectively serve response, recovery, and mitigation efforts, as well as the people affected by the disaster. Since 2017, Oak Ridge National Laboratory (ORNL) has partnered with the Federal Emergency Management Agency (FEMA) to establish a comprehensive and open source national database of building footprints called USA Structures. Several key attributions have been added to the dataset to support rapid disaster response. In the most recent update to the dataset, ORNL developed two additional attributions to the structures, leveraging several authoritative data sources.

42 ENGINEERING↗

Applications of Satellite Remote Sensing for Response to and Recovery from Meteorological Disasters

Numerous on‐orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short‐term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth‐observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF‐5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat‐7 and Landsat‐8 imagery help to identify the damaged areas. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. This presentation will provide an overview of near real‐time data products developed for dissemination to SPoRT's partners in NOAA's National Weather Service, through collaboration with the USGS and other federal agencies. Specifically, it will focus on integration of various data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.

Molthan, Andrew I.↗

Applications of Satellite Remote Sensing for Response to and Recovery from Meteorological Disasters

Numerous on‐orbit satellites provide a wide range of spatial, spectral, and temporal resolutions supporting the use of their resulting imagery in assessments of disasters that are meteorological in nature. This presentation will provide an overview of recent use of Earth remote sensing by NASA's Short‐term Prediction Research and Transition (SPoRT) Center in response to disaster activities in 2012 and 2013, along with case studies supporting ongoing research and development. The SPoRT Center, with support from NASA's Applied Sciences Program, has explored a variety of new applications of Earth‐observing sensors to support disaster response. In May 2013, the SPoRT Center developed unique power outage composites representing the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF‐5 tornado that occurred on May 20. Subsequent ASTER, MODIS, Landsat‐7 and Landsat‐8 imagery help to identify the damaged areas. Higher resolution imagery of Moore, Oklahoma were provided by commercial satellites and the recently available International Space Station (ISS) SERVIR Environmental Research and Visualization System (ISERV) instrument. New techniques are being explored by the SPoRT team in order to better identify damage visible in high resolution imagery, and to monitor ongoing recovery for Moore, Oklahoma. This presentation will provide an overview of near real‐time data products developed for dissemination to SPoRT's partners in NOAA's National Weather Service, through collaboration with the USGS and other federal agencies. Specifically, it will focus on integration of various data sets within the NOAA National Weather Service Damage Assessment Toolkit, which allows meteorologists in the field to consult available satellite imagery while performing their damage assessment.

Molthan, Andrew L.↗

A framework to enhance disaster debris estimation with AI and aerial photogrammetry

This study addresses the critical need to enhance disaster preparedness and response, focusing on hurricane impact assessment and debris estimation. Accurate assessments in this context are critical for post-event search-and-rescue (SAR) operations and resource distribution. Recent computing advancements are revealing the potential of unmanned aerial vehicles (UAVs) and artificial intelligence (AI) technologies in collecting data and assisting with post-hurricane reconnaissance. However, the use of AI and UAV photogrammetry for accurate disaster impact analysis remains underexplored. To this end, this study proposes a damage and debris analysis framework harnessing reality capture through aerial imagery and photogrammetry. Within this framework, a region-based neural network is leveraged to detect debris locations in aerial imagery with favorable performance. In a testbed within the Beaumont-Port Arthur region, in Southeast Texas, this study performs 3D reality captures of the built environment. Since the accuracy of the 3D reality capture is of importance in research areas associated with time-sensitive disaster response, we further investigate the optimal 2D aerial imagery overlap ratio required to generate a sufficiently accurate 3D model for disaster impact analysis and debris volume estimation. Results indicate that, in the case of aerial imagery for infrastructure systems, a minimum of 60 % overlap is recommended for damage assessment and debris analysis. In contrast, for flat green areas, a minimum of 50 % overlap is adequate. Overall, for disaster response applications, our study reveals that an overlap ratio between 60 % and 70 % is optimal for achieving a balance between time efficiency and data quality in aerial data collection. Furthermore, these quantitative recommendations are crucial for enabling efficient disaster response efforts. Additionally, our study outcomes will improve disaster impact analysis and facilitating timely and effective response strategies.

Artificial intelligence↗

Future Roles for Autonomous Vertical Lift in Disaster Relief and Emergency Response

System analysis concepts are applied to the assessment of potential collaborative contributions of autonomous system and vertical lift (a.k.a. rotorcraft, VTOL, powered-lift, etc.) technologies to the important, and perhaps underemphasized, application domain of disaster relief and emergency response. In particular, an analytic framework is outlined whereby system design functional requirements for an application domain can be derived from defined societal good goals and objectives.

Young, Larry A.↗

Using NASA LANCE Near Real-Time Products for Disaster Risk Reduction

The NASA Earth Science Disasters Program handles requests from stakeholders and provides rapid response for Disaster Risk Reduction using Near Real-Time (NRT) products from NASA’s Land, Atmosphere NRT Capability for Earth Observing System (EOS) (LANCE). The combination of all available LANCE NRT satellite products provides global coverage at multiple times per day, which makes it possible to help users in different phases of the disaster’s life cycle. LANCE NRT fire and atmosphere products have been used to locate fires and high-temperature heat sources, and to assess the extent of air pollution. LANCE NRT global flood products and NASA’s Black Marble night-time light products have been used to monitor land cover and land use change over time in disaster impacted areas. Generated products and related information have been archived in NASA Disasters Mapping Portal for the use of stakeholders and end-users.

Tian Yao↗

Using NASA LANCE Near Real-Time Earth Observations for Disaster Risk Reduction

The NASA Earth Science Disasters Program handles requests from stakeholders and provides rapid response for Disaster Risk Reduction using Near Real-Time (NRT) products from NASA’s Land, Atmosphere NRT Capability for Earth Observing System (EOS) (LANCE). The combination of all available LANCE NRT satellite products provides global coverage at multiple times per day, which makes it possible to help users in different phases of the disaster’s life cycle. For wildfires and volcano eruption disasters, LANCE NRT fire and atmosphere products have been used to locate fires and high-temperature heat sources, and to assess the extent of air pollutions. Knowledge of the geographical position and direction of smokes, fires, lava flows provided critical information for disaster prediction and prevention. For hurricanes, tropical cyclones and earthquakes, LANCE global flood products and NASA’s Black Marble night-time light products have been used for monitoring land cover and land use change over time in disaster impacted areas. Users can use pre- and post-disaster maps to assess the extent of damage, and to make decisions for activities in reconstruction and recovery in infrastructure and health on the ground. LANCE NRT data are made available through the Earth data website and have been archived and visualized in NASA Disasters Mapping Portal, NASA LANCE Fire Information for Resource Management System (FIRMS) and NASA Worldview for the use of stakeholders.

Tian Yao↗