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At least 73 records · Page 4

Aerial thermography for energy conservation

Thermal infrared scanning from an aircraft is a convenient and commercially available means for determining relative rates of energy loss from building roofs. The need to conserve energy as fuel costs makes the mass survey capability of aerial thermography an attractive adjunct to community energy awareness programs. Background information on principles of aerial thermography is presented. Thermal infrared scanning systems, flight and environmental requirements for data acquisition, preparation of thermographs for display, major users and suppliers of thermography, and suggested specifications for obtaining aerial scanning services were reviewed.

Jack, J. R.↗

Supporting Hazard Analysis for Wildfire Response Using fmdtools and MIKA

The System Wide Safety (SWS) Safety Demonstrator (SD) Series drives development of an increasingly capable In-Time Aviation Safety Management System (IASMS) focusing on humanitarian applications, starting with wildfire response (SD-1). The goals of this report are to (1) provide an early hazard analysis and mitigation evaluation of wildfire response to support these efforts and (2) provide a demonstration of capabilities of the Fault Model Design Tools (fmdtools) and Manager for Intelligent Knowledge Access (MIKA) tools. fmdtools provides a modeling, simulation, and resiliency analysis framework in which a wildfire response model, the System Modeling and Analysis of Resiliency in Scalable Traffic Management for Emergency Response Operations (SMARt-STEReO), is built. MIKA is an intelligent knowledge manager with several capabilities, including assisting in hazard analysis by extracting and analyzing hazards from historical incident reports. The following topics are covered in the report: Understanding Wildfire Hazard Dynamics. We provide a description and simulated examples of how hazards occur in the SMARt-STEReO model of wildfire response and their effect on its outcome. This provides a common mental model and focuses the analysis presented in the remainder of the report. Wildfire Hazard Identification. MIKA identifies wildfire hazards from three relevant datasets: the ICS-209-PLUS, SAFECOM, and SAFENET. Hazards are manually organized into a taxonomy and MIKA analyzes each hazard’s effects, likelihood, severity, and risk. Evaluating Mitigation Strategies. The SMARt-STEReO wildfire response model built in fmdtools evaluates a subset of identified hazards. Specifically, we simulate the effect of communications faults and equipment faults on operator safety, the effect of changing winds and flammability, and a scenario with multiple ignition points and heavy smoke. Tool Limitations and Usage Considerations. We provide a discussion of appropriate tool use cases as well as limitations and considerations for usage. The tool findings are used to synthesize recommendations for wildfire response operations, which can be captured as part of an IASMS. Key recommendations are as follows: Hazards are identified from a broad spectrum of sources including aircraft subsystems, operational sources, and ground crew operations. Highest risk operational environment hazards identified are Evacuations. The highest risk manned aerial operations hazard categorized is Jumper Operations Mishap. Ground crew hazards that are highest risk are Burns, Cargo Operations Overhead, Dehydration, Entrapment, Falling Objects, Heart Attacks, Heat Exhaustion, Inadequate Training or Certification, Vehicle Breakdown, and Vehicle Collision. Modelled containment failures arise from a mismatch between the difficulty of the firefighting scenario and the capacity (e.g., speed, effectiveness, awareness) of the response. In firefighting scenarios where containment is possible (e.g., because the fire does not spread too quickly), these mismatches can occur because of a change in environmental conditions (e.g., wind, flammability, etc) or because of planning, equipment, or communications faults. Improvements to communications increase the capacity of the firefighting response by reducing the time needed to respond to the fire. While surveillance does not increase this capacity by itself, it increases operator safety by increasing state awareness, enabling firefighters to evade approaching fires. Increasing both has a synergistic effect. In general, these performance and resilience increases generalize over fault scenarios as well as unforeseen changes to circumstances (i.e., wind, aridity, etc.). However, these improvements need to be designed so as not to make the system prone to persistent large-scale communications outages, which can reduce performance.

Hazard analysis↗

Spatial Analysis of Environmental Factors Related to Lyme Disease in Alabama by Means of NASA Earth Observation Systems

This slide presentation reviews the epidemiology of Lyme Disease that accounts for more than 95% or vector borne diseases in the United States. The history, symptoms and the life cycle of the tick, the transmitting agent of Lyme Disease, a map that shows the cases reported to the CDC between1990 and 2006 and the number of cases in Alabama by year from 1986 to 2007. A NASA project is described, the goals of which are to (1) Demonstrate the presence of the chain of infection of Lyme disease in Alabama (2) Identify areas with environmental factors that support tick population using NASA Earth Observation Systems data in selected areas of Alabama and (3) Increase community awareness of Lyme disease and recommend primary and secondary prevention strategies. The remote sensing methods included: Analyzed Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and DigitalGlobe Quickbird satellite imagery from summer months and Performed image analyses in ER Mapper 7.1. Views from the ASTER and Quickbird land cover are shown, the Normalized Difference Vegetation Index (NDVI) algorithm was applied to all ASTER and Quickbird imagery. The use of the images to obtain the level of soil moisture is reviewed, and this analysis was used along with the NDVI, was used to identify the areas that support the tick population.

