Results for “data landscape” — Page 58

DOE OSTI2023

AmeriFlux FLUXNET-1F US-xSB NEON Ordway-Swisher Biological Station (OSBS)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xSB NEON Ordway-Swisher Biological Station (OSBS). This is the FLUXNET version of the carbon flux data for the site US-xSB NEON Ordway-Swisher Biological Station (OSBS) produced by applying the standard ONEFlux (1F) software. Site Description - The Ordway-Swisher Biological Station (OSBS) is operated by the University of Florida and comprises over 9,300 acres. It is a year-round field station established for the long-term study and conservation of unique ecosystems through management, research and education. The Station is located approximately 20 miles east of Gainesville in Melrose (Putnam County, Florida). There are two aquatic arrays at Ordway-Swisher, representing the two dominant aquatic features on the landscape: 1) Suggs lake, a shallow surface water lake that is rich in taxa and biologically active in structure and function; and 2) Barco lake, a deep lake connected to ground water. The forest is maintained by fire and has a relatively open structure: it is managed with prescribed burns at a frequency of 3-4 years.

Network), NEON (National Ecological Observatory↗

NASA NTRS2020

Africa Food Security & Agriculture: Predicting the Likelihood of Human-elephant Conflict and Assessing Elephant Habitat Conditions During Extreme Drought and Crop Deficit in the Kavango-Zambezi Area

Human-wildlife conflict is increasingly more common due to human population growth, habitat fragmentation, and changing climatic conditions. This conflict is particularly evident in the Kavango-Zambezi area, where over three million people share the landscape with an abundant megafauna population. As the changing climate continues to exacerbate drought severity and subsequent food availability, conflict between humans and wildlife has become more prevalent. In the Kavango-Zambezi area, conflict between elephants and humans has resulted in crop loss, property damage, and threats to public safety. In order to manage current and future conflict, The Ecoexist Project and Connected Conservation have been working to empower farmers and conserve the natural habitat. This DEVELOP project employed Earth observations to conduct a time series analysis of vegetation health change, elephant movement, and climate conditions, from 2017 to 2020. Data were aggregated into the wet (November through April) and dry (May through October) seasons. The resulting analysis demonstrated the potential to use Landsat 8 Operational Land Imager (OLI), Global Precipitation Measurement’s Integrated Multi-satellite Retrievals for GPM (GPM IMERG), and TerraClimate data to identify potential areas of conflict under increased seasonal variability. An improved understanding of conflict drivers will help support sustainable wildlife conservation and food security in the future.

DEVELOP Project Summary↗

NASA NTRS2020

Africa Food Security & Agriculture: Predicting the Likelihood of Human-elephant Conflict and Assessing Elephant Habitat Conditions During Extreme Drought and Crop Deficit in the Kavango-Zambezi Area

Human-wildlife conflict is increasingly more common due to human population growth, habitat fragmentation, and changing climatic conditions. This conflict is particularly evident in the Kavango-Zambezi area, where over three million people share the landscape with an abundant megafauna population. As the changing climate continues to exacerbate drought severity and subsequent food availability, conflict between humans and wildlife has become more prevalent. In the Kavango-Zambezi area, conflict between elephants and humans has resulted in crop loss, property damage, and threats to public safety. In order to manage current and future conflict, The Ecoexist Project and Connected Conservation have been working to empower farmers and conserve the natural habitat. This DEVELOP project employed Earth observations to conduct a time series analysis of vegetation health change, elephant movement, and climate conditions, from 2017 to 2020. Data were aggregated into the wet (November through April) and dry (May through October) seasons. The resulting analysis demonstrated the potential to use Landsat 8 Operational Land Imager (OLI), Global Precipitation Measurement’s Integrated Multi-satellite Retrievals for GPM (GPM IMERG), and TerraClimate data to identify potential areas of conflict under increased seasonal variability. An improved understanding of conflict drivers will help support sustainable wildlife conservation and food security in the future.

