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At least 1,549 records · Page 86
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Maine Ecological Forecasting III: Utilizing Earth Observations to Monitor Federally Endangered Atlantic Salmon (Salmo salar) Habitat in Maine: An Interactive Workshop

Shifting patterns in land use and land cover (LULC), temperature, and precipitation have exacerbated a rapid decline in Federally Endangered wild Atlantic salmon (Salmo salar) populations. The team at NASA DEVELOP partnered with the Maine Department of Marine Resources (DMR) and the Downeast Salmon Federation (DSF) to create a comprehensive workshop designed to demonstrate the applicability of Earth observations in examining these threats using the Penobscot, Union, and Machias Rivers as case studies. This entailed curating tutorials for acquiring and analyzing satellite data using Google Earth Engine, EarthExplorer, and Earthdata. The team demonstrated how to classify LULC in ArcGIS Pro from 1985 until 2021 using Landsat 5 Thematic Mapper (TM), Landsat 8 Operation Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and datasets from the United Stated Geological Survey (USGS) National Land Cover Database (NLCD), showing an overall transition from coniferous forests to other LULC classes. The team also demonstrated how to use historical data from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Integrated Multi-satellite Retrievals for Global Precipitation Measurement (GPM IMERG) to generate 2021 land surface temperature (LST) and precipitation maps, respectively, showing that Maine was abnormally dry during the summer in an increasingly warm region. These workshop materials will aid the partners in integrating NASA Earth observations into their future salmon habitat restoration initiatives.

Jonathan Falciani↗
DOE OSTI2015

X-ray scattering echoes and ghost halos from the intergalactic medium: relation to the nature of AGN variability

X-ray bright quasars might be used to trace dust in the circumgalactic and intergalactic medium through the phenomenon of X-ray scattering, which is observed around Galactic objects whose light passes through a sufficient column of interstellar gas and dust. Of particular interest is the abundance of gray dust larger than 0.1 μm, which is difficult to detect at other wavelengths. To calculate X-ray scattering from large grains, one must abandon the traditional Rayleigh-Gans approximation. The Mie solution for the X-ray scattering optical depth of the universe is ∼1%. This presents a great difficulty for distinguishing dust scattered photons from the point source image of Chandra, which is currently unsurpassed in imaging resolution. The variable nature of AGNs offers a solution to this problem, as scattered light takes a longer path and thus experiences a time delay with respect to non-scattered light. If an AGN dims significantly (≳3 dex) due to a major feedback event, the Chandra point source image will be suppressed relative to the scattering halo, and an X-ray echo or ghost halo may become visible. I estimate the total number of scattering echoes visible by Chandra over the entire sky: N{sub ech}∼10{sup 3}(ν{sub fb}/yr{sup −1}), where ν{sub fb} is the characteristic frequency of feedback events capable of dimming an AGN quickly.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Microwave and Millimeter Wave Imaging Using Synthetic Aperture Focusing and Holographical Techniques

Microwave and millimeter wave nondestructive testing and evaluation (NDT&E) methods have shown great potential for determining material composition in composite structures, determining material thickness or debond thickness between two layers, and determining the location and size of flaws, defects, and anomalies. The same testing methods have also shown great potential to produce relatively high-resolution images of voids inside Spray On Foam Insulation (SOFI) test panels using real focused methods employing lens antennas. An alternative to real focusing methods are synthetic focusing methods. The essence of synthetic focusing is to match the phase of the scattered signal to measured points spaced regularly on a plane. Many variations of synthetic focusing methods have already been developed for radars, ultrasonic testing applications, and microwave concealed weapon detection. Two synthetic focusing methods were investigated; namely, a) frequency-domain synthetic aperture focusing technique (FDSAFT), and b) wide-band microwave holography. These methods were applied towards materials whose defects were of low dielectric contrast like air void in SOFI. It is important to note that this investigation used relatively low frequencies from 8.2 GHz to 26.5 GHz that are not conducive for direct imaging of the SOFI. The ultimate goal of this work has been to demonstrate the capability of these methods before they are applied to much higher frequencies such as the millimeter wave frequency spectrum (e.g., 30-300 GHz).