Renneboog, Nathan↗

Summary of Session Activities: Coordination of Environmental Education Projects

In this session, we address four fundamental questions related to environmental fields with emphasis on education. These are: What are the goals, objectives, and practical opportunities for coordinating our projects? How can we improve awareness of, interest in, access to, and support the products of our work? How can we build relationships between projects for scientific, educational, technical, and programmatic benefit? How can we evaluate the effectiveness of coordination efforts. In this working session, we produced answers to these questions and proposed a structure for future collaboration.

Keeler, Michael↗

Radiation-Hardened Electronics for the Space Environment

RHESE covers a broad range of technology areas and products. - Radiation Hardened Electronics - High Performance Processing - Reconfigurable Computing - Radiation Environmental Effects Modeling - Low Temperature Radiation Hardened Electronics. RHESE has aligned with currently defined customer needs. RHESE is leveraging/advancing SOA space electronics, not duplicating. - Awareness of radiation-related activities through out government and industry allow advancement rather than duplication of capabilities.

Keys, Andrew S.↗

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

The NASA Short ]term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real ]time configuration of the NASA Land Information System (LIS) with the Noah land surface model (LSM). Output from the SPoRT ]LIS run is used to initialize land surface variables for local modeling applications at select National Weather Service (NWS) partner offices, and can be displayed in decision support systems for situational awareness and drought monitoring. The SPoRT ]LIS is run over a domain covering the southern and eastern United States, fully nested within the National Centers for Environmental Prediction Stage IV precipitation analysis grid, which provides precipitation forcing to the offline LIS ]Noah runs. The SPoRT Center seeks to expand the real ]time LIS domain to the entire Continental U.S. (CONUS); however, geographical limitations with the Stage IV analysis product have inhibited this expansion. Therefore, a goal of this study is to test alternative precipitation forcing datasets that can enable the LIS expansion by improving upon the current geographical limitations of the Stage IV product. The four precipitation forcing datasets that are inter ]compared on a 4 ]km resolution CONUS domain include the Stage IV, an experimental GOES quantitative precipitation estimate (QPE) from NESDIS/STAR, the National Mosaic and QPE (NMQ) product from the National Severe Storms Laboratory, and the North American Land Data Assimilation System phase 2 (NLDAS ]2) analyses. The NLDAS ]2 dataset is used as the control run, with each of the other three datasets considered experimental runs compared against the control. The regional strengths, weaknesses, and biases of each precipitation analysis are identified relative to the NLDAS ]2 control in terms of accumulated precipitation pattern and amount, and the impacts on the subsequent LSM spin ]up simulations. The ultimate goal is to identify an alternative precipitation forcing dataset that can best support an expansion of the real ]time SPoRT ]LIS to a domain covering the entire CONUS.

Case, Jonathan L.↗

Scan angle dependence of radiance recorded by the NOAA-AVHRR

NOAA-AVHRR data is being used to monitor global vegetation type and condition and to study various environmental factors in addition to performance of meteorological functions. The AVHRR instrument has + or - 54 deg as maximum scan angle limits and it is necessary to be aware of the effects of sun-target-sensor geometry at extreme scan angles to be able to properly interpret the satellite images. In order to interpret the images for vegetation type and condition analysis, it is necessary to calibrate back to the nadir view position. Both simulation studies and empirical investigations with digital scanner data have been performed in order to sufficiently understand the effects of scan angle and sun angle, as well as the effects of atmospheric scattering, to eventually perform adequate calibrations. Not surprisingly, the effects are large and studies are continuing to provide improved calibrations.

Duggin, M. J.↗

Health and Safety Effects of Airborne Soil Dust in the Americas and Beyond

Risks associated with dust hazards are often underappreciated, a gap between the knowledge pool and public awareness that can be costly for impacted communities. This study reviews the emission sources and chemical, physical, and biological characteristics of airborne soil particles (dust) and their effects on human and environmental health and safety in the Pan-American region. American dust originates from both local sources (western United States, northern Mexico, Peru, Bolivia, Chile, and Argentina) and long-range transport from Africa and Asia. Dust properties, as well as the trends and interactions with criteria air pollutants, are summarized. Human exposure to dust is associated with adverse health effects, including asthma, allergies, fungal infections, and premature death. In the Americas, a well-documented and striking effect of soil dust is its association with Coccidioidomycosis, commonly known as Valley fever, an infection caused by inhalation of soil-dwelling fungi unique to this region. Besides human health, dust affects environmental health through nutrients that increase phytoplankton biomass, contaminants that diminish water supply and affect food (crops/fruits/vegetables and ready-to-eat meat), spread crop and marine pathogens, cause Valley fever among domestic and wild animals, transport heavy metals, radionuclides and microplastics, and reduce solar and wind power generation. Dust is also a safety hazard to road transportation and aviation, in the southwestern US where blowing dust is one of the deadliest weather hazards. To mitigate the harmful effects, coordinated regional and international efforts are needed to enhance dust observations and prediction capabilities, soil conservation measures, and Valley fever and other disease surveillance.

