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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Collisional Histories of Comets and Trojan Asteroids: Diopside, Magnesite, and Fayalite Impact Studies

Comets and asteroids have weathered dynamic histories, as evidenced by their rough surfaces. The Nice model describes a violent reshuffling of small bodies during the Late Heavy Bombardment, with collisions acting to grind these planetesimals away. This creates an additional source of impact material that can re-work the surfaces of the larger bodies over the lifetime of the solar system. Here, we investigate the possibility that signatures due to impacts (e.g. from micrometeoroids or meteoroids) could be detected in their spectra, and how that can be explained by the physical manifestation of shock in the crystalline structure of minerals. All impact experiments were conducted in the Johnson Space Center Experimental Impact Laboratory using the vertical gun. Impact speeds ranged from approx.2.0 km/s to approx.2.8 km/s. All experiments were conducted at room temperature. Minerals found in comets and asteroids were chosen as targets, including diopside (MgCaSi2O6, monoclinic pyroxene), magnesite (MgCO3, carbonate), and fayalite (FeSiO4, olivine). Impacted samples were analyzed using a Fourier Transform Infrared Spectrometer (FTIR) and a Transmission Electron Microscope (TEM). Absorbance features in the 8-13 m spectral region demonstrate relative amplitude changes as well as wavelength shifts. Corresponding TEM images exhibit planar shock dislocations in the crystalline structure, attributed to deformation at high strain and low temperatures. Elongating or shortening the axes of the crystalline structure of forsterite (Mg2SiO4, olivine) using a discrete dipole approximation model (Lindsay et al., submitted) yields changes in spectral features similar to those observed in our impacted laboratory minerals.

Lederer, S. M.↗
NASA NTRS2018

Virtual Sensors Determined Through Machine Learning

We propose a method that increases the capability of a conventional sensor, transforming it into an enhanced virtual sensor. This paper focuses on a virtual thermal Infrared Radiation (IR) sensor based on a conventional visual (RGB) sensor. The estimation of thermal IR images can enhance the ability of terrain classification, which is crucial for autonomous navigation of rovers. The estimate in IR from visual band has inherent limitations, as these are different bands, yet correlations between visual RGB and thermal IR images exist, as different terrains, which visually may appear different, also have different thermal inertia. This paper describes the developed deep learning-based algorithm that estimates thermal IR images from RGB images of terrains, providing the feasibility of the idea with average 1.21 error [degree Celsius].

Torresen, Jim↗
NASA NTRS1980

Concerning the feasibility of a real time SAR digital processor for VOIR low resolution imaging modes

The feasibility of real time digital processing of synthetic aperture radar data for Venus orbiting imaging radar low resolution modes was investigated. First, it is shown that range migration is not a problem for these modes. Then, under the assumption of no range migration, fast Fourier transform implementations for accomplishing both range and azimuth correlation in real time are shown to be feasible with current technology.

Truong, T. K.↗
NASA NTRS1993

A Novel Optical/digital Processing System for Pattern Recognition

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

Boone, Bradley G.↗
NASA NTRS1992

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

A new method for analyzing the kinematics of joint motion using magnetic resonance imaging (MRI) is described. The reconstruction of the metacarpalphalangeal joint of the left index finger into a 3D graphic display is shown. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones are obtained and processed by analyzing the screw motion of the joint. Landmark positions are chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily 2D planar motion of this joint is then studied using a method of constructing coordinate systems using three or more points. A transformation matrix based on a world coordinate system describes the location and orientation of the local target coordinate system. The findings show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove design for EVA.

Dickenson, Reuben D.↗
NASA NTRS2021

Exploring Sentinel-1 and Sentinel-2 diversity for Flood inundation mapping using deep learning