Case, Joseph Tobias↗
DOE OSTI2013

Full spatial characterization of a nanofocused x-ray free-electron laser beam by ptychographic imaging

The emergence of hard X-ray free electron lasers (XFELs) enables new insights into many fields of science. These new sources provide short, highly intense, and coherent X-ray pulses. In a variety of scientific applications these pulses need to be strongly focused. In this article, we demonstrate focusing of hard X-ray FEL pulses to 125 nm using refractive x-ray optics. For a quantitative analysis of most experiments, the wave field or at least the intensity distribution illuminating the sample is needed. We report on the full characterization of a nanofocused XFEL beam by ptychographic imaging, giving access to the complex wave field in the nanofocus. From these data, we obtain the full caustic of the beam, identify the aberrations of the optic, and determine the wave field for individual pulses. This information is for example crucial for high-resolution imaging, creating matter in extreme conditions, and nonlinear x-ray optics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Normal incidence X-ray telescope power spectra of X-ray emission from solar active regions. I - Observations. II - Theory

Fourier analysis is applied to very high resolution image of coronal active regions obtained by the Normal Incidence X-Ray Telescope is used to find a broad isotropic power-law spectrum of the spatial distribution of soft X-ray intensities. Magnetic structures of all sizes are present down to the resolution limit of the instrument. Power spectra for the X-ray intensities of a sample of topologically different active regions are found which fall off with increasing wavenumber as 1/k-cubed. A model is presented that relates the basic features of coronal magnetic fluctuations to the subphotospheric hydrodynamic turbulence that generates them. The model is used to find a theoretical power spectrum for the X-ray intensity which falls off with increasing wavenumber as 1/k-cubed. The implications of a turbulent regime in active regions are discussed.

Gomez, Daniel O.↗
NASA NTRS2003

Morphological Analysis of Annual Recurrence of Dark Dune Spots on Southern Polar Region of Mars

Analysis of the Mars Global Surveyor narrow-angle images of the dark dune spots (DDSs) in three subsequent Martian winters and springs in Southern Polar Region resulted in the recognition that year by year DDSs reappeared on the same place with almost the same configuration. Comparison of the 1999 and 2001 high-resolution images showed a very interest recovery process.

Horvath, A.↗
NASA NTRSDate not supplied

Comparing Tropopause-Penetrating Convection Identifications Derived from NEXRAD and GOES over the Contiguous United States

Overshooting cloud tops (OTs) are a result of powerful updrafts that rapidly transport air from the troposphere to the lower stratosphere. Aside from the well-known relationships between strong updrafts and severe weather, the boundaries of updrafts, including the OT, are turbulent, which leads to irreversible mixing of air between the stratosphere and troposphere, altering the composition of both layers. In order to better understand the impact of OTs, knowing precisely when and where they occur is vital. Within the last decade remote-sensing observations from satellites and radars have been used to identify OTs, but the results thus far have not been entirely consistent due to challenges with accurately identifying OTs with these sensor datasets. This study compares OTs identified using NEXRAD reflectivity data from the GridRad dataset with an approach that uses GOES infrared (IR) data. The GridRad method estimates the altitude of echo tops directly from the radar pointing geometry, merging a combination of radars that enables products every 5 mins, with 2 km spatial and 1 km vertical grid spacing. The GOES satellite method uses spatial patterns in tropopause-relative IR brightness temperature to derive an OT likelihood. The study region covers a large part of the contiguous United States during selected active convection dates in 2017 and includes data from GOES-13/16. A large sample of OTs observed by NEXRAD and GOES-13/16 satellites are analyzed to better understand NEXRAD and IR observations of OTs, quantify agreement between the OT detection methods, and demonstrate how the 4x increase in spatial resolution from GOES-13 to GOES-16 impacts OT algorithm detection performance. The results show that for nearly time-matched scenes, with many severe storms, GOES-13 and -16 detection accuracy is quite comparable; however, some missed detections are attributed to poorer GOES-13 image resolution. It was found that GOES-13 OT regions are ~2 K warmer than GOES-16 on average, but such differences exceed 5 K for the most intense OT regions. It is found that false GOES IR-based detections are unavoidable, given that cold cloud pixels significantly colder than the tropopause from nearby or recently decayed OTs can persist within anvils for 15 minutes or more.

