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NASA NTRS2008

Assessment and Mission Planning Capability For Quantitative Aerothermodynamic Flight Measurements Using Remote Imaging

High resolution calibrated infrared imagery of vehicles during hypervelocity atmospheric entry or sustained hypersonic cruise has the potential to provide flight data on the distribution of surface temperature and the state of the airflow over the vehicle. In the early 1980 s NASA sought to obtain high spatial resolution infrared imagery of the Shuttle during entry. Despite mission execution with a technically rigorous pre-planning capability, the single airborne optical system for this attempt was considered developmental and the scientific return was marginal. In 2005 the Space Shuttle Program again sponsored an effort to obtain imagery of the Orbiter. Imaging requirements were targeted towards Shuttle ascent; companion requirements for entry did not exist. The engineering community was allowed to define observation goals and incrementally demonstrate key elements of a quantitative spatially resolved measurement capability over a series of flights. These imaging opportunities were extremely beneficial and clearly demonstrated capability to capture infrared imagery with mature and operational assets of the US Navy and the Missile Defense Agency. While successful, the usefulness of the imagery was, from an engineering perspective, limited. These limitations were mainly associated with uncertainties regarding operational aspects of data acquisition. These uncertainties, in turn, came about because of limited pre-flight mission planning capability, a poor understanding of several factors including the infrared signature of the Shuttle, optical hardware limitations, atmospheric effects and detector response characteristics. Operational details of sensor configuration such as detector integration time and tracking system algorithms were carried out ad hoc (best practices) which led to low probability of target acquisition and detector saturation. Leveraging from the qualified success during Return-to-Flight, the NASA Engineering and Safety Center sponsored an assessment study focused on increasing the probability of returning spatially resolved scientific/engineering thermal imagery. This paper provides an overview of the assessment task and the systematic approach designed to establish confidence in the ability of existing assets to reliably acquire, track and return global quantitative surface temperatures of the Shuttle during entry. A discussion of capability demonstration in support of a potential Shuttle boundary layer transition flight test is presented. Successful demonstration of a quantitative, spatially resolved, global temperature measurement on the proposed Shuttle boundary layer transition flight test could lead to potential future applications with hypersonic flight test programs within the USAF and DARPA along with flight test opportunities supporting NASA s project Constellation.

Horvath, Thomas↗
NASA NTRSDate not supplied

Towards a Combined Low-Earth Orbit Lightning Climatology: Current Work and Assessing South Atlantic Anomaly Influence

This presentation discusses the current status and ongoing work towards a low-Earth orbit (LEO) lightning climatological product that includes both Lightning Imaging Sensors (LIS) and the Optical Transient Detector (OTD). The project builds upon the work by Cecil et al. (2014) to include the LIS on the International Space Station (ISS), featuring additional inter-instrumental comparisons to more accurately depict the unique capabilities of each instrument. A closer examination of the interference from the South Atlantic Anomaly (SAA) was also conducted on all three LEO sensors. The SAA is a region of the magnetosphere roughly spanning the south-central Atlantic wherein the inner Van Allen radiation belts are closer to Earth than anywhere else, subjecting spacecraft in LEO to significantly higher radiation flux levels. This radiation can produce interference with the LIS and OTD instruments, manifesting as non-lightning luminous events. While these events can be identified easily enough, they can occur in such quantities that they overwhelm the sensors’ processors and effectively ‘blind’ them. This is called the First-In First-Out (FIFO) buffer overflow, and this blinded time reduced the instruments’ view-time as a result. The FIFO overflow and view-time can reliably be used to track the SAA interference (Clark et al. 2024), which allows for the lightning counts attributable to the SAA to be assessed. The impact that the SAA had on the quality of observations from the LEO lightning instrumentation and the significance for the resulting climatological products was investigated. Substantial areas of interference were identified for all three instruments using the view-time and quality flags, each with a unique shape and temporal evolution. The temporal evolution and general region affected are of particular importance when constructing a climatological product, as there are notable reductions to view-time over prolonged periods across a lightning-rich region. However, a temporal element also makes isolating the subsequent impact on the lightning signal significantly more challenging. Lightning counts in this region are highly seasonal and exhibit inter-annual variability, which is compounded by the nature of LEO observations. This study includes preliminary analysis of the impact that the SAA has on the lightning counts given the notable impact shown in the metadata.

Austin G Clark↗
NASA NTRS2020

Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.

