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All sources NASA NTRS DOE OSTI

NASA NTRS2022

Puget Sound Water Resources: Using Earth Observations to Map Bull Kelp in the Puget Sound, Washington, to Support Conservation and Restoration

Bull kelp (Nereocystis luetkeana) is a critical component of nearshore ecosystems in the Puget Sound region of the Salish Sea. The Port of Seattle and Washington State Department of Natural Resources (DNR) have identified possible declines in bull kelp extent and changes in its distribution throughout the Central Puget Sound near Seattle, Washington. Bull kelp losses threaten critical ecological services and marine habitat, as well as important cultural resources. However, these changes are not well tracked or understood due to the expensive and time-intensive nature of traditional kelp canopy monitoring methods. The Port of Seattle and Washington DNR partnered with the NASA DEVELOP team to explore the feasibility of using Earth observations between 2016 and 2021 obtained from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 MultiSpectral Instrument (MSI) as a potential tool to monitor and map bull kelp. Our team identified a variety of challenges that need to be addressed before this approach can be utilized as an effective means for identifying or mapping nearshore urban kelp beds. We found that neither Sentinel-2 nor Landsat 8 significantly differentiates between kelp and no-known kelp using the Normalized Difference Vegetation Index (NDVI) or Normalized Difference Red-Edge Blue (NDREB). While the tidal and current filtering methods discussed here may be beneficial for identifying promising single image dates for kelp classification, the filters we used reduced the number of images each year to the point that modeling or mapping yearly kelp extent or creating time series of kelp did not appear to be feasible.

Mike Hitchner↗

DOE OSTI2024

Wind Energy Instrumentation Development Roadmap

The current instrumentation for observing the complex flow fields in and around wind plants struggles to match the fidelity of existing simulation tools. As a result, these measurement limitations create a hurdle for validating and assessing the quality of the wind plant numerical models. This roadmap for instrumentation development recommendations was created to offer guidance on narrowing the gap between measurement and simulation fidelity. A process was established to identify where gaps in instrumentation exist for wind energy test campaigns by analyzing the capabilities of instrumentation for capturing the various important phenomena at the necessary resolution for both the science goal and validation objectives. To this end, a multi-disciplinary team of experts on instrumentation, wind energy, and atmospheric science was assembled to identify these significant instrumentation needs. A recommendation for instrumentation to be developed is provided, and the framework developed through this process is expected to be useful to the design of future test campaigns. The mapping tools developed for this process will be distributed as part of a future International Energy Agency Wind Technology Collaboration Program task on instrumentation development.

17 WIND ENERGY↗

NASA NTRS2015

Results from the Wilkinson Microwave Anisotropy Probe

The Wilkinson Microwave Anisotropy Probe (WMAP) mapped the distribution of temperature and polarization over the entire sky in five microwave frequency bands. These full-sky maps were used to obtain measurements of temperature and polarization anisotropy of the cosmic microwave background with the unprecedented accuracy and precision. The analysis of two-point correlation functions of temperature and polarization data gives determinations of the fundamental cosmological parameters such as the age and composition of the universe, as well as the key parameters describing the physics of inflation, which is further constrained by three-point correlation functions. WMAP observations alone reduced the flat Λ cold dark matter (Lambda Cold Dark Matter) cosmological model (six) parameter volume by a factor of > 68, 000 compared with pre-WMAP measurements. The WMAP observations (sometimes in combination with other astrophysical probes) convincingly show the existence of non-baryonic dark matter, the cosmic neutrino background, flatness of spatial geometry of the universe, a deviation from a scale-invariant spectrum of initial scalar fluctuations, and that the current universe is undergoing an accelerated expansion. The WMAP observations provide the strongest ever support for inflation; namely, the structures we see in the universe originate from quantum fluctuations generated during inflation.