Identification of flood water extent from satellite images has historically relied on either synthetic aperture radar (SAR) or multi-spectral (MS) imagery. MS sensors are limited to cloud free conditions, whereas SAR imagery is plagued by noise-like speckle. Prior studies that use combinations of MS and SAR data to overcome individual limitations of these sensors have not fully examined sensitivity of flood mapping performance to different combinations of SAR and MS derived spectral indices or band transformations in color space. This study explores the use of diverse bands of Sentinel 2 (S2) through well-established water indices and Sentinel 1 (S1) derived SAR imagery along with their combinations to assess their capability for generating accurate flood inundation maps. The robustness in performance of S-1 and S-2 band combinations was evaluated using 446 hand labeled flood inundation images spanning across 11 flood events from Sen1Floods11 dataset which are highly diverse in terms of land cover as well as location. A modified K-fold cross validation approach is used to evaluate the performance of 32 combinations of S1 and S2 bands using a fully connected deep convolutional neural network known as U-Net. Our results indicated that usage of elevation information has improved the capability of S1 imagery to produce more accurate flood inundation maps. Compared to a median F1 score of 0.62 when using only S1 bands, the combined use of S1 and elevation information led to an improved median F1 score of 0.73. Water extraction indices based on S2 bands have a statistically significant superior performance in comparison to S1. Among all the band combinations, HSV (Hue, Saturation, Value) transformation of S2 bands provides a median F1 score of 0.9, outperforming the commonly used water spectral indices owing to HSV’s transformation’s superior contrast distinguishing abilities. Additionally, U-Net algorithm was able to learn the relationship between raw S2 based water extraction indices and their corresponding raw S2 bands, but not of HSV owing to relatively complex computation involved in the latter. Results of the paper establishes important benchmarks for the extension of S1 and S2 data-based flood inundation mapping efforts over large spatial extents.

Goutam Konapala↗
NASA NTRS2002

Spatial and temporal traction response in human airway smooth muscle cells

Tractions that cells exert on their substrates are essential in cell spreading, migration, and contraction. These tractions can be determined by plating the cells on a flexible gel and measuring the deformation of the gel by using fluorescent beads embedded just below the surface of the gel. In this article we describe the image correlation method (ICM) optimized for determining the displacement field of the gel under a contracting cell. For the calculation of the traction field from the displacement field we use the recently developed method of Fourier transform traction cytometry (FTTC). The ICM and FTTC methods are applied to human airway smooth muscle cells during stimulation with the contractile agonist histamine or the relaxing agonist isoproterenol. The overall intensity of the cell contraction (the median traction magnitude, the energy transferred from the cell to the gel, and the net contractile moment) increased after activation with histamine, and decreased after treatment with isoproterenol. Cells exhibited regional differences in the time course of traction during the treatment. Both temporal evolution and magnitude of traction increase induced by histamine varied markedly among different cell protrusions, whereas the nuclear region showed the smallest response. These results suggest that intracellular mediators of cell adhesion and contraction respond to contractile stimuli with different rates and intensities in different regions of the cell.

NASA Discipline Cell Biology↗
NASA NTRS1978

Comparison of in situ and remotely sensed ocean waves off Marineland, Florida

Comparison between X-band and L-band radar imagery of sea waves is made. Sea truth was obtained by in situ pitch-and-roll buoy measurements. Under the low wind and wave conditions of the tests, superior wave imagery and more useful Fourier transforms were obtained with X-band SAR as compared to L-band with equivalent signal-to-noise ratio and synthetic aperture resolution. A comparison between X-band wave images and the in situ measurements shows agreement in the dominant wave direction to within a few degrees. The normalized spectra show a striking resemblance in spectral shape.

Shemdin, O. H.↗
NASA NTRS1992

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

A new method of analyzing the kinematics of joint motion is developed. Magnetic Resonance Imaging (MRI) offers several distinct advantages. Past methods of studying anatomic joint motion have usually centered on four approaches. These methods are x-ray projection, goniometric linkage analysis, sonic digitization, and landmark measurement of photogrammetry. Of these four, only x-ray is applicable for in vivo studies. The remaining three methods utilize other types of projections of inter-joint measurements, which can cause various types of error. MRI offers accuracy in measurement due to its tomographic nature (as opposed to projection) without the problems associated with x-ray dosage. Once the data acquisition of MR images was complete, the images were processed using a 3D volume rendering workstation. The metacarpalphalangeal (MCP) joint of the left index finger was selected and reconstructed into a three-dimensional graphic display. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones were obtained and processed by analyzing the screw motion of the MCP joint. Landmark positions were chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily two dimensional planar motion of this joint was then studied using a method of constructing coordinate systems using three (or more) points. A transformation matrix based on a world coordinate system described the location and orientation of a local target coordinate system. Future research involving volume rendering of MRI data focusing on the internal kinematics of the hand's individual ligaments, cartilage, tendons, etc. will follow. Its findings will show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove (power assisted) design for extravehicular activity (EVA).

