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

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Observation of alpha-particles in recent D–T experiments on JET

The fusion reaction between deuterium and tritium, D(T,n) 4 He is the main source of energy in future thermonuclear reactors. Alpha-particles ( 4 He-ions) born with an average energy of 3.5 MeV transferring energy to the thermal plasma during their slowing down, should provide the self-sustained D–T plasma burn. The adequate confinement of α-particles is essential to provide efficient heating of the bulk plasma and steady burning of a reactor plasma. That is why the fusion-born α-particle studies have been a priority task in the second D–T experiments (DTE2) on the Joint European Torus (JET) to understand the main mechanisms of their slowing down, redistribution and losses and to develop optimal plasma scenarios. JET with Be-wall and W-divertor, enhanced auxiliary heating systems and improved energetic-particle diagnostic capabilities, producing significant population of α-particles, provided the possibility for comprehensive studying of the α-particle behaviour. Selected results of the confined and lost α-particle measurements, evidence of α-particle self-heating and assessments of the fusion performance are presented in this paper giving an opportunity for further modelling and extrapolation to the International Thermonuclear Experimental Reactor and burning plasma reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Error field predictability and consequences for ITER

Abstract ITER coil tolerances are re-evaluated using the modern understanding of coupling to least-stable plasma modes and an updated center-line-traced model of ITER’s coil windings. This reassessment finds the tolerances to be conservative through a statistical, linear study of n = 1 error fields (EFs) due to tilted, shifted misplacements and nominal windings of central solenoid and poloidal field coils within tolerance. We also show that a model-based correction scheme remains effective even when metrology quality is sub-optimal, and compare this to projected empirical correction schemes. We begin with an analysis of the necessity of error field correction (EFC) for daily operation in ITER using scalign laws for the EF penetration threshold. We then consider the predictability of EF dominant mode overlap across early planned ITER scenarios and, as measuring EFs in high power scenarios can pose risks to the device, the potential for extrapolation to the ITER Baseline Scenario (IBS). We find that carefully designing a scenario matching currents proportionally to those of the IBS is far more important than plasma shape or profiles in accurately measuring an optimal correction current set.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Evaluation of SPARC divertor conditions in H-mode operation using SOLPS-ITER

The predicted divertor conditions for the SPARC tokamak are calculated using SOLPS-ITER for a range of scrape-off-layer (SOL) heat flux widths λ q , input powers, and particle fueling locations. Under H-mode scenario conditions with an upstream separatrix density of 1 x 10 20 m -3 , the most conservative range of λ q extrapolations ( 0.15 mm) results in extremely high unmitigated particle and energy fluxes to the divertor, both under full field (12.2 T) and power (P SOL = 29 MW) conditions, and 2/3 field with P SOL = 10 MW. Increasing the cross-field SOL diffusivities by 2–10× reduces the magnitude of the mitigation challenge, however strategies such as impurity seeding or strike-point-sweeping will likely still be required. A combination of steady-state and time-dependent SOLPS-ITER simulations are used to map out phase space diagrams of upstream and divertor conditions. The simulations include parallel currents but neglect cross-field drifts. At low upstream density the inner and outer divertor conditions are highly asymmetric, with a large temperature difference and significant heat fluxes driven by parallel currents. The solution has sharp bifurcations with a region of hysteresis, depending on whether the initial state is at a low or high density. This behavior is observed even when the fueling location, cross-field diffusivity, and impurity level is changed, although the density window with asymmetry is reduced with increasing diffusivity. The addition of neon impurity seeding reduces the divertor heat fluxes, but also causes a drop in the upstream electron density with fixed particle throughput. This drop can be counteracted by increased main ion throughput, however too much neon results in a back transition into the asymmetric divertor regimes suggesting a need for control of both main ion and impurity seeding levels to achieve a desired divertor state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Dependence of divertor turbulence on plasma density and current in TCV