The Wilkinson Microwave Anisotropy Probe (WMAP)↗

NASA NTRS2020

PHALANX: Expendable Projectile Sensor Networks for Planetary Exploration

Technologies enabling long-term, wide-ranging measurement in hard-to-reach areas are a critical need for planetary science inquiry. Phenomena of interest include flows or variations in volatiles, gas composition or concentration, particulate density, or even simply temperature. Improved measurement of these processes enables understanding of exotic geologies and distributions or correlating indicators of trapped water or biological activity. However, such data is often needed in unsafe areas such as caves, lava tubes, or steep ravines not easily reached by current spacecraft and planetary robots. To address this capability gap, we have developed miniaturized, expendable sensors which can be ballistically lobbed from a robotic rover or static lander - or even dropped during a flyover. These projectiles can perform sensing during flight and after anchoring to terrain features. By augmenting exploration systems with these sensors, we can extend situational awareness, perform long-duration monitoring, and reduce utilization of primary mobility resources, all of which are crucial in surface missions. We call the integrated payload that includes a cold gas launcher, smart projectiles, planning software, network discovery, and science sensing: PHALANX. In this paper, we introduce the mission architecture for PHALANX and describe an exploration concept that pairs projectile sensors with a rover “mothership.” Science use cases explored include reconnaissance using ballistic cameras, volatiles detection, and building timelapse maps of temperature and illumination conditions. Strategies to autonomously coordinate constellations of deployed sensors to self-discover and localize with peer ranging (i.e. a “local GPS”) are summarized, thus providing communications infrastructure beyond-line-of-sight (BLOS) of the rover. Capabilities were demonstrated through both simulation and physical testing with a terrestrial prototype. The approach to developing a terrestrial prototype is discussed, including design of the launching mechanism, projectile optimization, micro-electronics fabrication, and sensor selection. Results from early testing and characterization of commercial-off-the-shelf (COTS) components are reported. Nodes were subjected to successful burn-in tests over 48 hours at full logging duty cycle. Integrated field tests were conducted in the Roverscape, a half-acre planetary analog environment at NASA Ames, where we tested up to 10 sensor nodes simultaneously coordinating with an exploration rover. Ranging accuracy has been demonstrated to be within +/-10cm over 20m using commodity radios when compared to high-resolution laser scanner ground truthing. Evolution of the design, including progressive miniaturization of the electronics and iterated modifications of the enclosure housing for streamlining and optimized radio performance are described. Finally, lessons learned to date, gaps toward eventual flight mission implementation, and continuing future development plans are discussed.

Dille, Michael↗

DOE OSTI2026

Demonstration of reconstruction-free static magnetic control of DIII-D plasma with deep reinforcement learning

This paper presents the development and experimental validation of a reinforcement learning (RL)-based magnetic controller on the DIII-D tokamak. The controller directly maps raw magnetic diagnostic signals to actuator commands, replacing the traditional isoflux control algorithm based on equilibrium reconstruction. Four RL controllers are trained using the Soft Actor–Critic algorithm with an asymmetric Actor–Critic architecture in the NSFsim simulator. All controllers are deployed in the DIII-D Plasma Control System and operated with a 4 kHz feedback loop. Two randomization strategies are evaluated during training: evolving kinetic profiles and fixed kinetic profiles within each episode. The latter approach is found to better capture experimental deviations in the current density profile and to provide overall improved control performance. Robust operation is demonstrated across heating power scans in both L- and H-mode plasmas, as well as during transient events such as L–H transitions and pellet injections. Control errors in plasma shape and radial position remained within 1.5–2.0 cm and 1 cm, respectively. A notable discrepancy was observed in the vertical X-point position, with errors of up to approximately 4 cm, attributed to the current density distribution mismatches between simulations and experiments.

DIII-D↗

DOE OSTI2026

ORCHA: A performance portability system for extreme heterogeneity

Heterogeneity is the prevalent trend in the rapidly evolving high-performance computing (HPC) landscape in both hardware and application software. The diversity in hardware platforms, currently comprising various accelerators and a future possibility of specializable chiplets, poses a significant challenge for scientific software developers aiming to harness optimal performance across different computing platforms while maintaining the quality of solutions when their applications are simultaneously growing more complex. Code synthesis and code generation can provide mechanisms to mitigate this challenge. We have developed a divide and conquer approach where different aspects of performance are handled by different stand-alone tools that are interfaced with the application through generated code. This portability system, ORCHA, enables users to configure and orchestrate their computations among available resources on a platform by specifying a high-level recipe, thereby permitting a many-to-many paradigm where each recipe results in a different variant of the application. The core design goal is to let users decide the application’s hardware mapping and orchestration by editing only the high-level recipe—without modifying the maintained source code or binding the application to a particular runtime system. Tools in ORCHA distribution are: CG-Kit for translating the recipe into an execution graph; Milhoja to execute the graph by orchestrating data and task movement among hardware resources; and Macroprocessor that enables users to define their own code-shorthand for higher composability and easier management of code variants. Additionally, the design of ORCHA permits tools to work in a plug-and-play mode where the application can build and run without CG-Kit and Milhoja, and either tool can be swapped out for other tools with similar capabilities by modifying the code generation portion of ORCHA. In this paper, we describe the design of ORCHA and the role that code-generation plays in isolating applications from tools. We demonstrate the breadth of configurations ORCHA enables with a case study in which an application configuration is realized on three distinct hardware mappings—a GPU-centric, a CPU/GPU balanced, and a CPU/GPU concurrent layouts by using different recipes.