EPIC↗
NASA NTRS2001

Three-Dimensional Stereoscopic Tracking Velocimetry and Experimental/Numerical Comparison of Directional Solidification

Measurement of three-dimensional (3-D) three-component velocity fields is of great importance in both ground and space experiments for understanding materials processing and fluid physics. The experiments in these fields most likely inhibit the application of conventional planar probes for observing 3-D phenomena. Here, we present the investigation results of stereoscopic tracking velocimetry (STV) for measuring 3-D velocity fields, which include diagnostic technology development, experimental velocity measurement, and comparison with analytical and numerical computation. STV is advantageous in system simplicity for building compact hardware and in software efficiency for continual near-real-time monitoring. It has great freedom in illuminating and observing volumetric fields from arbitrary directions. STV is based on stereoscopic observation of particles-Seeded in a flow by CCD sensors. In the approach, part of the individual particle images that provide data points is likely to be lost or cause errors when their images overlap and crisscross each other especially under a high particle density. In order to maximize the valid recovery of data points, neural networks are implemented for these two important processes. For the step of particle overlap decomposition, the back propagation neural network is utilized because of its ability in pattern recognition with pertinent particle image feature parameters. For the step of particle tracking, the Hopfield neural network is employed to find appropriate particle tracks based on global optimization. Our investigation indicates that the neural networks are very efficient and useful for stereoscopically tracking particles. As an initial assessment of the diagnostic technology performance, laminar water jets with and without pulsation are measured. The jet tip velocity profiles are in good agreement with analytical predictions. Finally, for testing in material processing applications, a simple directional solidification apparatus is built for experimenting with a metal analog of succinonitrile. Its 3-D velocity field at the liquid phase is then measured to be compared with those from numerical computation. Our theoretical, numerical, and experimental investigations have proven STV to be a viable candidate for reliably measuring 3-D flow velocities. With current activities are focused on further improving the processing efficiency, overall accuracy, and automation, the eventual efforts of broad experimental applications and concurrent numerical modeling validation will be vital to many areas in fluid flow and materials processing.

Lee, David↗
NASA NTRSDate not supplied

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗
NASA NTRS2012

Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly

A paper describes the Thermal Infrared Sensor (TIRS), a QWIP-based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a far-infrared imager operating in the pushbroom mode with two IR channels: 10.8 and 12 microns. The focal plane will contain three 640x512 QWIP arrays mounted on a silicon substrate. The silicon substrate is a custom-fabricated carrier board with a single layer of aluminum interconnects. The general fabrication process starts with a 4-in. (approx.10-cm) diameter silicon wafer. The wafer is oxidized, a single substrate contact is etched, and aluminum is deposited, patterned, and alloyed. This technology development is aimed at incorporating three large-format infrared detecting arrays based on GaAs QWIP technology onto a common focal plane with precision alignment of all three arrays. This focal plane must survive the rigors of flight qualification and operate at a temperature of 43 K (-230 C) for five years while orbiting the Earth. The challenges presented include ensuring thermal compatibility among all the components, designing and building a compact, somewhat modular system and ensuring alignment to very tight levels. The multi-array focal plane integrated onto a single silicon substrate is a new application of both QWIP array development and silicon wafer scale integration. The Invar-based assembly has been tested to ensure thermal reliability.

Jhabvala, Murzy↗
NASA NTRS2016

High Precision Sunphotometer using Wide Dynamic Range (WDR) Camera Tracking

The NASA Ames Sun-photometer-Satellite Group, DOE, PNNL Atmospheric Sciences and Global Change Division, and NASA Goddards AERONET (AErosol RObotic NETwork) team recently collaborated on the development of a new airborne sunphotometry instrument that provides information on gases and aerosols extending far beyond what can be derived from discrete-channel direct-beam measurements, while preserving or enhancing many of the desirable AATS features (e.g., compactness, versatility, automation, reliability). The enhanced instrument combines the sun-tracking ability of the current 14-Channel NASA Ames AATS-14 with the sky-scanning ability of the ground-based AERONET Sunsky photometers, while extending both AATS-14 and AERONET capabilities by providing full spectral information from the UV (350 nm) to the SWIR (1,700 nm). Strengths of this measurement approach include many more wavelengths (isolated from gas absorption features) that may be used to characterize aerosols and detailed (oversampled) measurements of the absorption features of specific gas constituents. The Sky Scanning Sun Tracking Airborne Radiometer (3STAR) replicates the radiometer functionality of the AATS14 instrument but incorporates modern COTS technologies for all instruments subsystems. A 19-channel radiometer bundle design is borrowed from a commercial water column radiance instrument manufactured by Biospherical Instruments of San Diego California (ref, Morrow and Hooker)) and developed using NASA funds under the Small Business Innovative Research (SBIR) program. The 3STAR design also incorporates the latest in robotic motor technology embodied in Rotary actuators from Oriental motor Corp. having better than 15 arc seconds of positioning accuracy. Control system was designed, tested and simulated using a Hybrid-Dynamical modeling methodology. The design also replaces the classic quadrant detector tracking sensor with a wide dynamic range camera that provides a high precision solar position tracking signal as well as an image of the sky in the 45 field of view around the solar axis, which can be of great assistance in flagging data for cloud effects or other factors that might impact data quality.