To reliably predict the distribution of heat and particle fluxes at the target plates of tokamaks, a comprehensive understanding of turbulence throughout the entire Scrape-Off-Layer (SOL) is imperative. This study examines divertor turbulence systematically across a broad parameter range on the TCV tokamak, including variations in magnetic field direction, plasma current I p ∈ [140,320] kA, edge safety factor q 95 ∈ [2.6,4.7] and Greenwald fraction f G ∈ [0.18,0.6]. The TCV X-point Gas Puff Imaging (GPI) system is used to measure 2D filament properties in the inner and outer divertor region. The fluctuation levels in the divertor are found to strongly increase with density (to 80% over most of the SOL) while remaining insensitive to I p . The previously identified divertor-localized filaments (DLF), located on the bad curvature side of the outer divertor leg, are found to be a common feature on TCV, while no filaments are observed in the PFR. DLFs are present over most of the parameter space and in both field directions. However, they are absent, or appear only closer to the target, for sufficiently large Λ div ≳ 10 or q 95 ≳ 3.7. Across both I p and f G scans, some clear trends with Λ div are found for divertor filament sizes and velocities, and with target fall-off lengths of density and heat flux profiles at the outer target. This study provides important experimental insights to turbulent transport in the divertor also for comparison with self-consistent, turbulence simulations and extrapolation to future reactor conditions.

cross-field transport↗
DOE OSTI2024

Assessing the impact of alpha particles on thermal confinement in JET D-T plasmas through global GENE-Tango simulations

The capability of the global, electromagnetic gyrokinetic GENE code interfaced with the transport Tango solver is exploited to address the impact of fusion alpha particles (in their dual role of fast particles and heating source) on plasma profiles and performance at JET in the discharges with the highest quasi-stationary peak fusion power during the DTE2 experimental campaigns. Employing radially global nonlinear electromagnetic GENE-Tango simulations, we compare results with/without alpha particles and alpha heating. Our findings reveal that alpha particles have a negligible impact on turbulent transport, with GENE-Tango converging to similar plasma profiles regardless of their inclusion as a kinetic species in GENE. On the other hand, alpha heating is found to contribute to the peaking of the electron temperature profiles, leading to a 1 keV drop on the on-axis electron temperature when alpha heating is neglected in Tango. The minimal impact of alpha particles on turbulent transport in this JET discharge–despite this being the shot with the highest fusion output–is attributed to the low content of fusion alpha in this discharge. To assess the potential impact of alpha particles on turbulent transport in regimes with higher alpha particle density, as expected in ITER and fusion reactors, we artificially increased the alpha particle concentration to levels expected for ITER. By performing global nonlinear GENE standalone simulations, we found that increasing the alpha particle density beyond five times the nominal value lead to significant overall turbulence destabilization. These results demonstrate that an increased alpha particle concentration can significantly impact transport properties under simulated JET experimental conditions. However, these findings cannot be directly extrapolated to ITER due to the substantial differences in parameters such as plasma size, magnetic field, plasma current, and thermal pressure.

energetic particles↗
DOE OSTI2025

Progress in pedestal and edge physics: Chapter 3 of the special issue: on the path to tokamak burning plasma operation

This paper describes the extensive progress that has been made in the understanding of tokamak pedestal physics since the 2007 publication of ‘Progress in the ITER Physics Basis’ (Ikeda 2007 Nucl. Fusion 47 E01–S500). It serves as Chapter 3 of the 2025 Nuclear Fusion Special Issue titled ‘On the Path to Tokamak Burning Plasma Operation’ (Campbell et al 2025 Nucl. Fusion ). This review was compiled by the pedestal and edge physics (PEP) community affiliated with the International Tokamak Physics Activity organization. It attempts to collect in one place citations to the majority of published literature on the pedestal physics topics that will be most important for the operation of a future power producing burning plasma tokamak. These include citations to publications describing the physics of the pedestal plasmas in many operating tokamaks worldwide and the pedestal physics projections for several near-term future devices including ITER. Descriptions of experimental results, interpretive modeling and predictive extrapolations are integrated together and comprehensive references are provided. This review is organized around four primary technical sections, viz.: pedestal structure, edge localized mode (ELM) characteristics, ELM control and regimes without large ELMs. Key results from many of the references are described briefly and set into the tokamak burning plasma power plant context. In addition, different perspectives on pedestal physics topics that are currently under debate within the community are also described, to provide guidance on needs for future research. Finally, attempts are made to describe conclusions from all of this progress consistent with discussions by the pedestal physics community at this time. The goal of this review is to provide a useful reference document for pedestal physics researchers going forward toward operation of a burning tokamak fusion plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Simulations of edge and SOL turbulence in diverted negative and positive triangularity plasmas