Lee, Youngjun↗

NASA NTRS2013

Diagnosing Aircraft Icing Potential from Satellite Cloud Retrievals

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This paper describes new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content (IWC and LWC) profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS and ground-based icing remote sensing datasets, the satellite icing detection and intensity accuracies are approximately 90% and 70%, respectively, and found to be similar for both low level and deep ice over water cloud systems. The satellite-derived icing boundaries capture the reported altitudes over 90% of the time. Satellite analyses corresponding to the time and location of several recent aviation accidents and with icing PIREPS are also presented that reveal skill in identifying severe icing conditions. These results demonstrate the utility of satellite cloud retrievals for quantitatively diagnosing the potential for icing conditions on temporal and spatial scales that should be useful to the aviation community. Plans are being developed to deliver these new satellite products to the GOES-R Proving Ground in the near future so that they can be evaluated in operational applications.

Smith, William L., Jr.↗

NASA NTRS2002

Monitoring of Structural Integrity of Composite Structures by Embedded Optical Fiber Sensors

Real time monitoring of the mechanical integrity and stresses on key aerospace composite structures like aircraft wings, walls of pressure vessels and fuel tanks or any other structurally extended components and panels as in space telescopes is very important to NASA. Future military and commercial aircraft as well as NASA space systems such as Space Based Radar and International Space Station will incorporate a monitoring system to sense any degradation to the structure. In the extreme flight conditions of an aerospace vehicle it might be desirable to measure the strain every ten centimeters and thus fully map out the strain field of a composite component. A series of missions and vehicle health management requirements call for these measurements. At the moment thousands of people support a few vehicle launches per year. This number can be significantly reduced by implementing intelligent vehicles with integral nervous systems (smart structures). This would require maintenance to be performed only as needed. Military and commercial aircrafts have an equally compelling case. Maintenance yearly costs are currently reaching astronomical heights. Monitoring techniques are therefore required that allow for maintenance to be performed only when needed. This would allow improved safety by insuring that necessary tasks are performed while reducing costs by eliminating procedures that are costly and not needed. The advantages fiber optical sensors have over conventional electro-mechanical systems like strain gauges have been widely extolled in the research literature. These advantages include their small size, low weight, immunity to electrical resistance, corrosion resistance, compatibility with composite materials and process conditions, and multiplexing capabilities. One fiber optic device which is suitable for distributed sensing is the fiber Bragg grating (FBG). Researchers at NASA MSFC are currently developing techniques for using FBGs for monitoring the integrity of advanced structural materials expected to become the mainstay of the current and future generation space structures. Since carbon-epoxy composites are the materials of choice for the current space structures, the initial study is concentrated on this type of composite. The goals of this activity are to use embedded FBG sensors for measuring strain and temperature of composite structures, and to investigate the effects of various parameters such as composite fiber orientation with respect to the optical sensor, unidirectional fiber composite, fabrication process etc., on the optical performance of the sensor. This paper describes an experiment to demonstrate the use of an embedded FBG for measuring strain in a composite material. The performance of the fiber optic sensor is determined by direct comparison with results from more conventional instrumentation.

