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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↗

NASA NTRS2021

Mass Inferencing Model Creation And Deployment To Lunar Excavation Robot, RASSOR

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. This research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. Radio wave propagation time to the Moon and back is ~2.56 seconds. Though teleoperation is possible with this delay, autonomous capability that enables RASSOR to plan and execute excavation missions intelligently and efficiently is preferred. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation (e.g. knowledge of whether drums are full informs the task of highest priority, whether it be continuing to dig, or returning to a processing plant to offload regolith). A configurable data reduction and analysis pipeline was created to allow for straightforward incorporation of new data, such as that from lunar excavation, to improve model performance in new environments. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All four models take in system states and output a mass prediction for each set of the robot’s bucket drums. Initial results from deployment to RASSOR and testing in a simulated lunar environment show that the models have <10% mean error during robot operation. Future work includes refinement of a model that estimates regolith mass in real-time during excavation as well as further testing of the developed models on the hardware.

ROS↗

DOE OSTI2023

Mapping Glacier Basal Sliding Applying Machine Learning

During the RESOLVE project (“High-resolution imaging in subsurface geophysics: development of a multi-instrument platform for interdisciplinary research”), continuous surface displacement and seismic array observations were obtained on Glacier d’Argentière in the French Alps for 35 days in May 2018. The data set is used to perform a detailed study of targeted processes within the highly dynamic cryospheric environment. In particular, the physical processes controlling glacial basal motion are poorly understood and remain challenging to observe directly. Especially in the Alpine region for temperate based glaciers where the ice rapidly responds to changing climatic conditions and thus, processes are strongly intermittent in time and heterogeneous in space. Spatially dense seismic and Global Positioning System (GPS) measurements are analyzed applying machine learning to gain insight into the processes controlling glacial motions of Glacier d’Argentière. Using multiple bandpass-filtered copies of the continuous seismic waveforms, we compute energy-based features, develop a matched field beamforming catalog and include meteorological observations. Features describing the data are analyzed with a gradient boosting decision tree model to directly estimate the GPS displacements from the seismic noise. We posit that features of the seismic noise provide direct access to the dominant parameters that drive displacement on the highly variable and unsteady surface of the glacier. The machine learning model infers daily fluctuations and longer term trends. The results show on-ice displacement rates are strongly modulated by activity at the base of the glacier. The techniques presented provide a new approach to study glacial basal sliding and discover its full complexity.

58 GEOSCIENCES↗

NASA NTRS1993

Observational and modeling studies of heat, moisture, precipitation, and global-scale circulation patterns

The research sponsored by this grant is a continuation and an extension of the work conducted under a previous contract, 'South Pacific Convergence Zone and Global-Scale Circulations'. In the prior work, we conducted a detailed investigation of the South Pacific convergence zone (SPCZ), and documented many of its significant features and characteristics. We also conducted studies of its interaction with global-scale circulation features through the use of both observational and modeling studies. The latter was accomplished toward the end of the contract when Dr. James Hurrell, then a Ph.D. candidate, successfully ported the NASA GLA general circulation model (GCM) to Purdue University. In our present grant, we have expanded our previous research to include studies of other convectively-driven circulation systems in the tropics besides the SPCZ. Furthermore, we have continued to examine the relationship between these convective systems and global-scale circulation patterns. Our recent research efforts have focused on three objectives: (1) determining the periodicity of large-scale bands of organized convection in the tropics, primarily synoptic to intraseasonal time scales in the Southern Hemisphere; (2) examining the relative importance of tropical versus mid-latitude forcing for Southern Hemisphere summertime subtropical jets, particularly over the Pacific Ocean; and (3) estimating tropical precipitation, especially over oceans, using observational and budget methods. A summary list of our most significant accomplishments in the past year is given.