Optimizing the performance of magnetic confinement fusion devices is critical to achieving an attractive fusion reactor design. Negative triangularity (NT) scenarios have been shown to achieve excellent levels of energy confinement, while avoiding edge localized modes. Modeling turbulent transport in the edge and SOL is key in understanding the impact of NT on turbulence and extrapolating the results to future devices and regimes. Previous gyrokinetic turbulence studies have reported beneficial effects of NT across a broad range of parameters. However, most simulations have focused on the inner plasma region, neglecting the impact of NT on the outermost edge. In this work, we investigate the effect of NT in edge and scrape-off layer simulations, including the magnetic X-point and separatrix. For the first time, we employ a multi-fidelity approach, combining global, non-linear gyrokinetic simulations with drift-reduced fluid simulations, to gain a deeper understanding of the underlying physics at play. First-principles simulations using the GENE-X code demonstrate that in comparable NT and PT geometries, similar profiles are achieved, while the turbulent heat flux is reduced by more than 50% in NT. Comparisons with results from the drift-reduced fluid turbulence code GRILLIX suggest that the turbulence is driven by trapped electron modes. The parallel heat flux width on the divertor targets is reduced in NT, primarily due to a lower spreading factor S.

GENE-X↗
DOE OSTI2026

Radiation modeling and experimental validation of sub-cyclotron frequency microwave synchrotron radiation as a diagnostic tool for runaway electrons in present and future tokamaks

The microwave synchrotron radiation in the sub-cyclotron frequency region has been systematically validated as a diagnostic method for runaway electrons (>1 MeV) with radiation modeling and experiments on the DIII-D tokamak. Experimental observations reveal that sub-cyclotron frequency microwave radiation emerges only after runaway electrons are excited during plasma disruptions. Electron gyro-magnetic radiation modeling confirms that only runaway electrons with energies exceeding 1 MeV can emit radiation in the observed sub-cyclotron frequency band on DIII-D. The synchrotron Razin and Beaming effects are modeled in both the sub-cyclotron and standard Electron Cyclotron Emission (ECE) frequency region. Due to the pronounced beaming effect, the modeling supports that a standard ECE system is insensitive to synchrotron radiation from beamed runaway electrons (p ∥ >> p ⟂ ), but very sensitive to ECE radiation from isotropic suprathermal electrons (100 keV or less). DIII-D experiments further show that combining ECE and sub-cyclotron receivers reveals new insights into transient runaway dynamics during the plateau phase. Certain transient crash events appear only in the sub-cyclotron band or lead to opposite changes on the sub-cyclotron and standard ECE signals, supporting models where transient MHD events can exert a different effect on electrons of different energy levels. This novel diagnostic technique offers a powerful tool for studying and detecting runaway electron dynamics in both present-day and high-field future tokamaks. The diagnostic approach has been extrapolated to the SPARC tokamak, where sub-cyclotron radiation is predicted to respond sensitively and solely to runaway electrons during SPARC’s L-mode startup phase.