John W. Cooney↗
DOE OSTI2021

NanoSIP: NanoSIMS Applications for Microbial Biology

High-resolution imaging with secondary ion mass spectrometry (nanoSIMS) has become a standard method in systems biology and environmental biogeochemistry and is broadly used to decipher ecophysiological traits of environmental microorganisms, metabolic processes in plant and animal tissues, and cross-kingdom symbioses. When combined with stable isotope-labeling—an approach we refer to as nanoSIP—nanoSIMS imaging offers a distinctive means to quantify net assimilation rates and stoichiometry of individual cell-sized particles in both low- and high-complexity environments. While the majority of nanoSIP studies in environmental and microbial biology have focused on nitrogen and carbon metabolism (using 15 N and 13 C tracers), multiple advances have pushed the capabilities of this approach in the past decade. The development of a high-brightness oxygen ion source has enabled high-resolution metal analyses that are easier to perform, allowing quantification of metal distribution in cells and environmental particles. New preparation methods, tools for automated data extraction from large data sets, and analytical approaches that push the limits of sensitivity and spatial resolution have allowed for more robust characterization of populations ranging from marine archaea to fungi and viruses. Further, NanoSIMS studies continue to be enhanced by correlation with orthogonal imaging and ‘omics approaches; when linked to molecular visualization methods, such as in situ hybridization and antibody labeling, these techniques enable in situ function to be linked to microbial identity and gene expression. Here we present an updated description of the primary materials, methods, and calculations used for nanoSIP, with an emphasis on recent advances in nanoSIMS applications, key methodological steps, and potential pitfalls.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

A comparison of histopathology imaging comprehension algorithms based on multiple instance learning

Whole slide imaging (WSI), also called digital virtual microscopy, is a new imaging modality. It allows for the application of AI and machine learning methods to cancer pathology to help establish a means for the automatic diagnosis of cancer cases. However, designing machine-learning models for WSI is computationally challenging due to its required ultra-high resolution. The current state-of-the-art models use multiple instance learning (MIL). MIL is a weakly-supervised learning method in which the model uses an array of inferences from many smaller instances to make a final classification about the entire set. In the context of WSI, researchers divide the ultra-high-resolution image into many patches. The model then classifies the slide based on an array of inferences from the patches. Among several ways of making the final classification, attention-based mechanisms have resulted in superb accuracy scores. The Transformer, one attention-based algorithm, has reported substantial improvements for WSI comprehension tasks. In this project, we studied and compared several WSI comprehension algorithms. We used the following three datasets: CAMELYON16+17, TCGALung, and TCGA-Kidney. We found that attention-based MIL algorithms performed better than standard MIL algorithms for classifying WSI images, achieving a higher mean accuracy and AUC. However, none of the attention-based algorithms performed significantly better than the others, reporting accuracy scores that varied widely. Presumably, it is due to the limited availability of training samples in the data corpus. Since it is not easy to increase the samples from human subjects, some machine learning techniques like transfer learning could help mitigate this issue.