Dickenson, Rueben D.↗
NASA NTRS1992

Optimization of the information content of multitemporal Landsat TM data sets for monitoring forest cover disturbance

Procedures that were developed to optimize the information content of multitemporal thematic mapper (TM) data sets for forest cover disturbance monitoring in Minnesota are described. TM imagery from three different years was calibrated to exoatmospheric reflectance. An atmospheric correction routine was applied combining two major components, atmospheric normalization over time and transformation to ground reflectance. Atmospheric conditions were modeled over time using regression functions derived from five ground features known to be unchanged over the time interval of interest and spanning the entire image reflectance range. The correlation between digital data and the forest cover was subsequently maximized and irrelevant information content was reduced by converting the band-specific reflectances into seven vegetation indices that were assumed to carry unique information. The application of two change detection algorithms to these seven indices ultimately resulted in 14 change features for each time interval of interest. Results show that the preprocessing sequence is vital to forest cover monitoring methodology.

Coppin, Pol R.↗
NASA NTRS1994

Visibility of DCT Basis Functions: Effects of Contrast Masking

Current strategies for compressing images neglect to accommodate certain aspects of the human visual system. One such neglected aspect is contrast masking. Here we provide measurements of contrast masking within the framework of the discrete cosine transform (DCT). We describe how to optimize DCT-based compression with respect to contrast masking.

Soloman, Joshua A.↗
NASA NTRS2011

Watching Galaxy Evolution in High Definition

As Einstein predicted, mass deflects light. In hundreds of known cases, "gravitational lenses" have deflected, distorted, and amplified images of galaxies or quasars behind them. As such, gravitational lensing is a way to "cheat" at studying how galaxies evolve, because lensing can magnify galaxies by factors of 10--100 times, transforming them from objects we can barely detect to bright objects we can study in detail. I'll summarize new results from a comprehensive program, using multi-wavelength, high-quality spectroscopy, to study how galaxies formed stars at redshifts of 1--3, the epoch when most of the Universe's stars were formed.

Rigby, Jane↗
NASA NTRS2012

Watching Galaxy Evolution in High Definition

As Einstein predicted, mass deflects light. In hundreds of known cases, "gravitational lenses" have deflected, distorted, and amplified images of galaxies or quasars behind them. As such, gravitational lensing is a way to "cheat" at studying how galaxies evolve, because lensing can magnify galaxies by factors of 10-100 times, transforming them from objects we can barely detect to bright objects we can study in detail. I'll summarize new results from a comprehensive program, using multi-wavelength, high-quality spectroscopy, to study how galaxies formed stars at redshifts of 1-3, the epoch when most of the Universe's stars were formed.

Rigby, Jane R.↗
NASA NTRS2013

A Dynamic Earth: 50 Years of Observations from Space

Observations of the surface of the Earth began more than a half century ago with the earliest space missions. The global geopolitical environment at the beginning of the space age fueled advances in rocketry and human exploration, but also advances in remote sensing. At the same time that space-based Earth Observations were developing, global investments in infrastructure that were initiated after World War II accelerated large projects such as the construction of highways, the expansion of cities and suburbs, the damming of rivers, and the growth of big agriculture. These developments have transformed the Earth s surface at unprecedented rates. Today, we have a remarkable library of 50 years of observations of the Earth taken by satellite-based sensors and astronauts, and these images and observations provide insight into the workings of the Earth as a system. In addition, these observations record the footprints of human activities around the world, and illustrate how our activities contribute to the changing face of the Earth. Starting with the iconic "Blue Marble" image of the whole Earth taken by Apollo astronauts, we will review a timeline of observations of our planet as viewed from space.

Evans, Cynthia A.↗
NASA NTRSDate not supplied

Dense Feature Tracking of Atmospheric Winds with Deep Optical Flow

Atmospheric winds are a key physical phenomenon impacting natural hazards, energy transport, ocean currents, large-scale circulation, and ecosystem fluxes. Observing winds is a complex process and presents a large gap in NASA’s Earth Observation System. Atmospheric motion vectors (AMVs) aim to fill this gap by making numerical estimates of cloud movement between sequences of multi-spectral satellite images, tracking clouds and water vapor. Recent imaging hardware and software advancements have enabled the use of numerical optical flow techniques to produce accurate and dense vector fields outperforming traditional methods. This work presents WindFlow as the first machine learning based system for feature tracking atmospheric motion using optical flow. Due to the lack of large-scale satellite-based observations, we leverage high-resolution numerical simulations from NASA's GEOS-5 Nature Run to perform supervised learning and transfer to satellite images. We demonstrate that our approach using deep learning based optical flow scales to ultra-high-resolution images of size 2881x5760 with less than 1 m/s bias and 2.5 m/s average error. Four network and learning architectures are compared and it is found that recurrent all-pairs field transforms (RAFT) produces the lowest errors on all metrics for wind speed and direction. Results on held out numerical outputs shows RAFT's good performance in each of the spatial, temporal, and physical dimensions. A comparison between WindFlow and an operational AMV product against rawinsonde observations show that RAFT transfers across simulations and thermal infrared satellite observations. This work shows that machine learning based optical flow is an efficient approach to generating robust feature tracking for AMVs consistently over large regions.