Yu, Guanying [Hefei Comprehensive National Science↗
DOE OSTI2026

Towards fully predictive gyrokinetic full- f simulations: validation and triangularity studies in TCV

Designing economical magnetic confinement fusion power plants motivates computational tools that can estimate plasma behavior from engineering parameters without direct reliance on experimental measurement of the plasma profiles. In this work, we present full-f global long-wavelength gyrokinetic simulations of edge and scrape-off layer turbulence in tokamaks that use only magnetic geometry, heating power, and particle inventory as inputs. Unlike many modeling approaches that employ free parameters fitted to experimental data, raising uncertainties when extrapolating to reactor scales. This approach directly simulates turbulence and resulting profiles through gyrokinetics without such empirical adjustments. This is achieved via an adaptive sourcing algorithm in Gkeyll that strictly controls energy injection and emulates particle sourcing due to neutral recycling. We show that the simulated kinetic profiles compare reasonably well with Thomson scattering and Langmuir probe data for Tokamak á Configuration Variable (TCV) discharge #65125, and that the simulations reproduce characteristic features such as blob transport and self-organized electric fields. Applying the same framework to study triangularity effects suggests mechanisms contributing to the improved confinement reported for negative triangularity (NT). Simulations of TCV discharges #65125 and #65130 indicate that NT increases the E x B flow shear (by about 20% in these cases), which correlates with reduced turbulent losses and a modest change in the distribution of power exhaust to the vessel wall. While the physical models contain approximations that can be refined in future work, the predictive capability demonstrated here, evolving multiple profile relaxation times with kinetic electron and ion models in hundreds of GPU hours, indicates the feasibility of using Gkeyll to support design studies of fusion devices.

Hoffmann, Antoine Cyril David [Princeton Plasma Ph↗
DOE OSTI2026

Variability of MHD instabilities in benign termination of high-current runaway electron beams in the JET and DIII-D tokamaks

Benign termination, in which magnetohydrodynamic (MHD) instabilities deconfine runaway electrons (REs) following hydrogenic injections, is a promising strategy for mitigating dangerous RE loads after disruptions. Recent experiments on the Joint European Torus (JET) have explored this scenario at higher pre-disruptive plasma currents than are achievable on other devices, revealing challenges in obtaining benign terminations at I p ≥2.5 MA. This work analyzes the evolution of these high-current RE beams and their terminating MHD events using fast magnetic sensor measurements and EFIT equilibrium reconstructions for approximately 40 JET and 20 DIII-D tokamak discharges. On JET, unsuccessful non-benign terminations occur at low edge safety factor (q edge ≈ 2), and are preceded by intermittent, non-terminating MHD events at higher rational qedge. Trends in the internal inductance I i indicate more peaked RE current profiles in the high-I p non-benign population, which may hinder successful recombination through re-ionization of the companion plasma. In contrast, benign terminations on JET typically occur at higher q edge ≥3 and exhibit less peaked RE current profiles. DIII-D displays a broader range of terminating edge safety factors, again correlated with the measured values. Across both tokamaks, the RE current peaking is therefore found to determine which MHD instability boundary is encountered, a result confirmed by linear resistive MHD modeling with the CASTOR3D code. Measured growth rates are similar for benign and non-benign cases, indicating that ideal MHD timescales at low density after hydrogenic injection do not alone explain efficient RE deconfinement. Instead, non-benign cases are most readily characterized by their comparably lower overall MHD perturbation amplitudes δB. These observations suggest that the interplay between ideal and resistive dynamics governs the termination process, with implications for extrapolating benign RE termination to high-I p reactor scenarios.

MHD instabilities↗
DOE OSTI2026

Understanding carbon sourcing and transport originating from the helicon antenna surfaces during high-power helicon discharge in DIII-D Tokamak

