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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Deeper Dive into Interoperability and Its Implications for LunaNet Communications and Navigation Services

The Artemis program being developed by United States’ (US) National Aeronautics and Space Administration (NASA) is developing the capabilities to return humans to the Moon and establish an initial base camp and associated infrastructure with extensive contributions from international and commercial partners. In planning for cislunar exploration and science missions, space agencies are collaborating to enable communications, networking, and Positioning, Navigation, and Timing (PNT) systems—called LunaNet—to exchange information and provide services to cislunar spacecraft and space systems, thus helping each other to achieve their shared goals. To achieve commonality and lower cost for mutual benefit, the strategy of interoperability is being adopted to help fit all the pieces together and function smoothly. Facilitating interoperability should benefit lunar missions by providing the ability to operate in a collaborative environment similar to the terrestrial Internet. Interoperability allows them to share information, navigate safely despite increasing radio frequency congestion, and follow common processes and procedures for effective joint operations. Unlike prior government-dominated efforts, this ecosystem is expected to include and benefit for-profit (commercial) businesses, non-profit organizations, and academic institutions as active stakeholders. Ultimately, the goal is to enable a cislunar ecosystem of service providers and users to contribute to and/or utilize infrastructure and capabilities to achieve mission objectives that span the full range of human endeavors while supporting a variety of business models. This approach enables a Systems of Systems (SoS), such as a Network-of-Networks, to be sustainable in the context of the LunaNet ecosystem as systems evolve over time in technologies, standards, components, and user applications. This paper reports on the results of an effort to help frame the development of the international LunaNet architecture by providing a canonical definition of interoperability broad enough to meet these needs, examining architectural and operational implications of the definition, and exploring interoperability strategies and tactics to deploy and evolve the services proposed for cislunar exploration and science missions.

interoperability↗
DOE OSTI2026

Generating multiple benefits from forests by producing value-added products: Lessons from the Pacific Northwestern US

This paper asks what conditions are needed to counteract a declining forest industry. The mobilization of supply chains for new value-added forest products and services can be supported by programs designed to simultaneously achieve multiple goals related to health, climate, and rural economic development. But several challenges are identified that underscore the need to stack benefits and incentives to achieve muti-sectoral goals. Based on a case study in Washington state, we find opportunities and constraints for sourcing forest products are determined by the local and regional conditions such as availability of working forests and their residues, socioeconomic conditions, workforce availability, transportation options, and perceptions about social license of the new industry. Key recommendations are the need for (1) a consistent demand and resilient supply chain for the new product; (2) a stable, supportive policy and assessment framework; (3) timely, transparent, and trusted monitoring and reporting of benefits and costs; (4) fostering engagement and buy-in from stakeholders; (5) a context-specific evaluation of opportunities and constraints; and (6) agreement on the goals of sustainable forestry. A diversity of products and markets builds a more resilient forest-based economy by mitigating impacts of disruptions in any individual market, adding value to biomass, increasing employment, and reducing forest risks to fire, insects, and disease.

Bioenergy↗
DOE OSTI2026

Complementary effects of supplemental feeding and straw retention on winter biodiversity in rice agroecosystems

Rice paddies are both major food-production systems and critical winter habitats for wildlife. In the Civilian Control Zone (CCZ) adjoining the Korean Demilitarized Zone (DMZ), post-harvest interventions such as supplementary grain feeding and straw retention are promoted through agronomic and conservation incentives. These measures differ in ecological scope: feeding provides direct, concentrated energetic subsidies, whereas straw management alters habitat structure and resource bases. We clarified whether these pathways function in complementary or substitutive ways to support resilient, long-term conservation strategies in rice agroecosystems. Using camera traps, we evaluated the effects of three straw treatments (chopped-straw, whole-straw, straw-removed) and supplemental feeding on winter bird and mammal communities across 48 rice fields in the CCZ. Our results demonstrate that feeding produced strong, localized increases in bird abundance and richness, driven mainly by cranes (Grus japonensis and Antigone vipio) and geese (Anser spp.), with limited effects on Shannon diversity or functional structure. Among non-feeding fields, chopped-straw paddies consistently supported higher richness and Shannon diversity than whole-straw or straw-removed fields, while centroid shifts in taxonomic and functional space were modest. Mammal abundance and diversity were largely insensitive to feeding or straw regimes, varying instead with road and forest distance and regional context. Supplemental feeding and straw retention are therefore not interchangeable tools: feeding concentrates a few avian guilds, whereas chopped-straw retention enhances baseline diversity across farmland. Collectively, our findings suggest integrating low-input straw retention with targeted feeding offers a more robust pathway for sustaining winter biodiversity in rice agroecosystems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗
DOE OSTI2025

The Economic, Environmental, and Performance Impacts of Co-locating Pollinator Habitat at Large Scale Solar Facilities (Final Technical Report)

The Pollinator Habitat Aligned with Solar Energy (PHASE) project studied the impacts of co-location of pollinator plantings at large-scale solar facilities (10 MW or larger). The project focused on the ecological benefits, economic considerations, and PV performance impacts of co-located pollinator vegetation through field research at seven operating solar sites.