DEVELOP Tech Paper↗

DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Guam: 2023 Energy Baseline Report

This report summarizes the currently available data on Guam's energy sector as of December, 2023. It describes primary energy consumption, end uses, energy production, relevant policies, and key challenges, including details on the power generation and transportation sectors. The report serves as a baseline of understanding to assess energy needs and priorities on the island.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2023

Predicting Patterns of Solar Energy Buildout to Identify Opportunities for Biodiversity Conservation

The construction of solar energy facilities can have positive or negative impacts on biodiversity depending on siting and associated land use transitions. We identified drivers of solar siting and quantified patterns of buildout in states surrounding the Chesapeake Bay watershed – a biodiversity hotspot with numerous ecosystem services. Using a convolutional neural network, we mapped the footprints of ground-mounted solar arrays present in satellite imagery annually from 2017 to 2021 in Delaware, Maryland, Pennsylvania, New York, Virginia, and West Virginia. As of 2021, we identified 958 solar arrays covering 52.3 km2 built primarily on previously cultivated land, while avoiding natural landcover. We fit a binomial-Weibull model to these solar timeseries data in a hierarchical, Bayesian framework to quantify the relationship between geospatial covariates and rate of solar development. Solar array construction rate increased in cultivated areas, areas of lower agricultural suitability, lower slope, lower forest cover, lower biodiversity protection, and greater distances from roads. We also estimated changes in the rate of solar construction over time and found differences among states: acceleration in Virginia and deceleration in New York. We used parameter estimates to map the relative likelihood of future solar development across the study area. This methodology can be used to anticipate where solar is likely to be built in different landscapes and how these patterns align with conservation goals. Around the Chesapeake Bay watershed, the selection of lower quality agricultural areas for solar energy minimizes removal of important habitat and provides opportunities for native plant and pollinator restoration.

Artificial Intelligence↗

DOE OSTI2024

A Functional Survey of the Regulatory Landscape of Estrogen Receptor–Positive Breast Cancer Evolution

Abstract Only a handful of somatic alterations have been linked to endocrine therapy resistance in hormone-dependent breast cancer, potentially explaining ∼40% of relapses. If other mechanisms underlie the evolution of hormone-dependent breast cancer under adjuvant therapy is currently unknown. In this work, we employ functional genomics to dissect the contribution of cis-regulatory elements (CRE) to cancer evolution by focusing on 12 megabases of noncoding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Parallel epigenetic perturbation (CRISPRi) in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies a limited set of noncoding changes potentially involved in therapy resistance. Overall, our data uncover how endocrine therapies trigger the emergence of transient features which could ultimately be exploited to hinder the adaptive process. Significance: This study shows that cells adapting to endocrine therapies undergo changes in the usage or regulatory regions. Dormant cells are less vulnerable to regulatory perturbation but gain transient dependencies which can be exploited to decrease the formation of dormant persisters.

Oncology↗

NASA NTRS1993

Assessing the Relationship Between Spectral Vegetation Indices and Shrub Cover in the Jornada Basin, New Mexico

We assessed the statistical relations between Spectral Vegetation Indices (SVI's) derived from SPOT multi-spectral data and semi-arid shrub cover at the Jornada LTER site in New Mexico. Despite a limited range of shrub cover in the sample the analyses resulted in r(sup 2) values as high as 0 central dot 77. Greenness SVI's (e.g., Simple Ratio, NDVI, SAVI, PVI and an orthogonal Greenness index) were shown to be more sensitive to shrub type and phenology than brightness SVis (e.g., green, red and near-infrared reflectances and a Brightness index). The results varied substantially with small-scale changes in plot size (60m by 60m to 100m by 100m) as a consequence of landscape heterogeneity. The results also indicated the potential for the spectral differentiation of shrub types, and shrubs from grass, using multi-temporal, multi-spectral analysis.

Duncan, Jeff↗

NASA NTRS2017

The Infrared Sensor Suite for SnowEx 2017

SnowEx is a winter airborne and field campaign designed to measure snow-water equivalent in forested landscapes. A major focus of Year 1 (2016-17) of NASA's SnowEx campaign will be an extensive field program involving dozens of participants from U.S. government agencies and from many universities and institutions, both domestic and foreign. Along with other instruments, two infrared (IR) sensors will be flown on a Naval Research Laboratory P-3 aircraft. Surface temperature is a critical input to hydrologic models and will be measured during the SnowEx mission. A Quantum Well Infrared Photodetector (QWIP) IR imaging camera system will be flown along with a KT-15 remote thermometer to aid in the calibration of the IR image data. Together, these instruments will measure surface temperature of snow and ice targets to an expected accuracy of less than 1C.