The high-power helicon wave system in the DIII-D tokamak could potentially introduce new plasma–material interaction (PMI) challenges owing to rectified RF sheath potentials that develop near the antenna and surrounding plasma-facing components. We present the first application of the STRIPE (Simulated Transport of RF Impurity Production and Emission) framework to helicon-induced PMIs, extending previous STRIPE studies of ICRH antennas by incorporating net erosion, local re-deposition, and three-dimensional global impurity transport. The integrated workflow couples SOLPS, COMSOL, RustBCA, GITR, and GITRm to simulate carbon erosion, re-deposition, and impurity transport for two experimentally constrained DIII-D H-mode helicon operating scenarios with different antenna–plasma gaps, coupled RF powers, and edge plasma conditions. COMSOL predicts rectified RF sheath potentials of 1–5 kV localized near the lower portion of the antenna, where the magnetic field intersects the surface at grazing incidence. Carbon self-sputtering dominates the erosion source, whereas RF-accelerated D + ions contribute approximately 1% of the total gross erosion. The smaller-gap operating scenario exhibits substantially stronger gross erosion, enhanced local re-deposition (∼12%), and a larger confined carbon inventory owing to increased plasma accessibility and broader RF sheath coverage. Comparison with available DIII-D measurements shows no distinct change in the global carbon signal that correlates with the helicon RF pulse, consistent with the simulations indicating that the helicon-generated carbon source remains small compared with the existing background carbon inventory under the present graphite-wall operating conditions. These results demonstrate the capability of STRIPE to integrate RF sheath modeling, plasma transport, surface interaction physics, and three-dimensional impurity transport for the interpretation of helicon-induced PMIs. The study further identifies the principal sources of modeling uncertainty, including grazing-angle RF sheath physics, slow-wave resolution, plasma-background extrapolation, and trace-impurity transport assumptions, providing a framework for future validation and model development.

Kumar, Atul [Oak Ridge National Laboratory (ORNL),↗
DOE OSTI2025

GRAPH — an readout ASIC for large MCP based detectors

We present a programmable 16 channel, mixed signal, low power readout ASIC, having the project historically named Gigasample Recorder of Analog waveforms from a PHotodetector (GRAPH). It is designed to read large aperture single photon imaging detectors using micro channel plates for charge multiplication, and measuring the detector's response on crossed strips anodes to extrapolate the incoming photon position. Each channel consists of a fast, low power and low noise charge sensitive amplifier, which provides a myriad of coarse and fine programmable options for gain and shaping settings. Further, the amplified signal is recorded using, to our knowledge novel, the Hybrid Universal sampLing Architecture (HULA) ADC. A kind of mixed signal double buffer memory, that enables concurrent waveform recording, and selected event digitized data extraction. The sampling frequency is freely adjustable between few kHz up to 125 MHz, while the chip's internal digital memory holds a history 2048 samples for each channel, with a digital headroom of 12 bits. An optimized region of interest sample-read algorithm allows to extract the information just around the event pulse peak, while selecting the next event, thus substantially reducing the operational dead time. The chip is designed in 130 nm TSMC CMOS technology, and its power consumption is around 47 mW per channel.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Measurement of the mean excitation energy of liquid argon

The mean excitation energy (I-value) of liquid argon is a critical input for energy estimation in neutrino oscillation experiments. It is measured to be 199 +4 -5 eV using the range of 402.2 MeV protons from the Fermilab Linac. This compares to the author's recent evaluation of (197 ± 7) eV based on a combination of an oscillator strength distribution analysis, gaseous argon range measurements, sparse stopping power data on solid argon, and an extrapolation of data on the effect of phase from other substances. Using all sources of information, we recommend a value of (198 ± 4) eV for liquid argon, which is significantly higher than 188 eV, from ICRU-37's gaseous argon evaluation, commonly used in Monte Carlo codes such as Geant4.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Cryogenic light detectors with thermal signal amplification for 0 νββ search experiments

