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All sourcesNASA NTRSDOE OSTI
NASA NTRS1975

Investigation to develop a multistage forest sampling inventory system using ERTS-1 imagery

The author has identified the following significant results. The annotation system produced a RMSE of about 200 m ground distance in the MSS data system with the control data used. All the analytical MSS interpretation models tried were highly significant. However, the gains in forest sampling efficiency that can be achieved by using the models vary from zero to over 50 percent depending on the area to which they are applied and the sampling method used. Among the sampling methods tried, regression sampling yielded substantial and the most consistent gains. The single most significant variable in the interpretation model was the difference between bands 5 and 7. The contrast variable, computed by the Hadamard transform was significant but did not contribute much to the interpretation model. Forest areas containing very large timber volumes because of large tree sizes were not separable from areas of similar crown cover but containing smaller trees using ERTS image interpretation only. All correlations between space derived timber volume predictions and estimates obtained from aerial and ground sampling were relatively low but significant and stable. There was a much stronger relationship between variables derived from MSS and U2 data than between U2 and ground data.

Langley, P. G.↗
NASA NTRS1991

A new system model for radar polarimeters

The validity of the 2 x 2 receive R and transmit T model for radar polarimeter systems, first proposed by Zebker et al. (1987), is questioned. The model is found to be invalid for many practical realizations of radar polarimeters, which can lead to significant errors in the calibration of polarimetric radar images. A more general model is put forward, which addresses the system defects which cause the 2 x 2 model to break down. By measuring one simple parameter from a polarimetric active radar calibration (PARC), it is possible to transform the scattering matrix measurements made by a radar polarimeter to a format compatible with a 2 x 2 R and T matrix model. Alternatively, the PARC can be used to verify the validity of the 2 x 2 model for any polarimetric radar system. Recommendations for the use of PARCs in polarimetric calibration and to measure the orientation angle of the horizontal (H) and vertical (V) coordinate system are also presented.

Freeman, Anthony↗
NASA NTRS1991

The fractional Fourier transform and applications

This paper describes the 'fractional Fourier transform', which admits computation by an algorithm that has complexity proportional to the fast Fourier transform algorithm. Whereas the discrete Fourier transform (DFT) is based on integral roots of unity e exp -2(pi)i/n, the fractional Fourier transform is based on fractional roots of unity e exp -2(pi)i(alpha), where alpha is arbitrary. The fractional Fourier transform and the corresponding fast algorithm are useful for such applications as computing DFTs of sequences with prime lengths, computing DFTs of sparse sequences, analyzing sequences with noninteger periodicities, performing high-resolution trigonometric interpolation, detecting lines in noisy images, and detecting signals with linearly drifting frequencies. In many cases, the resulting algorithms are faster by arbitrarily large factors than conventional techniques.

Bailey, David H.↗
NASA NTRS2013

Mixture-Tuned, Clutter Matched Filter for Remote Detection of Subpixel Spectral Signals

Mapping localized spectral features in large images demands sensitive and robust detection algorithms. Two aspects of large images that can harm matched-filter detection performance are addressed simultaneously. First, multimodal backgrounds may thwart the typical Gaussian model. Second, outlier features can trigger false detections from large projections onto the target vector. Two state-of-the-art approaches are combined that independently address outlier false positives and multimodal backgrounds. The background clustering models multimodal backgrounds, and the mixture tuned matched filter (MT-MF) addresses outliers. Combining the two methods captures significant additional performance benefits. The resulting mixture tuned clutter matched filter (MT-CMF) shows effective performance on simulated and airborne datasets. The classical MNF transform was applied, followed by k-means clustering. Then, each cluster s mean, covariance, and the corresponding eigenvalues were estimated. This yields a cluster-specific matched filter estimate as well as a cluster- specific feasibility score to flag outlier false positives. The technology described is a proof of concept that may be employed in future target detection and mapping applications for remote imaging spectrometers. It is of most direct relevance to JPL proposals for airborne and orbital hyperspectral instruments. Applications include subpixel target detection in hyperspectral scenes for military surveillance. Earth science applications include mineralogical mapping, species discrimination for ecosystem health monitoring, and land use classification.