14 SOLAR ENERGY↗
NASA NTRS2018

Agroforestry in the Sahel

West African farmers adjust tree cover to realize the co-benefits of agroforestry, according to analyses of remote sensing data.

Ecosystem services↗
NASA NTRS2024

Biodiversity loss reduces global terrestrial carbon storage

Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem’s carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.

Biodiversity↗
NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗
NASA NTRS2018

Integrating the Social, Hydrological and Ecological Dimensions of Freshwater Health: The Freshwater Health Index

Degradation of freshwater ecosystems and the services they provide is a primary cause of increasing water insecurity, raising the need for integrated solutions to freshwater management. While methods for characterizing the multi-faceted challenges of managing freshwater ecosystems abound, they tend to emphasize either social or ecological dimensions and fall short of being truly integrative. This paper suggests that management for sustainability of freshwater systems needs to consider the linkages between human water uses, freshwater ecosystems and governance. We present a conceptualization of freshwater resources as part of an integrated social-ecological system and propose a set of corresponding indicators to monitor freshwater ecosystem health and to highlight priorities for management. We demonstrate an application of this new framework -the Freshwater Health Index (FHI) - in the Dongjiang River Basin in southern China, where stakeholders are addressing multiple and conflicting freshwater demands. By combining empirical and modeled datasets with surveys to gauge stakeholders' preferences and elicit expert information about governance mechanisms, the FHI helps stakeholders understand the status of freshwater ecosystems in their basin, how ecosystems are being manipulated to enhance or decrease water-related services, and how well the existing water re-source management regime is equipped to govern these dynamics over time. This framework helps to operationalize a truly integrated approach to water resource management by recognizing the interplay between governance, stakeholders, freshwater ecosystems and the services they provide

ecosystem services↗
NASA NTRSDate not supplied

Making Heliophysics Research More Open and Accessible at the Community Coordinated Modeling Center (CCMC)

The Space Weather and Heliophysics modeling community seeks to improve our understanding of space weather events and their impact on human activities. The Community Coordinated Modeling Center’s (CCMC, https://ccmc.gsfc.nasa.gov) mission is to support the community by providing a convenient collaborative platform that brings together space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. This presentation reports on CCMC’s ongoing efforts in making Heliophysics models and data more accessible, open, and reproducible. We will also explore interoperability within the ecosystem of CCMC services and how this ecosystem interoperates with external partner services and data streams.

space weather↗
NASA NTRS2017

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Meng, Ran↗
NASA NTRS2020

Cloud-Computing and Machine Learning in Support of Country-Level Land Cover and Ecosystem Extent Mapping in Liberia and Gabon

Liberia and Gabon joined the Gaborone Declaration for Sustainability in Africa (GDSA), established in 2012, with the goal of incorporating the value of nature intonational decision making by estimating the multiple services obtained from ecosystems using the natural capital accounting framework. In this study, we produced 30-m resolution 10 classes land cover maps for the 2015 epoch for Liberia and Gabon using the Google Earth Engine (GEE) cloud platform to support the ongoing natural capital accounting efforts in these nations. We pro-pose an integrated method of pixel-based classification using Landsat 8 data, the Random Forest(RF) classifier and ancillary data to produce high quality land cover products to fit abroad range of applications, including natural capital accounting. Our approach focuses on a pre-classification filtering (Masking Phase) based on spectral signature and ancillary data to reduce the number of pixels prone to be misclassified; therefore, increasing the quality of the final product. The proposed approach yields an overall accuracy of 83% and 81% for Liberia and Gabon, respectively, out performing prior land cover products for these countries in both thematic content and accuracy. Our approach, while relatively simple and highly replicable, was able to produce high quality land cover products to fill an observational gap in up to date land cover data at national scale for Liberia and Gabon.

Celio de Sousa↗
NASA NTRS2018

Identifying and Forecasting Potential Biophysical Risk Areas within a Tropical Mangrove Ecosystem Using Multi-Sensor Data

Mangroves are one of the most productive ecosystems known for provisioning of various ecosystem goods and services. They help in sequestering large amounts of carbon, protecting coastline against erosion, and reducing impacts of natural disasters such as hurricanes. Bhitarkanika Wildlife Sanctuary in Odisha harbors the second largest mangrove ecosystem in India. This study used Terra, Landsat and Sentinel-1 satellite data for spatio-temporal monitoring of mangrove forest within Bhitarkanika Wildlife Sanctuary between 2000 and 2016. Three biophysical parameters were used to assess mangrove ecosystem health: leaf chlorophyll (CHL), Leaf Area Index (LAI), and Gross Primary Productivity (GPP). A long-term analysis of meteorological data such as precipitation and temperature was performed to determine an association between these parameters and mangrove biophysical characteristics. The correlation between meteorological parameters and mangrove biophysical characteristics enabled forecasting of mangrove health and productivity for year 2050 by incorporating IPCC projected climate data. A historical analysis of land cover maps was also performed using Landsat 5 and 8 data to determine changes in mangrove area estimates in years 1995, 2004 and 2017. There was a decrease in dense mangrove extent with an increase in open mangroves and agricultural area. Despite conservation efforts, the current extent of dense mangrove is projected to decrease up to 10% by the year 2050. All three biophysical characteristics including GPP, LAI and CHL, are projected to experience a net decrease of 7.7%, 20.83% and 25.96% respectively by 2050 compared to the mean annual value in 2016. This study will help the Forest Department, Government of Odisha in managing and taking appropriate decisions for conserving and sustaining the remaining mangrove forest under the changing climate and developmental activities.