As a step towards the realization of cryogenic-detector experiments to search for neutrinoless double-beta decay (such as CROSS, BINGO, and CUPID), we investigated a batch of 10 Ge light detectors (LDs) assisted by Neganov-Trofimov-Luke (NTL) signal amplification. Each LD was assembled with a large cubic light-emitting crystal (45 mm side) using the recently developed CROSS mechanical structure. The detector array was operated at milli-Kelvin temperatures in a pulse-tube cryostat at the Canfranc underground laboratory in Spain. We achieved good performance with scintillating bolometers from CROSS, made of Li 2 100 MoO 4 crystals and used as reference detectors of the setup, and with all LDs tested (except for a single device that encountered an electronics issue). No leakage current was observed for 8 LDs with an electrode bias up to 100 V. Operating the LDs at an 80 V electrode bias applied in parallel, we obtained a gain of around 9 in the signal-to-noise ratio of these devices, allowing us to achieve a baseline noise RMS of O(10 eV). Thanks to the strong current polarization of the temperature sensors, the time response of the devices was reduced to around half a millisecond in rise time. The achieved performance of the LDs was extrapolated via simulations of pile-up rejection capability for several configurations of the CUPID detector structure. Despite the sub-optimal noise conditions of the LDs (particularly at high frequencies), we demonstrated that the NTL technology provides a viable solution for background reduction in CUPID.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Bayesian parameter estimation and evaluation of the K -ω shear stress transport model for plane impinging jets

Numerical simulations with semi-empirical turbulence models are commonly used to model impinging jets, often used for cooling solid surfaces. In this work, the constants in the k-ω shear stress transport model in ANSYS FLUENT are calibrated to experimental velocity and heat transfer data for a plane turbulent impinging air jet to determine if Kennedy-O'Hagan calibration (Kennedy and O'Hagan 2001 J. R. Stat. Soc. B 63 425–64) can improve predictions of near-surface velocities and surface Nusselt numbers for similar flows. Impinging jets have been proposed to cool the target plates of the divertor in future magnetic fusion energy reactors, where simulations are used to estimate divertor performance. The flat-plate divertor (Wang et al 2009 Fusion Sci. Technol .56 1023–7) uses a plane jet of helium issuing from a B = 0.5 mm slot to cool a surface with radius of curvature of 44 B at a distance 4 B from the slot. Predictions from the calibrated numerical model are compared with independent experimental data at different flow conditions, as well as surface temperature data for a flat plate divertor test section. The contribution of this work is evaluation of the accuracy of a calibrated turbulence model for modest extrapolations in flow geometry and flow conditions for a plane impinging jet.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗
DOE OSTI2024

Active causal learning for decoding chemical complexities with targeted interventions

Abstract Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Deep-learning-based canopy height model generation from sub-meter resolution panchromatic satellite imagery

Canopy height models (CHMs) with sufficient resolution to distinguish individual trees are useful for a variety of applications. However, standard techniques to acquire such data, such as airborne lidar surveying, are often prohibitively expensive. Deep learning techniques for generating CHMs from high-resolution imagery are an attractive option to reduce costs. To date, success with these methods has been demonstrated using multichannel aerial photography and specialized satellite data products derived from multiple sensors, neither of which is commonly available at temporal resolutions finer than one year. Here we demonstrate a method to generate sub-meter resolution CHMs in three forests in California using a more abundant data source: sub-meter resolution, panchromatic satellite imagery from a single sensor. We show that phenology and species composition play important roles in model transferability; when trained using imagery from a single conifer forest in autumn, the model performs well on autumn imagery from a second conifer forest several hundred kilometers distant with no re-training. With modest additions to the training dataset, the same model generates minimally biased estimates of canopy height in both conifer and deciduous forests during multiple seasons. Because the model operates on satellite data with global coverage and a relatively short return interval, we propose its suitability to extrapolate tree-level canopy height data to remote regions and conduct high-temporal resolution monitoring of forest structure. We furthermore demonstrate the workflow’s applicability to fire modeling by conducting simulations in forests populated by trees measured using both this approach and airborne lidar surveying. We find minimal differences in fire behavior relative to a baseline case in which only statistical distributions of tree height and crown area are known. This result underscores the value of forest structural information derived from our workflow for improving the fidelity of wildland fire simulations, among other ecological applications.

54 ENVIRONMENTAL SCIENCES↗