Saunders, Adam↗
NASA NTRS2009

MODIS Solar Reflective Calibration Traceability

Long-term climate data records often consist of observations made by multiple sensors. It is, therefore, extremely important to have instrument overlap, to be able to track instrument stability, to quantify, measurement uncertainties, and to establish absolute scale traceable to the International System of Units (SI). The Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument for both the Terra and Aqua missions, which were launched in December 1999 and May 2002, respectively. It has 20 reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers and observes the Earth at three nadir spatial resolutions: 0.25km, 0.5km, and 1km. MODIS RSB on-orbit calibration is reflectance based with reference to the bidirectional reflectance factor (BRF) of its on-board solar diffuser (SD). The SD BRF characterization was made pre-launch by the instrument vendor using reference samples traceable directly to the National Institute of Standards and Technology (NIST). On-orbit SD reflectance degradation is tracked by an on-board solar diffuser monitor (SDSM). This paper provides details of this calibration chain, from prelaunch to on-orbit operation, and associated uncertainty assessments. Using MODIS as an example, this paper also discusses challenges and key design requirements for future missions developed for accurate climate studies.

Xiong, Xiaoxiong↗
NASA NTRS2014

Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008-2013)

We have investigated the stability of the MODerate resolution Imaging Spectroradiometer (MODIS) infrared-derived ice surface temperature (IST) data from Terra for use as a climate quality data record. The availability of climate quality air temperature data (TA) from a NOAA Global Monitoring Division observatory at Greenlands Summit station has enabled this high temporal resolution study of MODIS ISTs. During a 5 year period (July 2008 to August 2013), more than 2500 IST values were compared with 3-minute average TA values derived from the 1-minute data from NOAAs primary 2 m air temperature sensor. These data enabled an expected small offset between air and surface temperatures at this the ice sheet location to be investigated over multiple annual cycles.

Greenland↗
NASA NTRS2013

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS2021

First retrieval of AOD at fine-resolution over shallow and turbid coastal waters from MODIS

The widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Dark-Target (DT) aerosol product fails to accurately retrieve Aerosol Optical Depth (AOD) over shallow and turbid Coastal Waters (CWs). To fill in gaps, and to improve land to ocean AOD continuity, we developed a coastal water retrieval algorithm at a spatial resolution of 1 km (CW-1km). CW-1km relies on observed top-of-atmosphere reflectance at 2.1 μm (ρ2.1), both to derive AOD and to perform a spatial variation test that enhances the existing DT masks for clouds and land. We show that the CW-1km improves spatial continuity of AOD between land, coast, and open ocean, while also increasing AOD product availability by 47.0%. Comparing with 15 years of marine aerosol network measurements, CW-1km AODs are validated to have a normalized mean bias of 1.0%, which is much smaller than 17.6% for the original DT product.

MODIS AOD↗
DOE OSTI2014

Super-Resolution Study of Polymer Mobility Fluctuations near c *

Nanoscale dynamic heterogeneities in synthetic polymer solutions are detected using super-resolution optical microscopy. To this end, we map concentration fluctuations in polystyrene–toluene solutions with spatial resolution below the diffraction limit, focusing on critical fluctuations near the polymer overlap concentration, c*. Two-photon super-resolution microscopy was adapted to be applicable in an organic solvent, and a home-built STED-FCS system with stimulated emission depletion (STED) was used to perform fluorescence correlation spectroscopy (FCS). The polystyrene serving as the tracer probe (670 kg mol –1 , radius of gyration R G ≈ 35 nm, end-labeled with a bodipy derivative chromophore) was dissolved in toluene at room temperature (good solvent) and mixed with matrix polystyrene (3,840 kg mol –1 , R G ≈ 97 nm, M w /M n = 1.04) whose concentration was varied from dilute to more than 10c*. Whereas for dilute solutions the intensity–intensity correlation function follows a single diffusion process, it splits starting at c* to imply an additional relaxation process provided that the experimental focal area does not greatly exceed the polymer blob size. We identify the slower mode as self-diffusion and the increasingly rapid mode as correlated segment fluctuations that reflect the cooperative diffusion coefficient, D coop . These real-space measurements find quantitative agreement between correlation lengths inferred from dynamic measurements and those from determining the limit below which diffusion coefficients are independent of spot size. Furthermore, this study is considered to illustrate the potential of importing into polymer science the techniques of super-resolution imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Imaging Unstained Synthetic Polymer Crystals and Defects on Atomic Length Scales Using Cryogenic Electron Microscopy