Vincent, Dayton G.↗

NASA NTRS1989

Preliminary base heating environments for a generalized ALS LO2/LH2 launch vehicle, appendix 1 and 2

A secondary objective of contract NAS8-39141 is to provide base heating assessments, as required, to support Advanced Launch System (ALS) preliminary launch vehicle and propulsion system design studies. The ALS propulsion systems integration working group meeting (No. 3) recently completed in San Diego, California, focused attention on the need for base heating environment determination to provide preliminary requirements for LO2/LH2 propulsion systems currently being considered for ALS. We were requested to provide these environments for a range of possible propellant mixture and nozzle area ratios. Base heating environments can only be determined as a function of altitude when the engine operating conditions and vehicle base region geometry (engine arrangement) are known. If time dependent environments are needed to assess thermal loads, a trajectory must also be provided. These parameters are not fixed at this time since the ALS configurations and propulsion operating conditions are varied and continue to be studied by Phase B contractors. Therefore, for this study, a generalized LO2/LH2 system was selected along with a vehicle configuration consisting of a seven-engine booster and a three-engine core. MSFC provided guidance for the selection. We also selected a limited number of body points on the booster and core vehicles and engines for the environment estimates. Environments at these locations are representative of maximum heating conditions in the base region and are provided as a function of altitude only. Guidelines and assumptions for this assessment, methodology for determining the environments, and preliminary results are provided in this technical note. Refinements in the environments will be provided as the ALS design matures.

Bender, Robert L.↗

DOE OSTI2021

Using non-invasive MEMS pressure sensors for measuring building envelope air leakage

Micro-electromechanical systems (MEMS)-based sensors have seen significant improvements in accuracy and cost over the past several years, and due to the need for altitude sensing in unmanned aerial vehicles and wearable technologies, absolute pressure sensors have shown the most dramatic improvements. This paper investigates applications of MEMS sensors in commercial buildings, including pairing two absolute pressure sensors to determine differential pressures between different locations in and around buildings. Differential pressure measurements are commonly made in commercial buildings for a number of applications, including static pressure measurements for variable-speed supply fan control, air balancing in hospitals, and for envelope and duct air leakage testing. This paper focuses specifically on envelope air-leakage testing applications of these sensors. The use of continuous pressure measurements in addition to one-time non-intrusive outdoor airflow measurements of rooftop packaged units is investigated. A comparison with standardized leakage testing indicated that continuous measurements with MEMS pressure-sensors were able to estimate envelope leakage to within 3–16% of the standardized test result. In addition, the magnitude and stability of differential pressure differences that can be resolved with absolute pressure sensors are also investigated in the laboratory and the field. Results show that the sensors can be effectively used for pressures seen in low rise buildings with rooftop units.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2026

Autonomous monitoring of algal biomass: Success stories and lessons learned from long-term field deployment

Autonomous, high-frequency monitoring of outdoor algal ponds is needed to quantify biomass productivity and detect culture decline in environments prone to contamination, grazers, and variable operating conditions. We report successes and lessons learned in translating a laboratory spectroradiometric monitoring approach to a multi-year autonomous field deployment at the Arizona Center for Algae Technology and Innovation (AzCATI). The system measures spectrally resolved pond reflectance by ratioing upwelling radiance from each raceway to simultaneous downwelling sky irradiance using fiber-coupled spectrometers. A physics-based reflectance model (ASHARP) is fit to each spectrum pair to estimate optical parameters, including a biomass-proxy coefficient (C a ) which enables near-real-time tracking of biomass accumulation and culture state at 2–5 min intervals. From May 2022 through September 2025 the platform operated continuously while scaling from two to six raceway ponds. Several strains of algae were monitored successfully, including the high productivity Tetraselmis striata and Picochlorum celeri. Transitioning data acquisition from a Windows laptop to a Raspberry Pi improved uptime from 57% (2022) to ~89% (2024–2025) and enabled routine real-time analysis. Further, we converted relative biomass estimates to absolute ash-free dry weight (AFDW) using experimentally-derived calibrations, providing field-relevant biomass predictions with conservative confidence bounds. These results demonstrate the feasibility of long-term, autonomous optical monitoring for well-mixed open-raceway algal cultivation and provide practical guidance for reliable field operation and scaling.

