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NASA NTRSDate not supplied

Camera Exposure Time Determination for Artemis I Lunar Flyby

During Artemis I, a flight test was conducted using the Optical Navigation Camera to image Lunar terrain at low altitude prior to the Return Powered Flyby (RPF) burn. The vehicle descended rapidly toward the surface and transitioned over the Lunar Terminator during the time frame in which the images were to be gathered, creating challenging lighting conditions which required the development of a novel technique for exposure time determination to gather imagery of appropriate quality for post flight analysis. The resulting technique leveraged simple photometric models and simulations, as well as the spacecrafts altitude and pointing direction to determine the necessary change in exposure times over the course of the flyby, resulting in a successful flight test.

Terrain Relative Navigation↗

NASA NTRS2026

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen↗

NASA NTRS2023

South Slough Water Resources: Monitoring Changes in Water Quality to Identify Stressors in Eelgrass Extent Throughout the Coos Estuary

The Coos estuary in Southern Oregon supports a variety of habitats, including eelgrass (Zostera marina) meadows. Eelgrass meadows provide shelter and sustenance to local and migratory wildlife, including commercially important fishes, and cultural resources to local communities. These ecosystem services establish eelgrass as an ecologically, economically, and culturally important resource. However, the extent and density of eelgrass meadows within this estuary have declined substantially since 2005, threatening the ecosystem services they provide. NASA DEVELOP partnered with the South Slough National Estuarine Research Reserve and the Confederated Tribes of the Coos, Lower Umpqua, and Siuslaw Indians’ Department of Natural Resources to generate time-series maps of the water quality conditions (chlorophyll-a, turbidity) and eelgrass extent in the Coos estuary from 2016 to 2023 to better understand the conditions driving eelgrass decline. The DEVELOP team used NASA Earth observations including Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, and the European Space Agency’s Sentinel-2 Multispectral Instrument (MSI) to generate these time-series maps. The team faced limitations in the feasibility of detecting eelgrass within the Coos Estuary, including spectral resolution, tidal phase, and turbidity. These limitations indicate additional in situ data collection will be necessary for accurate eelgrass assessment. Meanwhile, the team determined it is feasible to assess turbidity and chlorophyll-a within the Coos Estuary using remote satellite data. These tools enabled the research partners to assess water quality characteristics within the Coos Estuary at a greater spatial scale and may provide a method of inexpensive preliminary investigation of eelgrass meadow locations.

eelgrass↗

NASA NTRS1986

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Data acquisition, initial site characterization, image and geographic information methods available, and brief evaluations of first-year for NASA's Thematic Mapper (TM) working group are presented. The TM and other spectral data are examined in order to relate local, intensive ecosystem research findings to estimates of carbon cycling rates over wide geographic regions. The effort is to span environments ranging from dry to moist climates and from good to poor site quality using the TM capability, with and without the inclusion of geographic information system (GIS) data, and thus to interpret the local spatial pattern of factors conditioning biomass or productivity. Twenty-eight TM data sets were acquired, archived, and evaluated. The ERDAS image processing and GIS system were installed on the microcomputer (PC-AT) and its capabilities are being investigated. The TM coverage of seven study areas were exported via ELAS software on the Prime to the ERDAS system. Statistical analysis procedures to be used on the spectral data are being identified.

Iverson, L. R.↗

NASA NTRSDate not supplied

NASA's CLARREO Pathfinder Mission: The Reflected Solar’s First SITSat

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission will take reflected solar (RS) highly accurate measurements needed to monitor Earth’s climate and will be the first RS SI-traceable Satellite Sensor (SITSat). The mission includes a RS spectrometer that will be installed on the International Space Station (ISS) and take measurements for at least one year. CLARREO Pathfinder (CPF) will use on-orbit calibration to achieve an unprecedented high accuracy with SI-traceability and the inter-calibration of other on-orbit instruments. The spectrometer is based on the HyperSpectral Imager for Climate Science (HySICS) instrument developed by the University of Colorado/Laboratory for Atmospheric and Space Physics of Boulder, CO, USA. HySICS is being designed to have a radiometric uncertainty of 0.3% (1-sigma), a five to ten times improvement over existing spaceflight RS instruments. High accuracy SI-traceable measurements such as these are critical to develop long-term climate-quality data sets. Additionally, by measuring spectral reflectance with high accuracy the CPF instrument will serve as an on-orbit intercalibration radiometric reference for operational Earth-viewing sensors, such as the Clouds and Earth’s Radiant Energy System (CERES) broadband shortwave instrument and the Visible/Infrared Imaging Radiometer Suite (VIIRS). Two-axis pointing, a spectral range from 350 nm to 2300 nm, and a spectral resolution ≤6 nm enable CPF to provide nearly coincident temporal, spatial, angular, and spectral matching of intercalibration targets, with sampling sufficient to reduce random errors. The intercalibration method will refine knowledge of target sensors’ effective offsets, gain, non-linearity, spectral response, and polarization sensitivity (as is relevant). Calibrated reflectance and reflected radiance spectra will be distributed to the scientific community through a NASA Distributed Active Archive Center (DAAC). We will present an overview of the CLARREO Pathfinder mission, its anticipated impact on monitoring climate variability, and the novel CPF direct intercalibration approach.

climate↗

NASA NTRS1984

Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming

A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.