Shanti Shrestha↗
NASA NTRS2021

Missing the Reef for the Corals: Unexpected Trends Between Coral Reef Condition and the Environment at the Ecosystem Scale

It is incontrovertible that many coral reefs are in various stages of decline and may be unable to withstand the effects of global climate change, jeopardizing vital ecosystem goods and services to hundreds of millions of people around the world. An estimated 50% of the world's corals have already been lost, and those remaining may be lost by 2030 under the “business as usual” CO2 emissions scenario. However, the foundation of these predictions is a surprisingly sparse dataset, wherein ~0.01–0.1% of the world's reef area has been quantitatively surveyed. Further, the available data comprise observations at the 1–10 m scale, which are not evenly spaced across reefs, but often clustered in areas representing focused survey effort. This impedes modeling and predicting the impact of a changing environment at the ecosystem scale. Here we highlight deficiencies in our current understanding of the relationship between coral reefs and their environments. Specifically, we conduct a meta-analysis using estimates of coral cover from a variety of local surveys, quantitatively relating reef condition to a suite of biogeophysical forcing parameters. We find that readily available public data for coral cover exhibit unexpected trends (e.g., a positive correlation between coral cover and multi-year cumulative thermal stress), contrary to prevailing scientific expectations. We illustrate a significant gap in our current understanding, and thereby prediction, of coral reefs at the ecosystem scale that can only be remedied with uniform, high-density data across vast coral reef regions, such as that from remote sensing.

Eric J Hochberg↗
NASA NTRS2022

Space Communications Responsive to Events Across Missions (SCREAM): An Investigation of Network Solutions for Transient Science Space Systems

Space Communications Responsive to Events Across Missions (SCREAM): An Investigation of Network Solutions for Transient Science Space Systems The National Academies have prioritized the pursuit of new scientific discoveries using diverse and temporally coordinated measurements from multiple ground and space-based observatories. Networked communications can enable such measurements by connecting individual observatories and allowing them to operate as a cohesive and purposefully designed system. Timely data flows across terrestrial and space communications networks are required to observe transient scientific events and processes. Currently, communications to space-based observatories experience large latencies due to manual service reservation and scheduling procedures, intermittent signal coverage, and network capacity constraints. If space communications network latencies could be reduced, new discoveries about dynamic scientific processes could be realized. However, science mission and network planners lack a systematic framework for defining, quantifying and evaluating timely space data flow implementation options for transient scientific observation scenarios involving multiple ground and space-based observatories. This dissertation presents a model-based systems engineering approach to investigate and develop network solutions to meet the needs of transient science space systems. First, a systematic investigation of the current transient science operations of the National Aeronautics and Space Administration’s (NASA) Tracking and Data Relay Satellite (TDRS) space data network and the Neil Gehrels Swift Observatory resulted in a formal architectural model for transient science space systems. Two methods individual missions may use to achieve timely network services were defined, quantitatively modeled, and experimentally compared. Next, the architectural model was extended to describe two alternative ways to achieve timely and autonomous space data flows to multiple space-based observatories within the context of a purposefully designed transient science observation scenario. A quantitative multipoint space data flow modeling method based in queueing theory was defined. General system suitability metrics for timeliness, throughput, and capacity were specified to support the evaluation of alternative network data flow implementations. A hypothetical design study was performed to demonstrate the multipoint data flow modeling method and to evaluate alternative data flow implementations using TDRS. The merits of a proposed future TDRS broadcast service to implement multipoint data flows were quantified and compared to expected outcomes using the as-built TDRS network. Then, the architectural model was extended to incorporate commercial network service providers. Quantitative models for Globalstar and Iridium short messaging data services were developed based on publicly available sources. Financial cost was added to the set of system suitability metrics. The hypothetical design study was extended to compare the relative suitability of the as-built TDRS network with the commercial Globalstar and Iridium networks. Finally, results from this research are being applied by NASA missions and network planners. In 2020, Swift implemented the first automated command pipeline, increasing its expected gravitational wave follow-up detection rate by greater than 400%. Current NASA technology initiatives informed by this research will enable future space-based observatories to become interoperable sensing devices connected by a diverse ecosystem of network service providers.

Christopher J. Roberts↗