Katinas, Christopher Michael [Sandia National Labo↗

NASA NTRS1978

Lidar observations of wave-like structure in the atmospheric sodium layer

The University of Illinois (Urbana) lidar system has been developed to study the atmospheric sodium layer near 90 km altitude through the mechanism of resonance scattering. The photocount data are processed using digital smoothing filters to obtain continuous estimates of the sodium density versus altitude. The filter cutoff frequency is related to the height resolution and accuracy of the estimated profile. Lidar photocount data processed using this filtering technique show wave-like structures in the sodium layer which move downward with time. The waves have typical wavelengths of 3-15 km and phase velocities of less than 1 m/sec. The movement of these structures seems to be independent of the motion of the bottomside of the layer, which also has been observed to move up or down by as much as 2 km over a period of a few hours.

Rowlett, J. R.↗

NASA NTRSDate not supplied

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

NASA NTRS2004

Global Lightning Activity

Our knowledge of the global distribution of lightning has improved dramatically since the advent of spacebased lightning observations. Of major importance was the 1995 launch of the Optical Transient Detector (OTD), followed in 1997 by the launch of the Lightning Imaging Sensor (LIS). Together, these instruments have generated a continuous eight-year record of global lightning activity. These lightning observations have provided a new global perspective on total lightning activity. For the first time, total lightning activity (cloud-to-ground and intra-cloud) has been observed over large regions with high detection efficiency and accurate geographic location. This has produced new insights into lightning distributions, times of occurrence and variability. It has produced a revised global flash rate estimate (44 flashes per second) and has lead to a new realization of the significance of total lightning activity in severe weather. Accurate flash rate estimates are now available over large areas of the earth (+/- 72 deg. latitude). Ocean-land contrasts as a function of season are clearly reveled, as are orographic effects and seasonal and interannual variability. The space-based observations indicate that air mass thunderstorms, not large storm system dominate global activity. The ability of LIS and OTD to detect total lightning has lead to improved insight into the correlation between lightning and storm development. The relationship between updraft development and lightning activity is now well established and presents an opportunity for providing a new mechanism for remotely monitoring storm development. In this concept, lightning would serve as a surrogate for updraft velocity. It is anticipated that this capability could lead to significantly improved severe weather warning times and reduced false warning rates. This talk will summarize our space-based lightning measurements, will discuss how lightning observations can be used to monitor severe weather, and present a concept for continuous geostationary-based lightning observations.

Christian, Hugh J.↗

DOE OSTI2026

Variational Optical Phase Learning on a Continuous-Variable Quantum Compiler

Quantum process learning is a fundamental primitive that draws inspiration from machine learning with the goal of better studying the dynamics of quantum systems. One approach to quantum process learning is quantum compilation, whereby an analog quantum operation is digitized by compiling it into a series of basic gates. While there has been significant focus on quantum compiling for discrete-variable systems, the continuous-variable (CV) framework has received comparatively less attention. We present an experimental implementation of a CV quantum compiler that uses two-mode squeezed light to learn a Gaussian unitary operation. We demonstrate the compiler by learning a parameterized linear phase unitary through the use of target and control phase unitaries to demonstrate a factor of 5.4 increase in the precision of the phase estimation and a 3.6-fold acceleration in the time-to-solution metric when leveraging quantum resources. We further show how our approach can be extended to higher-dimensional compilation tasks. Our results are enabled by the tunable control of our cost landscape via variable squeezing, thus providing a critical framework to simultaneously increase precision and reduce time-to-solution.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2002

Analysis of TRMM 3-Hourly Multi-Satellite Precipitation Estimates Computed in Both Real and Post-Real Time

Satellite data form the core of the information available for estimating precipitation on a global basis. While it is possible to create such estimates solely from one sensor, researchers have increasingly moved to using combinations of sensors in an attempt to improve accuracy, coverage, and resolution. This poster updates a long-term project in which the authors are working to provide routine combined-sensor estimates of precipitation over the entire globe at relatively fine time and space intervals. The goal is to produce these globally complete precipitation estimates on a 25-km grid every 3 hours. Since late January 2002 we have been estimating precipitation for the latitude band 50 degrees N-S within about 6 hours of observation time. This work is 1 of only 2 or 3 such efforts in the world. Now we are preparing to provide similar estimates for the last 5 years. All of this work is being carried out as part of the Tropical Rainfall Measuring Mission (TRMM). Initially, TRMM was focused on providing excellent long-term averages of precipitation in tropical regions, but since its launch in November 1997 continued research has allowed the same satellite and data system to be used for addressing weather-scale problems as well.