Thompson, David R.↗
DOE OSTI2020

Kinetics and Mechanisms of ZnO to ZIF-8 Transformations in Supercritical CO2 Revealed by in situ X-ray Diffraction

ZIF-8 was synthesized in supercritical carbon dioxide (scCO2). In situ powder X-ray diffraction, ex situ microscopy and simulations, provides a encompassing view of the formation of ZIF-8 and intermediary ZnO@ZIF-8 composites in this nontraditional solvent. Time-resolved imaging exposed divergent physicochemical reaction pathways from previous studies of the growth of anisotropic ZIF-8 core@shell structures in traditional solvents. Synthetically relevant physio-chemical properties of scCO2 were integrated into classical nucleation theory, relating interfacial forces with 3D nu-cleation outcomes. The kinetics of crystallization were examined and displayed a characteristic signature of time- and temperature-dependent mechanisms over the extent of the reaction. Lastly, we show that subtle factors, such as the extent of reaction and the size/shape of sacrificial templates can tailor ZIF-8 composition and size, eliciting control over hierarchical porosity in a nonconventional green solvent.

Sinnwell, Michael A.↗
DOE OSTI2026

AnisONet: A deep neural operator-based anisotropic permeability upscaler from pore to Darcy scale

Directional permeability variations, which govern directional fluid flow in porous media with anisotropy, are important to accurately predict flow behavior, reactive transport, and fluid–solid interactions for various processes such as enhanced geothermal systems, energy storage devices, and biological systems. However, the intricate architecture of porous media makes it difficult to predict directional permeabilities. In this work, we present a novel machine learning (ML) framework, AnisONet, built upon an integration of a convolutional neural network, Swin transformer, and the deep operator network architecture, designed to predict anisotropic permeability and upscale predictions to larger spatial domains. First, AnisONet was evaluated with three classes of two-dimensional (2D) porous media, including synthetic circular and elliptical grains and natural sandstone grains from micro-computed tomography images. A lattice Boltzmann model (LBM) was used to calculate directional permeabilities at every 10° angle, producing 19 data points per image of porous media. AnisONet is then trained to predict permeability as a function of rotation angle. AnisONet showed strong predictive capability of directional permeability. Second, we tested our model for five upscaling cases with a large image size in the finite-element method (FEM) for 2D Darcy flow with various permeability tensor construction methods. Overall, upscaled permeability tensors in FEM simulations produce a reasonably good match with LBM results, highlighting the importance of selecting appropriate tensor formation strategies for accurate permeability upscaling. AnisONet, as a directional permeability estimator, could be further developed for more complex geometries, with the potential to develop a foundational ML model for various applications in porous media.

42 ENGINEERING↗
DOE OSTI2017

The Risk of Radiation-Induced Tumors or Malignant Transformation After Single-Fraction Intracranial Radiosurgery: Results Based on a 25-Year Experience

Purpose: To determine the risk of radiation-induced tumors or malignant transformation after single-fraction intracranial stereotactic radiosurgery (SRS). Methods and Materials: We performed a retrospective review of 1837 patients who received single-fraction SRS for arteriovenous malformation or benign tumor (meningioma, vestibular schwannoma, pituitary adenoma, glomus tumor) at a single center between 1990 and 2009. Patients were excluded if they refused research authorization (n=31), had a genetic predisposition to tumor development (n=84), received prior or concurrent radiation therapy (n=79), or had less than 5 years of imaging follow-up after SRS (n=501). The median imaging follow-up period for the remaining 1142 patients was 9.0 years (range, 5-24.9 years). Results: No radiation-induced tumors were identified in 11,264 patient-years of follow-up after SRS. The risk of a radiation-induced tumor developing after SRS was 0.0% at 5 years (95% confidence interval [CI], 0.0%-0.4%), 0.0% at 10 years (95% CI, 0.0%-0.9%), and 0.0% at 15 years (95% CI, 0.0%-2.8%). Malignant transformation occurred in 7 of 316 meningioma patients (2.2%) and 1 of 358 vestibular schwannoma patients (0.3%) at a median of 4.9 years (range, 2.8-13.8 years) after SRS. No cases of malignant transformation were noted in patients with pituitary adenomas (n=188) or glomus tumors (n=47). The 5-, 10-, and 15-year risk of malignant transformation was 0.5% (95% CI, 0.0%-0.9%), 0.8% (95% CI, 0.0%-1.8%), and 2.4% (95% CI, 0.0%-5.5%), respectively. Patients who underwent prior resection (hazard ratio, 14.56; 95% CI, 1.79-118.33; P=.01) and who had meningioma pathology (hazard ratio, 11.72; 95% CI, 1.44-96.15; P=.02) were at increased risk of malignant transformation. Conclusions: The risk of radiation-induced tumors or malignant transformation after SRS is very low and should not be used as a justification for choosing alternative treatment approaches (surgical resection, observation) over SRS for appropriate patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2021