SnowEx↗

NASA NTRSDate not supplied

Mapping National Forest Aboveground Biomass in Mexico By Integrating GEDI and Landsat Times Series Data

Mexico is one of the countries with great potential for the UN's Reducing Emissions from Deforestation and Forest Degradation (REDD+) program, a key nature-based solution for the forest sector. To monitor carbon stock changes, there is a growing demand for unbiased Monitoring Reporting Verification (MRV) systems to facilitate effective forest management and climate change mitigation strategies. Remote sensing-based national aboveground biomass density (AGBD) estimation over Mexico is scarce and often limited to one-time static mapping, leading to spatiotemporal inconsistency in inputs. As an effort under NASA's Carbon Monitoring System (CMS) program, we have developed a remote sensing-based approach to create consistent historical AGBD maps of Mexico using multi-stream remote sensing data, including spaceborne lidar GEDI and long-term Landsat time series, as well as topographic information. We employ the continuous change detection and classification (CCDC) algorithm for temporal modeling of Landsat surface reflectance, followed by the inference of forest AGBD using a random forest machine learning algorithm with the temporal information of land surface dynamics extracted by the CCDC as input. GEDI provides unprecedented forest structure and AGBD sampling datasets for model training and validation practices. In this presentation, we share the progress made in developing a spatially explicit mapping of historical AGBD changes associated with land surface changes and post-disturbance landscapes.

Taejin Park↗

DOE OSTI2025

Integrated Distribution Planning

The contemporary distribution planning landscape is comprised of an increasing number of factors that require integration into the engineering of the modern electric grid. Expectations for electric utilities to accommodate heightened awareness of stakeholders' interest in things like decarbonization, resilience and equity are growing. As these interests are formed into objectives, many jurisdictions will experience increasing levels of load modifying technologies like DER, building and industrial electrification and electric vehicles which prove not only to challenge the capabilities of the grid; but the processes by which planning for it is traditionally done. Other related factors that strain the conventional distribution planning mold are the swelling amount and sources of data associated with these technologies and the need it creates for improved capabilities in the processes and tools that manage it. As the complexity of the distribution system expands, so will the distribution system's effects on the transmission and generation systems that it is a part of. Forecasting distribution system load and DER are examples of areas where this complexity will manifest, and harmonizing distribution forecasting with transmission and generation forecasting requires higher amounts of intentionality as these typically separate processes become a solitary one. Of course, core activities do not cease as a utility begins to integrate these other factors, and in this webinar we explore specifics of how distribution planning can be expected to evolve as progress towards Integrated Distribution System Planning is made.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

A Novel DNA Repair Gene Signature for Immune Checkpoint Inhibitor-Based Therapy in Gastric Cancer

Gastric cancer is a heterogeneous group of diseases with only a fraction of patients responding to immunotherapy. The relationships between tumor DNA damage response, patient immune system and immunotherapy have recently attracted attention. Accumulating evidence suggests that DNA repair landscape is a significant factor in driving response to immune checkpoint blockade (ICB) therapy. In this study, to explore new prognostic and predictive biomarkers for gastric cancer patients who are sensitive and responsive to immunotherapies, we developed a novel 15-DNA repair gene signature (DRGS) and its related scoring system and evaluated the efficiency of the DRGS in discriminating different molecular and immune characteristics and therapeutic outcomes of patients with gastric adenocarcinoma, using publicly available datasets. The results demonstrated that DRGS high score patients showed significantly better therapeutic outcomes for ICB compared to DRGS low score patients (p < 0.001). Integrated analysis of multi-omics data demonstrated that the patients with high DRGS score were characteristic of high levels of anti-tumor lymphocyte infiltration, tumor mutation burden (TMB) and PD-L1 expression, and these patients exhibited a longer overall survival, as compared to the low-score patients. Results obtained from HPA and IHC supported significant dysregulation of the genes in DRGS in gastric cancer tissues, and a positive correlation in protein expression between DRGS and PD-L1. Therefore, the DRGS scoring system may have implications in tailoring immunotherapy in gastric cancers. A preprint has previously been published (Yuan et al., 2021).