Albert J. Osei↗

NASA NTRS2003

Investigation of Structural Properties of Carbon-Epoxy Composites Using Embedded Fiber-Optic Bragg Gratings

Real time monitoring of the mechanical integrity and stresses on key aerospace composite structures like aircraft wings, walls of pressure vessels and fuel tanks or any other structurally extended components and panels as in space telescopes is very important to NASA. Future military and commercial aircraft as well as NASA space systems such as Space Based Radar and International Space Station will incorporate a monitoring system to sense any degradation to the structure. In the extreme flight conditions of an aerospace vehicle it might be desirable to measure the strain every ten centimeters and thus fully map out the strain field of a composite component. A series of missions and vehicle health management requirements call for these measurements. At the moment thousands of people support a few vehicle launches per year. This number can be significantly reduced by implementing intelligent vehicles with integral nervous systems (smart structures). This would require maintenance to be performed only as needed. Military and commercial aircrafts have an equally compelling case. Annual maintenance costs are currently reaching astronomical heights. Monitoring techniques are therefore required that allow for maintenance to be performed only when needed. This would allow improved safety by insuring that necessary tasks are performed while reducing costs by eliminating procedures that are costly and not needed. The advantages fiber optical sensors have over conventional electro-mechanical systems like strain gauges have been widely extolled in the research literature. These advantages include their small size, low weight, immunity to electrical resistance, corrosion resistance, compatibility with composite materials and process conditions, and multiplexing capabilities. One fiber optic device which is suitable for distributed sensing is the fiber Bragg grating (FBG). This is a periodic perturbation in the refractive index of the fiber core. When a broadband light is coupled into the optical fiber sensor, a reflection peak will be obtained centered around a wavelength called Bragg-wavelength. The Bragg-wavelength depends on the refractive index and the period of the grating, which both change due to mechanical and thermal strain applied to the sensor. The shift in the Bragg-wavelength is directly proportional to the strain. Researchers at NASA MSFC are currently developing techniques for using FBGs for monitoring the integrity of advanced structural materials expected to become the mainstay of the current and future generation space structures. Since carbon-epoxy composites are the materials of choice for the current space structures, the initial study is concentrated on this type of composite. The goals of this activity are to use embedded FBG sensors for measuring strain and temperature of composite structures, and to investigate the effects of various parameters such as composite fiber orientation with respect to the optical sensor, unidirectional fiber composite, fabrication process etc., on the optical performance of the sensor. This paper describes an experiment to demonstrate the use of an embedded FBG for measuring strain in a composite material. The performance of the fiber optic sensor is determined by direct comparison with results from more conventional instrumentation.

Osei, Albert J.↗

NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗

NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

computer vision↗

DOE OSTI2024

Saccharomycotina yeasts defy long-standing macroecological patterns

The Saccharomycotina yeasts (“yeasts” hereafter) are a fungal clade of scientific, economic, and medical significance. Yeasts are highly ecologically diverse, found across a broad range of environments in every biome and continent on earth; however, little is known about what rules govern the macroecology of yeast species and their range limits in the wild. Here, we trained machine learning models on 12,816 terrestrial occurrence records and 96 environmental variables to infer global distribution maps at ~1 km2 resolution for 186 yeast species (~15% of described species from 75% of orders) and to test environmental drivers of yeast biogeography and macroecology. We found that predicted yeast diversity hotspots occur in mixed montane forests in temperate climates. Diversity in vegetation type and topography were some of the greatest predictors of yeast species richness, suggesting that microhabitats and environmental clines are key to yeast diversity. We further found that range limits in yeasts are significantly influenced by carbon niche breadth and range overlap with other yeast species, with carbon specialists and species in high-diversity environments exhibiting reduced geographic ranges. Finally, yeasts contravene many long-standing macroecological principles, including the latitudinal diversity gradient, temperature-dependent species richness, and a positive relationship between latitude and range size (Rapoport’s rule). These results unveil how the environment governs the global diversity and distribution of species in the yeast subphylum. These high-resolution models of yeast species distributions will facilitate the prediction of economically relevant and emerging pathogenic species under current and future climate scenarios.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2005

The Space Technology 7 disturbance reduction system

The NASA New Millennium Program Space Technology 7 (ST7) project was selected for the purpose of flight validation of technology for minimizing disturbances on spacecraft and freely-floating test masses. Measurements of the motion of test masses are used for determining the gravitational field in its location, providing information on the nearby mass distribution or looking gravitational waves generated by distant star systems. Any unmeasured forces acting on the test mass cause a deviation from a purely gravitational trajectory and so limit the accuracy of the gravity field estimation. The ST7 project will validate the capability to eliminate unwanted forces to a level 3000 times lower than the current state of the art. The ST7 design is based on the concept of a freely-floating test mass surrounded by a spacecraft which shields the test mass from unwanted disturbances. since some disturbance of the test mass can be caused by motion of the spacecraft itself with respect to the test mass, the disturbance reduction system includes the capability of precisely measuring the position of the spacecraft with respect to the test mass and control of the spacecraft position to within 1/100 of a wavelength of light.. The overall system performance of the ST7 project will be infused into space observatories for gravitational waves such as the Laser Interferometer Space Antenna project, and into future mission for mapping the time-variable Earth gravity field. The ST7 precision control capability also has applications for separated-spacecraft interferometric imaging projects. ST7 will consist of an instrument package and a set of microthrusters, which will be attached to the European Space Agency’s LISA Pathfinder spacecraft with launch scheduled for 2008.