aerosols↗
NASA NTRS2020

Continuity of MODIS and VIIRS Snow Cover Extent Data Products for Development of an Earth Science Data Record

An Earth Observing System global snow cover extent data products record at moderate spatial resolution (375–500 m) began in February 2000 with the Moderate-resolution Imaging Spectroradiometer (MODIS) instrument onboard the Terra satellite. The record continued with the Aqua MODIS in July 2002, the Suomi-National Polar Platform (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) in January 2012 and continues with the Joint Polar Satellite System-1 (JPSS-1) VIIRS, launched in November of 2017. The objective of this work is to develop a snow cover extent Earth Science Data Record (ESDR) using different satellites, sensors and algorithms. There are many issues to understand when data from different algorithms and sensors are used over a decade-scale time period to create a continuous dataset. Issues may also arise with sensor degradation and even differences in sensor band locations. In this paper we describe development of an ESDR derived from existing MODIS and VIIRS data products and demonstrate continuity among the products. The MODIS and VIIRS snow cover detection algorithms produce very similar daily snow cover maps, with 90–97% agreement in snow cover extent (SCE) in different landscapes. Differences in SCE between products ranged from 2–15% and are attributable to convolved factors of viewing geometry, pixel spread across a scan and time of observation. Compared at a common grid size of 1 km, there is a mean of 95% agreement in SCE and a difference range of 1–10% between the MODIS and VIIRS SCE maps. Mapping sensor observations to a coarser resolution grid reduces the effect of the factors convolved in the 500 m tile to tile comparisons. We conclude that the MODIS and VIIRS SCE data products are reliable constituents of a moderate-resolution ESDR.

snow cover extent↗
NASA NTRS2013

Electrical Capacitance Volume Tomography for the Packed Bed Reactor ISS Flight Experiment

Fixed packed bed reactors are compact, require minimum power and maintenance to operate, and are highly reliable. These features make this technology a highly desirable unit operation for long duration life support systems in space. NASA is developing an ISS experiment to address this technology with particular focus on water reclamation and air revitalization. Earlier research and development efforts funded by NASA have resulted in two hydrodynamic models which require validation with appropriate instrumentation in an extended microgravity environment. To validate these models, the instantaneous distribution of the gas and liquid phases must be measured.Electrical Capacitance Volume Tomography (ECVT) is a non-invasive imaging technology recently developed for multi-phase flow applications. It is based on distributing flexible capacitance plates on the peripheral of a flow column and collecting real-time measurements of inter-electrode capacitances. Capacitance measurements here are directly related to dielectric constant distribution, a physical property that is also related to material distribution in the imaging domain. Reconstruction algorithms are employed to map volume images of dielectric distribution in the imaging domain, which is in turn related to phase distribution. ECVT is suitable for imaging interacting materials of different dielectric constants, typical in multi-phase flow systems. ECVT is being used extensively for measuring flow variables in various gas-liquid and gas-solid flow systems. Recent application of ECVT include flows in risers and exit regions of circulating fluidized beds, gas-liquid and gas-solid bubble columns, trickle beds, and slurry bubble columns. ECVT is also used to validate flow models and CFD simulations. The technology is uniquely qualified for imaging phase concentrations in packed bed reactors for the ISS flight experiments as it exhibits favorable features of compact size, low profile sensors, high imaging speed, and flexibility to fit around columns of various shapes and sizes. ECVT is also safer than other commonly used imaging modalities as it operates in the range of low frequencies (1 MHz) and does not radiate radioactive energy. In this effort, ECVT is being used to image flow parameters in a packed bed reactor for an ISS flight experiment.

Tomography↗
NASA NTRS2010

Cast Glance Near Infrared Imaging Observations of the Space Shuttle During Hypersonic Re-Entry