Lang, H. R.↗

NASA NTRS1984

Landsat-4 data quality analysis

Landsat-4 satellite Thematic Mapper (TM) and multispectral scanner (MSS) data have been analyzed in order to ascertain data quality and information content. Geometric evaluations have tested band-to-band registration accuracy, and the TM's overall system resolution was evaluated for the case of image objects with high contrast, sharp edge responses. The information content evaluation employed clustering, principal components, and the transformed divergence separability measured on data from Iowa and Chicago, Illinois. The MSS classification analysis compared MSS and TM information contents for a large number of science classes.

Anuta, P.↗

NASA NTRS1991

NDE standards for high temperature materials

High temperature materials include monolithic ceramics for automotive gas turbine engines and also metallic/intermetallic and ceramic matrix composites for a range of aerospace applications. These are materials that can withstand extreme operating temperatures that will prevail in advanced high-efficiency gas turbine engines. High temperature engine components are very likely to consist of complex composite structures with three-dimensionality interwoven and various intermixed ceramic fibers. The thermomechanical properties of components made of these materials are actually created in-place during processing and fabrication stages. The complex nature of these new materials creates strong incentives for exact standards for unambiguous evaluations of defects and microstructural characteristics. NDE techniques and standards that will ultimately be applicable to production and quality control of high temperature materials and structures are still emerging. The needs range from flaw detection to below 100 micron levels in monolithic ceramics to global imaging of fiber architecture and matrix densification anomalies in composites. The needs are different depending on the processing stage, fabrication method, and nature of the finished product. The standards are discussed that must be developed in concert with advances in NDE technology, materials processing research, and fabrication development. High temperature materials and structures that fail to meet stringent specifications and standards are unlikely to compete successfully either technologically or in international markets.

Vary, Alex↗

NASA NTRS1991

Regional exploration in desert terrains - A guide to the use of Landsat Thematic Mapper imagery

This paper provides a guide for the acquisition, processing, and interpretation of Landsat Thematic Mapper (TM) imagery of desert terrains for use in regional exploration. Sun angle considerations, data quality cautions, noise suppression routines, band selections, data calibration, spectral enhancements, perceptual considerations of displays, and general interpretation guidelines are all discussed as components of an image-information extraction procedure.

Crippen, Robert E.↗

NASA NTRS1995

Planetary and Primitive Object Strength Measurement and Sampling Apparatus

Support is requested for continuation of a program of dynamic impact (harpoon) coring of planetary, comet, or asteroid surface materials. We have previously demonstrated that good quality cores are obtainable for planetary materials with compressive strengths less than 200 MPa. Since the dynamics of penetration are observable on a Discovery class spacecraft, which images the sampling operation, these data can be used with a model developed under this project, to measure in-situ strength and frictional strength of the crust of the object. During the last year we have developed a detailed analytic model of penetrator mechanics. Progress is reported for the solid penetrators experiments, the CIT penetrator model, and the impact spall sampling apparatus.

Ahrens, Thomas J.↗

NASA NTRS1999

Energy Minimization of Molecular Features Observed on the (110) Face of Lysozyme Crystals

Molecular dynamics and energy minimization have been carried out using the program XPLOR to check the plausibility of a model lysozyme crystal surface. The molecular features of the (110) face of lysozyme were observed using atomic force microscopy (AFM). A model of the crystal surface was constructed using the PDB file 193L, and was used to simulate an AFM image. Molecule translations, van der Waals radii, and assumed AFM tip shape were adjusted to maximize the correlation coefficient between the experimental and simulated images. The highest degree of 0 correlation (0.92) was obtained with the molecules displaced over 6 A from their positions within the bulk of the crystal. The quality of this starting model, the extent of energy minimization, and the correlation coefficient between the final model and the experimental data will be discussed.

Perozzo, Mary A.↗

NASA NTRS2007

Cloud Motion Vectors from MISR using Sub-pixel Enhancements

The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences - in speed of 2.4 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.

Davies, Roger↗

NASA NTRS2006

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

Yang, Wenze↗

NASA NTRS2000

Progress in Laser Based Carbon Nanotube Production and In-Situ Diagnostics at NASA/JSC

This paper focuses on the improvement of carbon nanotube production with the upgraded laser system operating at 60 Hz. The yield has increased by about five times with the new system, while the quality of the single wall nanotube (SWNT) is unchanged. Recent diagnostic data of spatial and temporal evolution of C2 in the laser ablation plume are obtained by imaging the plume area on a gated change coupled device. A three-laser setup is used to monitor nickel atoms in different parts of the plume by laser induced fluorescence (LIF). Measurements are made at different times after the ablating lasers. These results, along with the previous measurements of emission and LIF of C2 will be discussed. Our ultimate goal is to use these measurements to model the nanotube growth mechanism.