Folkner, W. M.↗

DOE OSTI2021

The nanoscale distribution of copper and its influence on charge collection in CdTe solar cells

For decades, Cu has been the primary dopant in CdTe photovoltaic absorbers. Typically, Cu acceptor concentrations in these devices are on the order of 1 1014 cm-3, which has made it notoriously difficult to directly correlate nanoscale Cu distributions to the local charge transport properties of these devices. To measure and correlate these properties, measurement techniques require high sensitivity to elemental concentration, large penetration depth, and operando compatibility. Techniques such as secondary-ion mass spectroscopy and X-ray energy dispersive spectroscopy are widely adopted to measure Cu concentrations, but they are limited by penetration depth, sensitivity, or spatial resolution. Additionally, they lack the operando capabilities required to correlate one-to-one Cu concentrations to electrical performance. In this work, correlative X-ray microscopy is used to investigate the spatial distribution of Cu and its impact on charge collection through the depth and breadth of CdTe photovoltaic devices. Plan-view, nanoscale X-ray fluorescence maps clearly demonstrate the spatial segregation of copper around regions thought to be CdTe grain boundaries. Complementary cross-section imaging unveils the transition of the maximum charge-collection efficiency from the ZnTe-CdTe interface to the CdS-CdTe interface as a function of Cu incorporation. The copper concentration through the depth of the CdTe layer is characterized by slow and fast diffusion components, and cross-section charge-transport modeling shows that the experimentally obtained charge collection can be explained by the modeled acceptor distribution through the depth of the CdTe layer.

14 SOLAR ENERGY↗

NASA NTRS1988

Coastal Zone Color Scanner

The Coastal Zone Color Scanner (CZCS) spacecraft ocean color instrument is capable of measuring and mapping global ocean surface chlorophyll concentration. It is a scanning radiometer with multiband capability. With new electronics and some mechanical, and optical re-work, it probably can be made flight worthy. Some additional components of a second flight model are also available. An engineering study and further tests are necessary to determine exactly what effort is required to properly prepare the instrument for spaceflight and the nature of interfaces to prospective spacecraft. The CZCS provides operational instrument capability for monitoring of ocean productivity and currents. It could be a simple, low cost alternative to developing new instruments for ocean color imaging. Researchers have determined that with global ocean color data they can: specify quantitatively the role of oceans in the global carbon cycle and other major biogeochemical cycles; determine the magnitude and variability of annual primary production by marine phytoplankton on a global scale; understand the fate of fluvial nutrients and their possible affect on carbon budgets; elucidate the coupling mechanism between upwelling and large scale patterns in ocean basins; answer questions concerning the large scale distribution and timing of spring blooms in the global ocean; acquire a better understanding of the processes associated with mixing along the edge of eddies, coastal currents, western boundary currents, etc., and acquire global data on marine optical properties.

Johnson, B.↗

NASA NTRS2008

Spatially Resolved Imaging at 350 Micrometers of Cold Dust in Nearby Elliptical Galaxies

Continuum observations at 350 micrometers of seven nearby elliptical galaxies for which CO gas disks have recently been resolved with interferometry mapping are presented. These SHARC II mapping results provide the first clearly resolved far-infrared (FIR)-to-submillimeter continuum emission from cold dust (with temperatures 31 K is approximately greater than T approximately greater than 23 K) of any elliptical galaxy at a distance greater than 40 Mpc. The measured FIR excess shows that the most likely and dominant heating source of this dust is not dilute stellar radiation or cooling flows, but rather star formation that could have been triggered by an accretion or merger event and fueled by dust-rich material that has settled in a dense region cospatial with the central CO gas disks. The dust is detected even in two cluster ellipticals that are deficient in H (sub I), showing that, unlike H (sub I), cold dust and CO in ellipticals can survive in the presence of hot X-ray gas, even in galaxy clusters. No dust cooler than 20 K, either distributed outside the CO disks or cospatial with and heated by the entire dilute stellar optical galaxy (or very extended H (sub I)), is currently evident.