NASA's Surface Biology and Geology Concept Study: Status and Next Steps

The National Academies Decadal Survey for Earth Science recommended that NASA pursue global imaging spectroscopy and thermal infrared measurements in the coming decade [1]. Both measurements would offer repeat coverage on approximately five-day to biweekly cadence, with comprehensive coverage of the globe's coastal and terrestrial area. This would be an unprecedented volume of data with the potential to transform remote sensing practice. To address this recommendation, NASA has sponsored a concept study by NASA research centers and associated university partners (https://sbg.jpl.nasa.gov). This study is determining a family of architecture options - including launch vehicle, spacecraft, instrument, and suborbital components - that could address the Decadal Survey objectives. The architecture study is driven by science needs and builds on input of the research community. As of this writing, the study is entering a phase in which a large field of system possibilities is pared down to a representative handful for an ultimate decision by NASA.

Imaging Spectroscopy↗
DOE OSTI2025

Soil porous microstructure control over soil organic matter mobility: A multimethod workflow for understanding chemistry-dependent organic matter binding in soil

Soil organic matter (SOM) has attracted a great deal of interest; particularly for its potential to mitigate human derived CO 2 emissions. Studies have demonstrated that SOM plays a critical role in carbon storage and CO 2 sequestration. However, the sorption properties of SOM, which influence its transport in pore water and stabilization within the soil, remain poorly understood. This study develops a workflow to: (1) examine compound-specific advective and diffusive transport and desorption behaviors, (2) quantify desorption rates through stop-flow and continuous-flow column experiments, and (3) evaluate the impact of soil microporosity on SOM mobility using high-resolution imaging and extractions. Intact core column experiments were conducted on Uncultivated (Natural) and Cultivated soil samples, both were arid soils, collected in Washington State. X-ray computed tomography was employed to measure porosity and pore connectivity, while Fourier-transform ion cyclotron resonance mass spectrometry was used to analyze SOM composition. The findings revealed that cultivation increased total carbon and nitrogen levels due to irrigation and fertilization, enhancing carbon capture potential in arid soils. In contrast, the Natural soil, characterized by higher porosity and connectivity, contained more oxidized carbon. Pore network analysis indicated that soil compaction in the Cultivated soil may lead to longer diffusion pathways, significantly influencing SOM transport and stability.

Hydraulic Properties↗
NASA NTRS1974

Measurement of the earth resources technology satellite /ERTS-1/ multi-spectral scanner OTF from operational imagery

The optical transfer function (OTF) of some typical ERTS-1 multispectral imagery was obtained by comparison of matched sets of aircraft underflight and ERTS photographic and digital images. One-dimensional OTF analysis consisted in obtaining U-2 and ERTS microdensitometer scans followed by density to transmission conversion, microdensitometer aperture correction, exposure calibration, scan correlation scale optimization, OTF calculation, obtaining a form weighted average of the OTFs, transformation of the OTFs back to the spatial domain (giving the line spread function or LSF), and application of a window function to the LSF resulting in a smoothed OTF. Date-to-date comparison of ERTS OTFs showed a drop in quality on April 4, 1973, compared with January 4, 1973.