Arepalli, Sivaram↗

NASA NTRS2016

VIIRS Reflective Solar Band Radiometric and Stability Evaluation Using Deep Convective Clouds

This work takes advantage of the stable distribution of deep convective cloud (DCC) reflectance measurements to assess the calibration stability and detector difference in Visible Infrared Imaging Radiometer Suite (VIIRS) reflective bands. VIIRS Sensor Data Records (SDRs) from February 2012 to June 2015 are utilized to analyze the long-term trending, detector difference, and half angle mirror (HAM) side difference. VIIRS has two thermal emissive bands with coverage crossing 11 microns for DCC pixel identification. The comparison of the results of these two processing bands is one of the indicators of analysis reliability. The long-term stability analysis shows downward trends (up to approximately 0.4 per year) for the visible and near-infrared bands and upward trends (up to 0.5per year) for the short- and mid-wave infrared bands. The detector difference for each band is calculated as the difference relative to the average reflectance overall detectors. Except for the slightly greater than 1 difference in the two bands at 1610 nm, the detector difference is less than1 for other solar reflective bands. The detector differences show increasing trends for some short-wave bands with center wavelengths from 400 to 600 nm and remain unchanged for the bands with longer center wavelengths. The HAM side difference is insignificant and stable. Those short-wave bands from 400 to 600 nm also have relatively larger HAM side difference, up to 0.25.Comparing the striped images from SDR and the smooth images after the correction validates the analyses of detector difference and HAM side difference. These analyses are very helpful for VIIRS calibration improvement and thus enhance product quality

VIIRS↗

NASA NTRS2020

Review: Strategies for Using Satellite-Based Products in Modeling PM2.5 and Short-Term Pollution Episodes

Short-term air pollution episodes motivate improved understanding of the association between air pollution and acute morbidity and mortality episodes, and triggers required mitigation plans. A variety of methods have been employed to estimate exposure to air pollution episodes, including GIS-based dispersion models, interpolation between sparse monitoring sites, land-use regression models, optimization models, line- or area-dispersion plume models, and models using information from imaging satellites, often including land-use and meteorological variables. There has been increasing use of satellite-borne aerosol products for assessing short-term air quality events. They provide better spatial coverage, but currently at the price of low temporal coverage and rather crude spatial resolution. This brief review of using satellite data for modeling short-term air quality and pollution events. The review can be pursued as a practical guide for modeling air quality with satellite-based products, as it includes important questions that should be considered in both the study design as well as the model development stages. Progress in this field is detailed and includes published models and their use in environmental and health studies. Both current and future satellite-borne capabilities are covered. It also provides links to access and download relevant datasets and some R code for data processing and modeling.

Meytar Sorek-Hamer↗

NASA NTRS2020

The Precipitation Imaging Package: Assessment of Microphysical and Bulk Characteristics of Snow

Remote-sensing observations are needed to estimate the regional and global impacts of snow. However, to retrieve accurate estimates of snow mass and rate, these observations require augmentation through additional information and assumptions about hydrometeor properties. The Precipitation Imaging Package (PIP) provides information about precipitation characteristics and can be utilized to improve estimates of snowfall rate and accumulation. Here, the goal is to demonstrate the quality and utility of two higher-order PIP-derived products: liquid water equivalent snow rate and an approximation of volume-weighted density called equivalent density. Accuracy of the PIP snow rate and equivalent density is obtained through intercomparison with established retrieval methods and through evaluation with colocated ground-based observations. The results confirm the ability of the PIP-derived products to quantify properties of snow rate and equivalent density, and demonstrate that the PIP produces physically realistic snow characteristics. When compared to the National Weather Service (NWS) snow field measurements of six-hourly accumulation, the PIP-derived accumulations were biased only +2.48% higher. Additionally, this work illustrates fundamentally different microphysical and bulk features of low and high snow-to-liquid ratio events, through assessment of observed particle size distributions, retrieved mass coefficients, and bulk properties. Importantly, this research establishes the role that PIP observations and higher-order products can serve for constraining microphysical assumptions in ground-based and spaceborne remotely sensed snowfall retrievals.

Claire Pettersen↗

NASA NTRS2016

The First Focused Hard X-Ray Images of the Sun with NuSTAR

We present results from the first campaign of dedicated solar observations undertaken by the Nuclear Spectroscopic Telescope ARray (NuSTAR) hard X-ray (HXR) telescope. Designed as an astrophysics mission, NuSTAR nonetheless has the capability of directly imaging the Sun at HXR energies (3 keV) with an increase in sensitivity of at least two magnitude compared to current non-focusing telescopes. In this paper we describe the scientific areas where NuSTAR will make major improvements on existing solar measurements. We report on the techniques used to observe the Sun with NuSTAR, their limitations and complications, and the procedures developed to optimize solar data quality derived from our experience with the initial solar observations. These first observations are briefly described, including the measurement of the Fe K-shell lines in a decaying X-class flare, HXR emission from high in the solar corona, and full-disk HXR images of the Sun.

Grefenstette, Brian W.↗