60 APPLIED LIFE SCIENCES↗

NASA NTRS2002

Optical properties of intact leaves for estimating chlorophyll concentration

Changes in leaf chlorophyll content can serve as relative indicators of plant vigor and environmental quality. This study identified reflectance, transmittance, and absorptance wavebands and band ratios within the 400- to 850-nm range for intact leaves that could be used to estimate extracted leaf chlorophyll per unit leaf area (areal concentration) with minimal error. Leaf optical properties along with chlorophyll a, b, and a + b concentrations were measured for the planar-leaved sweetgum (Liquidambar styraciflua L.), red maple (Acer rubrum L.), wild grape (Vitis rotundifolia Michx.), and switchcane [Arundinaria gigantea (Walter) Muhl.], and for needles of longleaf pine (Pinus palustris Miller). Generally, reflectance, transmittance, and absorptance corresponded most precisely with chlorophyll concentrations at wavelengths near 700 nm, although regressions were also strong in the 550- to 625-nm range. A power function was superior to a simple linear function in yielding low standard deviations of the estimate (s). When data were combined among the planar-leaved species, s values were low at approximately 50 mumol/m2 out of a 940 mumol/m2 range in chlorophyll a + b at best-fit wavelengths of 707 to 709 nm. Minimal s values for chlorophyll a + b ranged from 32 to 62 mumol/m2 across species when band ratios having numerator wavelengths of 693 to 720 nm were used with the application of a power function. Optimal denominator wavelengths for the band ratios were 850 nm for reflectance and transmittance and 400 nm for absorptance. This information can be applied in designing field portable chlorophyll meters and in the landscape-scale remote sensing of plant responses to the environment.

Chlorophyll/analysis↗

NASA NTRS2020

Massachusetts Water Resources: Assessing Flood Events Resulting from North American Beaver Reintroduction with NASA Earth Observations to Inform Biodiversity and Infrastructure Management

North American beavers (Castor canadensis) are returning to Massachusetts after overhunting decimated their populations in the 1700s. Current regulations have allowed this species to recolonize, resulting in increasingly prevalent human-beaver conflicts. These ecosystem engineers can quickly change their environment through the creation of dams, leading to floods that can adversely affect human infrastructures, such as basements, roads, or septic systems. Conversely, beaver dams can positively influence their environment, modifying the physical and chemical properties of streams and providing crucial habitats to a variety of wildlife. The 2020 Spring Boston NASA DEVELOP team collaborated with the Massachusetts Audubon Society to support their efforts in monitoring beaver impacts and managing human-beaver conflicts. The project-utilized data from Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager to map the spectral signature created from beaver-induced flooding. The team created a tool called Beaver-Flood Event Detector (B-FED) in Google Earth Engine using imagery from 1985 to 2019. Ancillary datasets were incorporated into B-FED that allow the tool to highlight flood events in wetland areas and in situ observations of beaver presence. Beaver observations in or near flooded areas indicated likelihood that the flood was beaver induced. Time series and animations were also produced to display key regions of landscape change across Massachusetts. B-FED will allow the partner to identify and assess potential ecosystem changes and infrastructural impacts from beavers across Massachusetts and inform future management practices.

Water Resources↗

NASA NTRS2020

Massachusetts Water Resources: Assessing Flood Events Resulting from North American Beaver Reintroduction with NASA Earth Observations to Inform Biodiversity and Infrastructure Management

North American beavers (Castor canadensis) are returning to Massachusetts after overhunting decimated their populations in the 1700s. Current regulations have allowed this species to recolonize, resulting in increasingly prevalent human-beaver conflicts. These ecosystem engineers can quickly change their environment through the creation of dams, leading to floods that can adversely affect human infrastructures, such as basements, roads, or septic systems. Conversely, beaver dams can positively influence their environment, modifying the physical and chemical properties of streams and providing crucial habitats to a variety of wildlife. The 2020 Spring Boston NASA DEVELOP team collaborated with the Massachusetts Audubon Society to support their efforts in monitoring beaver impacts and managing human-beaver conflicts. The project-utilized data from Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager to map the spectral signature created from beaver-induced flooding. The team created a tool called Beaver-Flood Event Detector (B-FED) in Google Earth Engine using imagery from 1985 to 2019. Ancillary datasets were incorporated into B-FED that allow the tool to highlight flood events in wetland areas and in situ observations of beaver presence. Beaver observations in or near flooded areas indicated likelihood that the flood was beaver induced. Time series and animations were also produced to display key regions of landscape change across Massachusetts. B-FED will allow the partner to identify and assess potential ecosystem changes and infrastructural impacts from beavers across Massachusetts and inform future management practices