Properties of soft crystalline materials such as synthetic polymers are governed by locations of constituent atoms. Determining atomic-scale structures in these materials is difficult because they degrade rapidly when studied by electron microscopy, and techniques such as x-ray scattering average over volumes much larger than coherent blocks of the unit cells. We obtained cryo-electron microscopy images of self-assembled nanosheets of a peptoid polymer, made by solid-phase synthesis, in which we see a variety of crystalline motifs. A combination of crystallographic and single particle methods, developed for cryo-electron microscopy of biological macromolecules, was used to obtain high resolution images of the crystals. Individual crystals contain grains that are mirror images of each other with concomitant grain boundaries. We have used molecular dynamic simulations to build an atomic model of the crystal structure to facilitate the interpretation of electron micrographs. Direct visualization of crystalline grains and grain boundaries on atomic length scales represents a new level of information for the polymer field.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Scalable Pipeline for Gigapixel Whole Slide Imaging Analysis on Leadership Class HPC Systems

Whole Slide Imaging (WSI) captures microscopic details of a patient's histopathological features at multiple res-olutions organized across different levels. Images produced by WSI are gigapixel-sized, and saving a single image in memory requires a few gigabytes which is scarce since a complicated model occupies tens of gigabytes. Performing a simple met-ric operation on these large images is also expensive. High-performance computing (HPC) can help us quickly analyze such large images using distributed training of complex deep learning models. One popular approach in analyzing these images is to divide a WSI image into smaller tiles (patches) and then train a simpler model with these reduced-sized but large numbers of patches. However, we need to solve three pre-processing challenges efficiently for pursuing this patch-based approach. 1) Creating small patches from a high-resolution image can result in a high number (hundreds of thousands per image) of patches. Storing and processing these images can be challenging due to a large number of I/O and arithmetic operations. To reduce I/Oand memory accesses, an optimal balance between the size and number of patches must exist to reduce I/O and memory accesses. 2) WSI images may have tiny annotated regions for cancer tissue and a significant portion with normal and fatty tissues; correct patch sampling should avoid dataset imbalance. 3) storing and retrieving many patches to and from disk storage might incur I/O latency while training a deep learning model. An efficient distributed data loader should reduce I/O latency during the training and inference steps. This paper explores these three challenges and provides empirical and algorithmic solutions deployed on the Summit supercomputer hosted at the Oak Ridge Leadership Computing Facility.

Dash, Sajal↗
DOE OSTI2024

Optical Photometric Indicators of Galaxy Cluster Relaxation

Abstract The most dynamically relaxed clusters of galaxies play a special role in cosmological studies as well as astrophysical studies of the intracluster medium (ICM) and active galactic nucleus feedback. While high-spatial-resolution imaging of the morphology of the ICM has long been the gold standard for establishing a cluster’s dynamical state, such data are not available from current or planned surveys, and thus require separate, pointed follow-up observations. With optical and/or near-IR photometric imaging, and red-sequence cluster finding results from those data, expected to be ubiquitously available for clusters discovered in upcoming optical and millimeter-wavelength surveys, it is worth asking how effectively photometric data alone can identify relaxed cluster candidates, before investing in, e.g., high-resolution X-ray observations. Here we assess the ability of several simple photometric measurements, based on the redMaPPer cluster finder run on Sloan Digital Sky Survey data, to reproduce X-ray classifications of dynamical state for an X-ray selected sample of massive clusters. We find that two simple metrics contrasting the bright central galaxy (BCG) to other cluster members can identify a complete sample of relaxed clusters with a purity of ∼40% in our data set. Including minimal ICM information in the form of a center position increases the purity to ∼60%. However, all three metrics depend critically on correctly identifying the BCG, which is presently a challenge for optical red-sequence cluster finders.

79 ASTRONOMY AND ASTROPHYSICS↗