Huffman, George J.↗

NASA NTRS1999

Far Ultraviolet Imaging from the Image Spacecraft: System Design - 1

Direct imaging of the magnetosphere by the IMAGE spacecraft A,ill be supplemented by observation of the global aurora, the footprint of magnetospheric regions. To assure the simultaneity of these observations and tile measurement of the magnetospheric back-round neutral gas density, the IMAGE satellite instrument complement includes three Far Ultraviolet (FUV) instruments. In tile wavelength region 120-1 90 nm. a downward-viewing aurora imager is only minimally contaminated sunlight, scattered from clouds and ground, and radiance of the aurora observed in a nadir viewing geometry can be observed in the presence of the high-latitude day-low. Tile Wideband Imaging Camera (WIC) will provide broadband ultraviolet images of the aurora for maximum spatial and temporal resolution by imaging the LBH N2 bands of the aurora. The Spectrographic Imager (SI), a monochromatic imager, will image different types of aurora, filtered by wavelength. By measuring the Doppler-shifted Lyman-alpha, the proton-induced component of the aurora will be imaged separately. Finally, the GEO instrument will observe the distribution of the geocoronal emission, which is a measure of the neutral background density source of the charge exchange in the magnetosphere. The FUV instrument complement looks radially outward from the rotating IMAGE satellite and, therefore, it spends only a short time observing tile aurora and the Earth during, each spin. Detailed descriptions of the WIC, Si, GEO, and their individual performance validations are discussed in companion papers. This paper summarizes the system requirements and system design approach taken to satisfy the science requirements. One primary requirement is to maximize photon collection efficiency and use efficiently tile short time available foe exposures. The FUV auroral imagers WIC and SI both have wide fields of view and take data continuously as the auroral region proceeds through the field of view. To minimize data volume, multiple images are taken and electronically co-added by suitably shifting each image to compensate for the spacecraft rotation. In order to minimize resolution loss, the images have to be distortion-corrected in real time foe both WIC and Si prior to co-adding. The distortion correction is accomplished using high-speed look Lip tables that are pre-generated by least square fitting to polynomial functions by the on-orbit processor. The instruments were calibrated individually while on stationary platforms, mostly in vacuum chambers as described in the companion papers. Extensive -round-based testing was performed with visible and near UV simulators mounted oil a rotating platform to estimate their on-orbit performance. The predicted instrument system performance is summarized and some of the preliminary data formats are shown.

Mende, S. B.↗

DOE OSTI2024

Hamiltonian learning using machine-learning models trained with continuous measurements

Here, we build upon recent work on the use of machine-learning models to estimate Hamiltonian parameters using continuous weak measurement of qubits as input. We consider two settings for the training of our model: (1) supervised learning, where the weak-measurement training record can be labeled with known Hamiltonian parameters, and (2) unsupervised learning, where no labels are available. The first has the advantage of not requiring an explicit representation of the quantum state, thus potentially scaling very favorably to a larger number of qubits. The second requires the implementation of a physical model to map the Hamiltonian parameters to a measurement record, which we implement using an integrator of the physical model with a recurrent neural network to provide a model-free correction at every time step to account for small effects not captured by the physical model. We test our construction on a system of two qubits and demonstrate accurate prediction of multiple physical parameters in both the supervised context and the unsupervised context. We demonstrate that the model benefits from larger training sets, establishing that it is “learning,” and we show robustness regarding errors in the assumed physical model by achieving accurate parameter estimation in the presence of unanticipated single-particle relaxation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Cost‐benefit assessment framework for robotics‐driven inspection of floating offshore wind farms

