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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Lake Anna Water Resources: Using NASA Earth Observations to Identify Algal Event Risk Factors in Lake Anna and Help Inform Future Management Practices

Lake Anna is a man-made reservoir and popular recreation destination that spans over 13,000 acres-9,600 public and 3,400 private-in the Piedmont region of Virginia. The Lake has recently seen a rise in documented harmful algal blooms (HABs), which pose a variety of community and ecological concerns and are often exacerbated by anthropogenic factors, such as excess nutrient loads from agricultural runoff. NASA DEVELOP has partnered with the Virginia Department of Environmental Quality (DEQ) to help monitor cyanobacteria and nutrient pollution indicators across Lake Anna. The team utilized Earth observations (EO) and in situ ancillary data to identify and monitor algal bloom trends. The team used Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Sentinel-3 Ocean and Land Color Instrument (OLCI) to analyze water quality variables such as chlorophyll-a, turbidity, surface temperature, and cyanobacteria. Due to the lack of comprehensive in situ data and historic HAB event records, our ability to compare and validate EOs was limited. Additionally, deficient spatial resolutions, along with a geographically complicated shoreline, accentuated the spatial constraints we faced in our analysis. After examining EOs, our results indicated conditions conducive to the formation of HABs within the upper reaches of Lake Anna. Yet, spatially dependent limiting factors may have also influenced where these phenomena developed. When used in concert with existing in situ datasets, NASA EOs provide relevant stakeholders with more comprehensive analyses with which to engage in enhanced monitoring and watershed management.

cyanobacteria↗
NASA NTRS2024

Identifying Solar Wind and Other Volatiles in Space-Weathered Samples From Asteroid Bennu

On September 24, 2023, NASA’s Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission returned >70 g of material from asteroid Bennu to Earth. The Sample Return Capsule was opened at NASA Johnson Space Center (JSC), and a spillover sample was collected from the avionics deck to perform quick-look (QL) analyses. In addition to providing a reconnaissance investigation of its mineralogy, the sample was also examined for evidence of surface exposure on asteroid Bennu by identifying signatures of space weathering. Space weathering changes the morphology, microstructure, and chemistry of regolith on the surfaces of airless bodies. Driven by micrometeoroid bombardment and solar wind irradiation, our understanding of how space weathering modifies particles on the surfaces of carbonaceous asteroids is still developing. To bolster the interpretation of remote sensing data and to further address driving Hypothesis 10, we must investigate the nanoscale structural and chemical changes in returned samples from Bennu to understand how space weathering affects carbonaceous surface materials. Here we explore evidence for solar wind irradiation in QL samples from asteroid Bennu.

M S Thompson↗
NASA NTRS2024

Alaska Ecological Conservation: Using NASA Earth Observations to Identify Recent Changes in River Ice Phenology and Its Impacts on Caribou Migration

Each fall, caribou (Rangifer tarandus) in the Western Arctic Herd migrate hundreds of kilometers across northwestern Alaska to acquire seasonal resources and reach wintering grounds. Various rivers intersect migration paths, and caribou can only cross over open water or high-ice extents but are unable to cross rivers in stages of partial freezing. Recent temperature increases in Alaska can alter the timing and duration of ice formation periods, impeding migratory patterns. The Massachusetts NASA DEVELOP team partnered with the National Park Service in Alaska to detect river ice onset dates and formation periods using Landsat 8 Operational Land Imager and Landsat 9 Operational Land Imager-2, Sentinel-1 C-band Synthetic Aperture Radar and Sentinel-2A/B MultiSpectral Instrument imagery in Google Earth Engine. This feasibility analysis measured ice coverage using the Normalized Difference Infrared Index, Relative Difference River Ice, and Vertical-Vertical/Vertical-Horizontal backscatter values based on the spectral and surface characteristics of rivers. The team produced annual freezing timelines, time series plots, and maps at three river stretches to analyze river ice phenology changes. Radar imagery assessed ice coverage more accurately, while optical imagery better identified ice onset dates. Meanwhile indices were unable to robustly establish ice formation thresholds across the study period. These study results can help the National Park Service to better evaluate spatiotemporal migratory shifts and contextualize recent regional caribou declines.

river phenology↗
NASA NTRS2024

Heterogeneous Outgassing Regions Identified on Active Centaur 29P/Schwassmann–Wachmann 1

Centaurs are transitional objects between primitive trans-Neptunian objects and Jupiter-family comets. Their compositions and activities provide fundamental clues regarding the processes affecting the evolution of and interplay between these small bodies. Here we report observations of centaur 29P/Schwassmann–Wachmann 1 (29P) with the James Webb Space Telescope (JWST). We identified localized jets with heterogeneous compositions driving the outgassing activity. We employed the NIRSpec mapping spectrometer to study the fluorescence emissions of CO and obtain a definitive detection of CO 2 for this target. The exquisite sensitivity of the instrument also enabled carbon and oxygen isotopic signatures to be probed. Molecular maps reveal complex outgassing distributions, such as jets and anisotropic morphology, which indicate that 29P’s nucleus is dominated by active regions with heterogeneous compositions. These distributions could reflect that it has a bilobate structure with compositionally distinct components or that strong differential erosion takes place on the nucleus. As there are no missions currently planning to visit a centaur, these observations demonstrate JWST’s unique capabilities in characterizing these objects.