health↗

BIOME: A browser-aware search and order system

The Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC), which is associated with NASA's Earth Observing System Data and Information System (EOSDIS), provides access to a large number of tabular and imagery datasets used in ecological and environmental research. Because of its large and diverse data holdings, the challenge for the ORNL DAAC is to help users find data of interest from the hundreds of thousands of files available at the DAAC without overwhelming them. Therefore, the ORNL DAAC developed the Biogeochemical Information Ordering Management Environment (BIOME), a search and order system for the World Wide Web (WWW). The WWW provides a new vehicle that allows a wide range of users access to the data. This paper describes the specialized attributes incorporated into BIOME that allow researchers easy access to an otherwise bewildering array of data products.

Grubb, Jon W.↗

Investigating the Impacts of Land Use Change on Urban Heat and Vulnerability in Cali, Columbia

The urban heat island effect (UHI) is an environmental phenomenon where cities experience higher temperatures than rural areas due to increased pavement and decreased cooling from vegetation. Approximately 76% of people in Colombia live in urban areas, and the city of Santiago de Cali is facing UHI challenges exacerbated by land use change. Wetlands and forests formerly surrounded the city but were replaced by development and agriculture. The Colombian municipal government agency Departamento Administrativo de Gestión del Medio Ambiente and the community organization Fundacion Dinamizadores Ambientales partnered with NASA DEVELOP to evaluate communities in Cali most vulnerable to urban heat. This project illustrated the utility of using NASA Earth observations to evaluate the relationship between land use, temperature, and social factors in Cali, Colombia between 2013 and 2023. The team used Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), and Landsat 9 OLI-2/TIRS-2 to generate land surface temperature (LST), normalized difference vegetation index (NDVI), and albedo maps in Google Earth Engine. Heavy cloud cover limited the accuracy of the LST but incorporating up to three satellites for a median image reduced potential errors. Through further analysis in ArcGIS Pro, the team classified land use change using a deep learning model and found that LST was significantly higher in urban areas than in wetlands or forests. Using R studio, the team ran a principal component analysis to determine which social factors had the strongest correlation with LST. The team found that health care and green space access were negatively correlated, and Afro-Colombian ethnicity was positively correlated with LST. With awareness of the most impacted and vulnerable regions, the partner organizations can work to prioritize green space establishment in those areas to reduce the impacts of urban heat. Addressing the urban heat island effect will reduce environmental justice concerns within the city and improve overall health, air, and water quality for those who live there.

Brenna Bruffey↗

Beyond Fair: Engagement, Data Usability, and Open Community Productivity through the NASA Open Science Data Repository

The FAIR principle (findable, accessible, interoperable, and reusable) governs the storage and sharing of NASA space biology and health data[1]. These guiding principles maximize reuse of data and the reproducibility of scientific findings. The NASA Open Science Data Repository (OSDR; an expansion of NASA GeneLab) was built on the FAIR principles and houses over 500 studies and close to 1000 datasets from decades of space life sciences experiments. OSDR embodies the FAIR principles through data governance that includes mediated, embargoed, and fully open access data. The FAIR data governance principles were recently proposed to be expanded to encompass a FAIREST framework for assessing research data repositories (FAIR + Engagement, Social connections, and Trust)[2]. FAIREST emphasizes the importance of data repositories engaging with the scientific community and gaining the trust of researchers regarding data quality. Trust also refers to the TRUST principles developed for assessment of digital repositories: Transparency, Responsibility, User Focus, Sustainability, Technology[3]. We present the “Open Science for Life in Space” Analysis Working Groups (AWGs) as evidence regarding the power of engagement, social connections, and trust which has enhanced OSDR’s capabilities and productivity. AWG members engage in two main activities. One, members provide feedback on OSDR scientific standards for data ingestion, curation, and reuse (study, subject and assay metadata; processing pipelines; dataset formats and uniformed structures for machine-readability). Two, AWG members collaborate to mine-reuse OSDR data to conduct scientific analysis. With nearly 800 active members, the AWGs have resulted in 32 publications re-using OSDR data and contributed many papers in two major special issues in Cell (2020) and Nature (2024). AWGs also serve as networking groups, facilitate social connections between researchers at all levels of experience, and also have a social online ‘Forum’ used to keep members informed on projects and opportunities. This community-centric, productive, and trustworthy data culture has resulted in a broader effect with international space agencies, academics, and the commercial space sector wanting to submit their data to OSDR. Ten studies of Inspiration 4 data were recently publicly released by OSDR, as were some JAXA human data. Coming up soon in OSDR are data submissions from the European Space Agency, Virgin Galactic PIs, and SpaceX Polaris Dawn. A major benefit of OSDR is the array of standardized and uniformly formatted data (which was developed through AWG member consensus), from which visualization tools, analysis tools, and machine learning models can be built or trained. This talk will cover the Multi-Study Visualization Tool, the Environmental Data Application, RadLab, and a UCSF-NSF funded knowledge graph biomedical health discovery tool ‘SPOKE’ currently being integrated with OSDR. OSDR also provides training programs in bioinformatics and machine learning to improve the scientific community’s awareness of data availability and to boost their ability to perform data analysis. The increasing engagement of the scientific community and the public with technologies powered by artificial intelligence (AI) heightens the need for data analysis to be transparent. The AI for Life in Space initiative leverages the data products provided in OSDR to train AI models, with an emphasis on explainable and trustworthy AI, which would not be possible without FAIR data and metadata. Overall, here we will demonstrate the importance for NASA life sciences data repositories to adhere to the FAIREST framework, by providing examples and success stories from different aspects of OSDR.