Water Resources↗

DOE OSTI2024

Purple is the new green: biopigments and spectra of Earth-like purple worlds

ABSTRACT With more than 5500 detected exoplanets, the search for life is entering a new era. Using life on Earth as our guide, we look beyond green landscapes to expand our ability to detect signs of surface life on other worlds. While oxygenic photosynthesis gives rise to modern green landscapes, bacteriochlorophyll-based anoxygenic phototrophs can also colour their habitats and could dominate a much wider range of environments on Earth-like exoplanets. Here, we characterize the reflectance spectra of a collection of purple sulfur and purple non-sulfur bacteria from a variety of anoxic and oxic environments. We present models for Earth-like planets where purple bacteria dominate the surface and show the impact of their signatures on the reflectance spectra of terrestrial exoplanets. Our research provides a new resource to guide the detection of purple bacteria and improves our chances of detecting life on exoplanets with upcoming telescopes. Our biological pigment data base for purple bacteria and the high-resolution spectra of Earth-like planets, including ocean worlds, snowball planets, frozen worlds, and Earth analogues, are available online, providing a tool for modellers and observers to train retrieval algorithms, optimize search strategies, and inform models of Earth-like planets, where purple is the new green.

Coelho, Lígia Fonseca (ORCID:0000000150081249)↗

DOE OSTI2020

Interplay of changing irrigation technologies and water reuse: example from the upper Snake River basin, Idaho, USA

Abstract. Careful allotment of water resources for irrigation is critical for ensuring the resiliency of agriculture in semiarid regions, and modernizing irrigation technology to minimize inefficient water losses is an important tool for farmers and agricultural economies. While modernizing irrigation technology can achieve reductions in the nonbeneficial use of water, such as bare soil evaporation and nonconsumptive losses, water returned to the landscape is also reduced, often eliminating flow paths that other users rely on. In basins using a combination of surface and groundwater, replenishing aquifer storage by the managed aquifer recharge (MAR) of seasonally available water can mitigate the aquifer drawdown that results from reduced recharge when irrigation efficiency is improved. We examine the effects of MAR on the system-scale efficiency of modernizing irrigation technology and the resulting changes in the reuse of nonconsumptive losses, using a macroscale hydrologic model applied to the semiarid upper Snake River basin (USRB) of western Wyoming and southern Idaho, USA. Irrigation technologies were represented explicitly in the model, and available data informed baseline parameterizations of the irrigation technology. A suite of parameterizations were simulated that updated the existing technologies to be more efficient, both with and without sufficient MAR to cause a stabilization of the aquifer at the present-day head. As expected, simulated changes in irrigation technology resulted in greater downstream export of pristine water and a higher rate of aquifer drawdown when MAR was not simulated. Under current water use and cropping patterns, we were not able to simulate aquifer stabilization and maintain discharge downstream at any level of irrigation efficiency. We found support for the hypothesis that, as efficiency improves, less MAR is required to maintain a stable aquifer than when return flows are reduced due to increased efficiency. To evaluate the hypothesis, we defined the management benefit as a metric that compared the difference between the change in irrigation's net recharge and the change in MAR required as irrigation technology became more efficient. The metric generally indicated that less MAR was needed than net recharge was lost, but only for the most efficient case did the management benefit exceed the MAR needed at the baseline to stabilize the aquifer. Increasing efficiency of irrigation technology reduced the reuse of the gross irrigation derived from prior nonconsumptive losses, but simulating MAR increased reuse for a given parameterization, leading to higher effective irrigation efficiency. We find that local groundwater storage that users depend on is generally more sensitive to management decisions than downstream flows, and the drawdown of the aquifer without MAR always exceeded any decrease in discharge induced by MAR. Improving resource sufficiency in semiarid systems like the USRB will require an array of solutions that will need to balance benefits to local and downstream users.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Tectonic, volcanic, and climatic geomorphology study of the Sierras Pampeanas Andes, northwestern Argentina

A proposed analysis of Shuttle Imaging Radar-B (SIR-B) data extends current research in the Sierras Pampeanas and the Puna of northwestern Argentina to the determination - by the digital analysis of mountain-front sinuousity - of the relative age and amount of fault movement along mountain fronts of the late-Cenozoic Sierras Pampeanas basement blocks; the determination of the age and history of the boundary across the Andes at about 27 S latitude between continuing volcanism to the north and inactive volcanism to the south; and the determination of the age and extent of Pleistocene glaciation in the High Sierras, as well as the comparative importance of climatic change and tectonic movements in shaping the landscape. The integration of these studies into other ongoing geology projects contributes to the understanding of landform development in this active tectonic environment and helps distinguish between climatic and tectonic effects on landforms.

Bloom, A. L.↗