Sara Faggi↗
NASA NTRSDate not supplied

The Application of Artificial Intelligence and Deep Learning to Visually Identify Micrometeoroid and Orbital Debris Impacts

Recent advancements in Artificial Intelligence (AI) have made Machine Learning (ML) techniques readily available for practical applications while using a fraction of time that was previously required. In particular, the use of Deep Learning (DL) algorithms has advanced the field of image and pattern recognition. With the use of Deep Learning algorithms, Micrometeoroid and Orbital Debris(MMOD) penetrations can be identified with high accuracy and give possibilities to new understandings of hypervelocity impacts.

Deep Learning↗
NASA NTRS2025

Nevada Wildland Fires: Mapping Historical Burned Areas and Identifying Drivers of Fuel Load Growth to Inform Desert Tortoise Habitat Management in Southern Nevada

Wildfire frequency and intensity in the Mojave desert are increasing, driven by invasive grasses that outcompete native vegetation not well-adapted to wildfire. These grasses, primarily cheatgrass (Bromus tectorum) and red brome (Bromus rubens), and the wildfires that occur when the grasses ignite, are a serious threat to the critically endangered Mojave desert tortoise (Gopherus agassizii). Declining Mojave desert tortoise populations are of great concern to project partners, the Bureau of Land Management Southern Nevada District Office, the US Forest Service’s Rocky Mountain Research Station, and the US Department of Agriculture Agricultural Research Service’s Arid Lands Ecology Lab, who currently lack the resources for fire recovery studies essential for informed fire and invasive grass management. To address this gap, the team utilized NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI), to analyze trends in burned areas over the past 20 years through historic burn maps and to examine fuel load growth drivers, with a focus on invasive vegetation. These historical burn maps revealed a pattern of precipitation anomalies that strongly correlate with higher Normalized Difference Vegetation Index (NDVI) values. Years with significant precipitation and NDVI spikes led to greater fuel load in the dry season and larger burns. Additionally, El Niño years correlated significantly with precipitation anomalies which may provide our partners with insights into burn trends and enable better allocation of fuel load treatment practices. However, while identifying drivers of fuel load growth proved feasible, a lack of in situ data hindered attempts to analyze pre-fire growth of invasive grasses compared with native grasses. Despite this limitation, the project demonstrated the feasibility of using Earth observations for wildfire and habitat management, ultimately benefiting conservation efforts for the Mojave desert tortoise.

fuel load↗
NASA NTRS2024

South Africa Ecological Conservation: Identifying and Mapping Riparian Areas in South Africa with Earth Observations

Riparian zones are thin strips of wetland that occur along the edges of rivers, lakes, and other water bodies. They provide many ecosystem and societal benefits such as stream bank stabilization, flood control, and habitat stability, making these zones very important areas to preserve and protect. Recognizing the need to accurately map these ecosystems in a cost-effective way, we partnered with the South African National Biodiversity Institute (SANBI) and the Biodiversity Survey of the Cape(BioSCape) to develop a GI methodology using Esri's ArcGIS Pro and data from Landsat 9 Operational Land Imager-2, Sentinel-2 Multispectral Instrument, and the Shuttle Radar Topography Mission to identify potential riparian zones (PRZ) and observed riparian vegetation(ORV) in the Southern Cape and the North West Province of South Africa to estimate the actual riparian vegetation (ARV) within those areas. Potential riparian ecosystems were calculated by utilizing a Topographic Wetness Index (TWI) and a water feature layer, while observed riparian vegetation were calculated by overlaying a Normalized Difference Vegetation Index (NDVI) and TWI. Actual Riparian Vegetation is determined by the overlap of ORV with PRZ and is done with conditional statements; ORV within PRZ is ARV. This method significantly improved a current riparian land cover classification since it combined high resolution optical imagery and topographic data. We anticipate such maps will be used by conservationists and practitioners interested in riparian monitoring and management.

Remote Sensing↗
NASA NTRS2025

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗
NASA NTRSDate not supplied

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗
NASA NTRSDate not supplied

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗
NASA NTRS2024

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗
NASA NTRS1996

A Space Data System Interface for Self-Identifying Devices

Improved technologies and declining budgets for space exploration have space agencies around the world examining new approaches to building and flying spacecraft. This paper descibes development efforts aimed at a standard message specification for space system devices.

self identifying devices self configuring devices ↗