Schowengerdt, R. A.↗
NASA NTRS1992

Passive microwave precipitation mapping and retrieval simulation

A numerical simulation of the satellite-based multispectral passive microwave mapping and precipitation retrieval process is described. The simulation contains three major components: (1) the forward radiative transfer calculation; (2) the sensor observation simulation; and (3) the precipitation retrieval algorithm. Secondary components include a Karhunen-Loeve transformation module and antenna pattern deconvolution module. The simulation facilitates the investigation of candidate precipitation retrieval algorithms using sub-Nyquist brightness temperature imagery, and the comparison of the relative merits of proposed radiometric systems such as the EOS multispectral imaging microwave radiometer (MIMR), the tropical rainfall measurement mission (TRMM) microwave imager (TRMM TMI), and the geosynchronous satellite sensors. A procedure for retrieving rain rates using a statistical iterative approach is outlined.

Skofronick, G. M.↗
NASA NTRS2006

Aeroelastic Flight Data Analysis with the Hilbert-Huang Algorithm

This report investigates the utility of the Hilbert Huang transform for the analysis of aeroelastic flight data. It is well known that the classical Hilbert transform can be used for time-frequency analysis of functions or signals. Unfortunately, the Hilbert transform can only be effectively applied to an extremely small class of signals, namely those that are characterized by a single frequency component at any instant in time. The recently-developed Hilbert Huang algorithm addresses the limitations of the classical Hilbert transform through a process known as empirical mode decomposition. Using this approach, the data is filtered into a series of intrinsic mode functions, each of which admits a well-behaved Hilbert transform. In this manner, the Hilbert Huang algorithm affords time-frequency analysis of a large class of signals. This powerful tool has been applied in the analysis of scientific data, structural system identification, mechanical system fault detection, and even image processing. The purpose of this report is to demonstrate the potential applications of the Hilbert Huang algorithm for the analysis of aeroelastic systems, with improvements such as localized online processing. Applications for correlations between system input and output, and amongst output sensors, are discussed to characterize the time-varying amplitude and frequency correlations present in the various components of multiple data channels. Online stability analyses and modal identification are also presented. Examples are given using aeroelastic test data from the F-18 Active Aeroelastic Wing airplane, an Aerostructures Test Wing, and pitch plunge simulation.

Brenner, Martin J.↗
NASA NTRS2009

Direct-Solve Image-Based Wavefront Sensing

A method of wavefront sensing (more precisely characterized as a method of determining the deviation of a wavefront from a nominal figure) has been invented as an improved means of assessing the performance of an optical system as affected by such imperfections as misalignments, design errors, and fabrication errors. The method is implemented by software running on a single-processor computer that is connected, via a suitable interface, to the image sensor (typically, a charge-coupled device) in the system under test. The software collects a digitized single image from the image sensor. The image is displayed on a computer monitor. The software directly solves for the wavefront in a time interval of a fraction of a second. A picture of the wavefront is displayed. The solution process involves, among other things, fast Fourier transforms. It has been reported to the effect that some measure of the wavefront is decomposed into modes of the optical system under test, but it has not been reported whether this decomposition is postprocessing of the solution or part of the solution process.

Lyon, Richard G.↗
NASA NTRS2017

Performance of a Space-Based Wavelet Compressor for Plasma Count Data on the MMS Fast Plasma Investigation

Data compression has been a staple of imaging instruments for years. Recently, plasma measurements have utilized compression with relatively low compression ratios. The Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale (MMS) mission generates data roughly 100 times faster than previous plasma instruments, requiring a higher compression ratio to fit within the telemetry allocation. This study investigates the performance of a space-based compression standard employing a Discrete Wavelet Transform and a Bit Plane Encoder (DWT/BPE) in compressing FPI plasma count data. Data from the first 6 months of FPI operation are analyzed to explore the error modes evident in the data and how to adapt to them. While approximately half of the Dual Electron Spectrometer (DES) maps had some level of loss, it was found that there is little effect on the plasma moments and that errors present in individual sky maps are typically minor. The majority of Dual Ion Spectrometer burst sky maps compressed in a lossless fashion, with no error introduced during compression. Because of induced compression error, the size limit for DES burst images has been increased for Phase 1B. Additionally, it was found that the floating point compression mode yielded better results when images have significant compression error, leading to floating point mode being used for the fast survey mode of operation for Phase 1B. Despite the suggested tweaks, it was found that wavelet-based compression, and a DWT/BPE algorithm in particular, is highly suitable to data compression for plasma measurement instruments and can be recommended for future missions.