Atmospheric winds↗
NASA NTRS2024

CREST: a Climate Data Record of Stratospheric Aerosols

Climate-related studies need information about the distribution of stratospheric aerosols, which influence the energy balance of the Earth’s atmosphere. In this work, we present a merged dataset of vertically resolved stratospheric aerosol extinction coefficients, which is derived using data from six limb and occultation satellite instruments: SAGE (Stratospheric Aerosol and Gas Experiment) II on ERBS (Earth Radiation Budget Satellite), GOMOS (Global Ozone Monitoring by Occultation of Stars) and SCIAMACHY (Scanning Imaging Spectrometer for Atmospheric Chartography) on Envisat, OSIRIS (Optical Spectrograph and InfraRed Imaging System) on Odin, OMPS (Ozone Monitor Profiling Suite Limb Profiler) on Suomi NPP, and SAGE III on the ISS (International Space Station). The merging of aerosol profiles is performed via the transformation of the aerosol datasets from individual satellite instruments to the same wavelength (750 nm) and their de-biasing and homogenization by adjusting the seasonal cycles. After such homogenization, the data from individual satellite instruments are in good agreement. The merged aerosol extinction coefficient is computed as the median of the adjusted data from the individual instruments. The merged time series of vertically resolved monthly mean aerosol extinction coefficients at 750 nm is provided in 10° latitudinal bins from 90° S to 90° N, in the altitude range from 8.5 to 39.5 km. The time series of the stratospheric aerosol optical depth (SAOD) is created via the integration of aerosol extinction profiles from the tropopause to 39.5 km; it is also provided as monthly mean data in 10° latitudinal bins. The created aerosol climate record covers the period from October 1984 until December 2023, and it is intended to be extended in the future. The merged CREST aerosol dataset (v2) is available at https://doi.org/10.57707/fmib2share.dfe14351fd8548bcaca3c2956b17f665 (Sofieva et al., 2024a). It can be used in various climate-related studies.

Viktoria F Sofieva↗
NASA NTRS1989

An evaluation of imaging spectrometry for estimating forest canopy chemistry

High spectral resolution Airborne Imaging Spectrometer (AIS) data were acquired over 20 well-studied Wisconsin forest sites to evaluate the potential of remote sensing for estimating forest canopy chemistry. Intensive nutrient cycling research in these forests demonstrates that canopy lignin content is strongly related to measured annual nitrogen mineralization at the undisturbed sites and may serve as an accurate index for nitrogen cycling rates. Ground measurements were made of foliar biomass and canopy nitrogen and lignin content, the latter within two weeks of the AIS overflight. The spectral data were transformed using derivative techniques modified from laboratroy spectroscopy. Stepwise regression assisted in determining combinations of wavelengths most highly correlated with canopy chemistry and biomass. Strong correlations between AIS data and total canopy lignin content in deciduous forests and canopy lignin concentration (total lignin/biomass) in both deciduous and coniferous stands indicate that imaging spectrometry can be used to estimate canopy lignin content and, from that, the spatial distribution of annual nitrogen mineralization rates.

Wessman, Carol A.↗
NASA NTRS1980

The effects of seeing on the reflected spectrum of Uranus and Neptune

The results of a redetermination of the rotational periods of Uranus and Neptune, based on spectrograms obtained with the coude spectrograph of the 5 m Hale telescope, are presented. The effects of image motion on the shape of the spectral lines reflected by a planet rotating as a solid body and coherently scattering solar light, has been studied analytically. A general relation between the seeing transformed velocities at any point on the disk and those at the equator is established. It is shown that, for the case of Gaussian seeing, the brightness continuum of the smeared disk contains all the information required to derive the shape of the reflected lines. The shift, change in r.m.s. width, and asymmetry of the seeing transformed lines at the equator have been numerically evaluated for the brightness distribution of Uranus determined from Stratoscope II.

Muench, G.↗