photometry↗

NASA NTRS1996

Studies of Westward Electrojets and Field-Aligned Currents in the Magnetotail During Substorms: Implications for Magnetic Field Models

This section outlines those tasks undertaken in the final year that contribute integrally to the overarching project goals. Fast, during the final year, it is important to note that the project benefited greatly with the addition of a Boston University graduate student, Ms. Karen Hirsch. Jointly, we made substantial progress on the development of and improvements to magnetotail magnetic field and plasma models. The ultimate aim of this specific task was to assess critically the utility of such models for mapping low-altitude phenomena into the magnetotail (and vice-versa). The bulk of this effort centered around the finite-width- magnetotail convection model developed by and described by Spence and Kivelson (J. Geophys. Res., 98, 15,487, 1993). This analytic, theoretical model specifies the bulk plasma characteristics of the magnetotail plasma sheet (number density, temperature, pressure) across the full width of the tail from the inner edge of the plasma sheet to lunar distances. Model outputs are specified by boundary conditions of the source particle populations as well as the magnetic and electric field configuration. During the reporting period, we modified this code such that it can be interfaced with the auroral particle precipitation model developed by Dr. Terry Onsager. Together, our models provide a simple analytic specification of the equatorial distribution of fields and plasma along with their low-altitude consequences. Specifically, we have built a simple, yet powerful tool which allows us to indirectly 'map' auroral precipitation signatures (VDIS, inverted-V's, etc.) measured by polar orbiting spacecraft in the ionosphere, to the magnetospheric equatorial plane. The combined models allow us to associate latitudinal gradients measured in the ion energy fluxes at low-altitudes with the large-scale pressure gradients in the equatorial plane. Given this global, quasi-static association, we can then make fairly strong statements regarding the location of discrete features in the context of the global picture. We reported on our initial study at national and international meetings and published the results of our predictions of the low-altitude signatures of the plasma sheet. In addition, the PI was invited to contribute a publication to the so-called 'Great Debate in Space Physics' series that is a feature of EOS. The topic was on the nature of magnetospheric substorms. Specific questions of the when and where a substorm occurs and the connection between the auroral and magnetospheric components were discussed in that paper. This paper therefore was derived exclusively from the research supported by this grant. Attachment: Empirical modeling of the quite time nightside magnetosphere.' 'CRRES observations of particle flux dropout event.' The what, where, when, and why of magnetospheric substorm triggers'. and 'Low altitude signature of the plasma sheet: model prediction of local time dependence'.

Spence, Harlan E.↗

NASA NTRS2021

Colorado Ecological Forecasting: Monitoring Post-fire Cheatgrass (Bromus tectorum) Distribution to Inform Management Planning

Cheatgrass (Bromus tectorum) is a species of concern across the western United States as it has the potential to outcompete native plant species, reduce biodiversity, and diminish nutrient availability for ungulates. Furthermore, because cheatgrass can quickly dominate disturbed landscapes it has the potential to exacerbate wildfire risk by increasing fuel loads. In 2020, the Cameron Peak fire burned more than 200,000 acres on the Arapaho and Roosevelt National Forests in Colorado. These issues are of imminent concern for our partners at the Forest Service (USFS), as they are tasked with wildfire risk and invasive species mitigation. Disturbances such as wildfires can substantially increase the rate and extent of cheatgrass spread. Current cheatgrass mitigation methods rely on field crews to physically locate cheatgrass on the landscape, which takes time, money, and extensive manpower. Here, we developed two Random Forest models within the Software for Assisted Habitat Modeling (SAHM) using remote sensing predictors derived from Sentinel-2 MultiSpectral Instrument (MSI) and Shuttle Radar Topography Mission (SRTM). The first model identified suitable cheatgrass habitat while the other detected cheatgrass presence during the 2021 growing season. Topographic variables were found to be the most important in driving the habitat suitability model. Cheatgrass detection was also found to be possible within a short timespan with limited imagery surrounding a phenological shift of the plant. Maps produced from these models provide natural resource managers the ability to implement early detection and rapid response to prevent the spread of cheatgrass to new locations.

DEVELOP Tech Paper↗