data↗

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Case, Jonathan L.↗

NASA Kennedy Space Center: Contributions to Sea Turtle Science and Conservation

The National Aeronautics and Space Administration (NASA) is a United States (US) federal agency that oversees US space exploration and aeronautical research. NASA's primary launch site, Kennedy Space Center (KSC) is located along the east coast of Florida, on Cape Canaveral and the western Atlantic Ocean. The natural environment within KSC's large land boundaries, not only functions as an extensive safety buffer-area, it performs simultaneously as a wildlife refuge and a national seashore. In the early 1960s, NASA was developing KSC for rocket launches and the US was establishing an awareness of, and commitment to protecting the environment. The US began creating regulations that required the consideration of the environment when taking action on federal land or with federal funds. The timing of the US Endangered Species Act (1973), the US National Environmental Policy Act (1972), coincided with the planning and implementation of the US Space Shuttle Program. This resulted in the first efforts to evaluate the impacts of space launch operation operations on waterways, air quality, habitats, and wildlife. The first KSC fauna and flora baseline studies were predominantly performed by University of Central Florida (then Florida Technological University). Numerous species of relative importance were observed and sea turtles were receiving regulatory review and protection as surveys by Dr. L Ehrhart (UCF) from 1973-1978 described turtles nesting along the KSC beaches and foraging in the KSC lagoon systems. These data were used in the first NASA Environmental Impact Statement for the Space Transportation System (shuttle program) in 1980. In 1982, NASA began a long term ecological monitoring program with contracted scientists on site. This included efforts to track sea turtle status and trends at KSC and maintain protective measures for these species. Many studies and collaborations have occurred on KSC over these last 45 years with agencies (USFWS, NOAA, NAVY), students, and universities (UCF, University of Toronto, Texas A&M, UF). This presentation will review the various studies and collaborations on sea turtles at KSC that include: nest distributions and success, stranding network development, aerial survey testing for nest counts, predator control assessments, the earliest baseline blood chemistry health determinations on nesting females, stress hormones in nesting females, multi-year study of hatchling sex ratios, genetics, species composition, abundance and distribution of in-water juveniles, turtle cold stun response, exterior lighting impacts and control, and satellite tag tracking of post-nesting turtles in the vicinity of near shore shoals and sand mining sites. Through these studies, monitoring, and recommendations, KSC has provided excellent stewardship and protection of the local environment. While conducting its space program mission, KSC has also made significant contributions of information for agencies charged with the conservation and management of these species

Provancha, Jane A.↗

Fatigue and associated performance decrements in air transport operations

A study of safety reports was conducted to examine the hypothesis that fatigue and associated performance decrements occur in air transport operations, and that these are associated with some combination of factors: circadian desynchronosis, duty time; pre-duty activity; sleep; work scheduling; workload; and environmental deprivation. The findings are based on a selected sample of reported incidents in which the reporter associated fatigue with the occurrence. In comparing the fatigue reports with a control set, significant performance decrements were found to exist related to time-of-day, awareness and attention to duty, less significantly, final phases of flights. The majority of the fatigue incidents involved such unsafe events as altitude deviations, takeoffs and landing without clearance, and the like. Considerations of duty and sleep are the major factors in the reported fatigue conditions.

Lyman, E. G.↗

Expansion of the Real-Time SPoRT-Land Information System for NOAA/National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014.This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations.

Case, Jonathan L↗