plasma↗
DOE OSTI2023

Evaluation of Neutron-Radiation Tolerance of Lithium Indium Diselenide Semiconductors

Herein we discuss lithium indium diselenide (LISe) as a semiconductor that holds promise for neutron imaging sensor technologies because of its high neutron absorption efficiency and its corresponding ability to discriminate between gamma rays and neutrons. However, being a semiconductor, LISe may not be sufficiently radiation hard for practical application in radiation hard environments. Therefore, a systematic evaluation of the changes in material and electronic properties of LISe after high neutron fluence exposures is investigated. Herein, the characterization methods are utilized which included UV–vis, X-ray diffraction, radioluminescence, Raman, fourier transform infrared spectroscopy (FTIR), current–voltage, and neutron sensing. Characteristics of LISe material that appeared in the literature are identified herein along with several that are expected to appear based on theoretical analyses. The results obtained show clear changes in the material properties of LISe after neutron exposure up to a fluence of 10 16 n cm -2 . However, LISe is still able to sense neutrons above the background at 10 16 n cm -2 , suggesting that LISe may be suitable for use in neutron imaging sensors at neutron imaging facilities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Electron Microscopy Studies of Soft Nanomaterials

This review highlights recent efforts on applying electron microscopy (EM) to soft (including biological) nanomaterials. We will show how developments of both the hardware and software of EM have enabled new insights into the formation, assembly, and functioning (e.g., energy conversion and storage, phonon/photon modulation) of these materials by providing shape, size, phase, structural, and chemical information at the nanometer or higher spatial resolution. Specifically, we first discuss standard real-space two-dimensional imaging and analytical techniques which are offered conveniently by microscopes without special holders or advanced beam technology. The discussion is then extended to recent advancements, including visualizing three-dimensional morphology of soft nanomaterials using electron tomography and its variations, identifying local structure and strain by electron diffraction, and recording motions and transformation by in situ EM. On these advancements, we cover state-of-the-art technologies designed for overcoming the technical barriers for EM to characterize soft materials as well as representative application examples. Here, the even more recent integration of machine learning and its impacts on EM are also discussed in detail. With our perspectives of future opportunities offered at the end, we expect this review to inspire and stimulate more efforts in developing and utilizing EM-based characterization methods for soft nanomaterials at the atomic to nanometer length scales in academic research and industrial applications.

Imaging↗
DOE OSTI2022

Austenitic parent grain reconstruction in martensitic steel using deep learning

In this work we develop a deep convolutional architecture to estimate the prior austenite structure from observed martensite electron backscatter diffraction micrographs. A novel data augmentation strategy randomizes the global reference coordinate system which makes it possible to train our model from only four micrographs. The model is much faster than algorithmic approaches and generalizes well when applied to micrographs of a different material. Empirical evidence suggests the efficacy of the model depends on the scale of the microstructure and receptive field of the vision model. Furthermore, this work demonstrates that modern computer vision approaches are well suited for capturing complex spatial-orientation patterns present in orientation imaging micrographs.

36 MATERIALS SCIENCE↗
NASA NTRS1983

LANDSAT-4 image data quality analysis

Seven heterogeneous areas within the entire Des Moines, Iowa test site were selected to define candidate spectral training classes using a clustering algorithm. In addition to the 91 cluster nonsupervised classes, three supervised training classes were defined. The original candidate training classes were reduced to 42 spectrally separable training classes. The minimum and average transformed divergence values for the 42 spectral classes and for the best subsets of Y TM spectral bands are shown in a table. The best spectral band for any combination of 1 through 7 bands is the first middle IR band. The next best band is the near IR, followed by the red band and than the thermal IR. The best combination of four bands includes one from each of the four regions of the spectrum (visible, near IR, middle IR, and thermal IR).

Anuta, P. E.↗