Abstract Operations and maintenance (O&M) of floating offshore wind farms (FOWFs) poses various challenges in terms of greater distances from the shore, harsher weather conditions, and restricted mobility options. Robotic systems have the potential to automate some parts of the O&M leading to continuous feature‐rich data acquisition, operational efficiency, along with health and safety improvements. There remains a gap in assessing the techno‐economic feasibility of robotics in the FOWF sector. This paper investigates the costs and benefits of incorporating robotics into the O&M of a FOWF. A bottom‐up cost model is used to estimate the costs for a proposed multi‐robot platform (MRP). The MRP houses unmanned aerial vehicle (UAV) and remotely operated vehicle (ROV) to conduct the inspection of specific FOWF components. Emphasis is laid on the most conducive O&M activities for robotization and the associated technical and cost aspects. The simulation is conducted in Windfarm Operations and Maintenance cost‐Benefit Analysis Tool (WOMBAT), where the metrics of incurred operational expenditure (OPEX) and the inspection time are calculated and compared with those of a baseline case consisting of crew transfer vessels, rope‐access technicians, and divers. Results show that the MRP can reduce the inspection time incurred, but this reduction has dependency on the efficacy of the robotic system and the associated parameterization e.g., cost elements and the inspection rates. Conversely, the increased MRP day rate results in a higher annualized OPEX. Residual risk is calculated to assess the net benefit of incorporating the MRP. Furthermore, sensitivity analysis is conducted to find the key parameters influencing the OPEX and the inspection time variation. A key output of this work is a robust and realistic framework which can be used for the cost‐benefit assessment of future MRP systems for specific FOWF activities.

17 WIND ENERGY↗

DOE OSTI2021

Sea Level-Driven Marsh Migration Results in Rapid Net Loss of Carbon

Sea level rise alters coastal carbon cycling by driving the rapid migration of coastal ecosystems, salinization of freshwater systems, and replacement of terrestrial forests with tidal wetlands. Wetland soils accumulate carbon (C) at faster rates than terrestrial soils, implying that sea level rise may lead to enhanced carbon accumulation. Here, we show that carbon stored in tree biomass greatly exceeds carbon stored in adjacent marsh soils so that marsh migration reduces total carbon stocks by ~50% in less than 100 years. Continued marsh soil carbon accumulation may eventually offset forest carbon loss, but we estimate that the time for replacement is similar to estimates of marsh survival (i.e., centuries), which suggests that forest C may never be replaced. These findings reveal a critical C source not included in coastal C budgets driven by migrating ecosystems and rapidly shifting allocations between carbon stored in soils and biomass.

58 GEOSCIENCES↗

NASA NTRS1972

Control of linear uncertain systems utilizing mismatched state observers

The control of linear continuous dynamical systems is investigated as a problem of limited state feedback control. The equations which describe the structure of an observer are developed constrained to time-invarient systems. The optimal control problem is formulated, accounting for the uncertainty in the design parameters. Expressions for bounds on closed loop stability are also developed. The results indicate that very little uncertainty may be tolerated before divergence occurs in the recursive computation algorithms, and the derived stability bound yields extremely conservative estimates of regions of allowable parameter variations.

Goldstein, B.↗

NASA NTRS1987

Methods for extracting aerodynamic accelerations from Orbiter High Resolution Accelerometer Package flight data

This report presents a process for extracting the aerodynamic accelerations of the Shuttle Orbiter Vehicle from the High Resolution Accelerometer Package (HiRAP) flight data during reentry. The methods for obtaining low-level aerodynamic accelerations, principally in the rarefied flow regime, are applied to 10 Orbiter flights. The extraction process is presented using data obtained from Space Transportation System Flight 32 (Mission 61-C) as a typical example. This process involves correcting the HiRAP measurements for the effects of temperature bias and instrument offset from the Orbiter center of gravity, and removing acceleration data during times they are affected by thruster firings. The corrected data are then made continuous and smooth and are further enhanced by refining the temperature bias correction and removing effects of the auxiliary power unit actuation. The resulting data are the current best estimate of the Orbiter aerodynamic accelerations during reentry and will be used for further analyses of the Orbiter aerodynamics and the upper atmosphere characteristics.

Thompson, J. M.↗