High resolution calibrated infrared imagery of the Space Shuttle was obtained during hypervelocity atmospheric entries of the STS-119, STS-125 and STS128 missions and has provided information on the distribution of surface temperature and the state of the airflow over the windward surface of the Orbiter during descent. This data collect was initiated by NASA s Hypersonic Thermodynamic Infrared Measurements (HYTHIRM) team and incorporated the use of air- and land-based optical assets to image the Shuttle during atmospheric re-entry. The HYTHIRM objective is to develop and implement a set of mission planning tools designed to establish confidence in the ability of an existing optical asset to reliably acquire, track and return global quantitative surface temperatures of the Shuttle during entry. On Space Shuttle Discovery s STS-119 mission, NASA flew a specially modified thermal protection system tile and instrumentation package to monitor heating effects from boundary layer transition during re-entry. On STS-119, the windward airflow on the port wing was deliberately disrupted by a four-inch wide and quarter-inch tall protuberance built into the modified tile. In coordination with this flight experiment, a US Navy NP-3D Orion aircraft was flown 28 nautical miles below Discovery and remotely monitored surface temperature of the Orbiter at Mach 8.4 using a long-range infrared optical package referred to as Cast Glance. Approximately two months later, the same Navy Cast Glance aircraft successfully monitored the surface temperatures of the Orbiter Atlantis traveling at approximately Mach 14.3 during its return from the successful Hubble repair mission. In contrast to Discovery, Atlantis was not part of the Boundary Layer Transition (BLT) flight experiment, thus the vehicle was not configured with a protuberance on the port wing. In September 2009, Cast Glance was again successful in capturing infrared imagery and monitoring the surface temperatures on Discovery s next flight, STS-128. Again, NASA flew a specially modified thermal protection system tile and instrumentation package to monitor heating effects from boundary layer transition during re-entry. During this mission, Cast Glance was able to image laminar and turbulent flow phenomenology optimizing data collection for Mach 14.7. The purpose of this paper is to describe key elements associated with STS-119/125/128 mission planning and execution from the perspective of the Cast Glance flight crew that obtained the imagery. The paper will emphasize a human element of experience, expertise and adaptability seamlessly coupled with Cast Glance system and sensor technology required to manually collect the required imagery. Specific topics will include a near infrared (NIR) camera upgrade that was implemented just prior to the missions, how pre-flight radiance modeling was utilized to optimize the IR sensor configuration, communications, the development of aircraft test support positions based upon Shuttle trajectory information, support to contingencies such as Shuttle one orbit wave-offs/west coast diversions and then the Cast Glance perspective during an actual Shuttle imaging mission.

Tack, Steve↗
NASA NTRS2019

An Experimental Investigation of a Wing-Fuselage Junction Model in the NASA Langley 14- by 22-Foot Subsonic Tunnel

Current turbulence models, such as those employed in Reynolds-averaged Navier-Stokes CFD, are unable to reliably predict the onset and extent of the three-dimensional separated flow that typically occurs in wing-fuselage junctions. To critically assess, as well as to improve upon, existing turbulence models, experimental validation-quality flow-field data in the junction region is needed. In this report, we present an overview of experimental measurements on a wing-fuselage junction model that addresses this need. The experimental measurements were performed in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The model was a full-span wing-fuselage body that was configured with truncated DLR-F6 wings, both with and without leading-edge extensions at the wing root. The model was tested at a fixed chord Reynolds number of 2.4 million, and angles-of-attack ranging from -10 degrees to +10 degrees were considered. Flow-field measurements were performed with a pair of miniature laser Doppler velocimetry (LDV) probes that were housed inside the model and attached to three-axis traverse systems. One LDV probe was used to measure the separated flow field in the trailing-edge junction region. The other LDV probe was alternately used to measure the flow field in the leading-edge region of the wing and to measure the incoming fuselage boundary layer well upstream of the leading edge. Both LDV probes provided measurements from which all three mean velocity components, all six independent components of the Reynolds-stress tensor, and all ten independent components of the velocity triple products were calculated. In addition to the flow-field measurements, static and dynamic pressures were measured at selected locations on the wings and fuselage of the model, infrared imaging was used to characterize boundary-layer transition, oil-flow visualization was used to visualize the separated flow in the leading- and trailing-edge regions of the wing, and unsteady shear stress was measured at limited locations using capacitive shear-stress sensors. Sample results from the measurement techniques employed during the test are presented and discussed.

Kegerise, Michael A.↗
NASA NTRS2011

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Murphy, Kevin J.↗
NASA NTRS2020

SNPP VIIRS Reflective Solar Bands On-Orbit Calibration Using the Moon

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi National Polar-Orbiting Partnership (SNPP) satellite has been on orbit for more than eight years since its launch on October 28, 2011. The VIIRS has 22 spectral bands, among which 14 are reflective solar bands(RSBs) covering a spectral range from 0.41 to 2.25 m. The VIIRS RSBs are primarily calibrated on-orbit by an onboard solar diffuser (SD) panel and a solar diffuser stability monitor (SDSM). Besides the SD and SDSM calibration, the RSBs are scheduled to view the Moon approximately monthly through the instrument’s space view (SV). The lunar observations have also been used to calibrate the RSBs on-orbit since early mission. Due to the non uniformity of the SD’s degradation, the calibration coefficients that are derived from the SD/SDSM calibration have long-term biases, especially at short wavelengths. In addition, the SDSM has no capability to monitor the SD degradation beyond 0.935 m, resulting in long-term bias in the shortwave infrared bands, about 0.72% for band M8 (1.238 m). These biases induce significant errors and long-term drifts in the VIIRS sensor data records (SDR) and consequently in the environmental data records (EDR). Unlike the SD, the Moon is a known stable target and any temporal drifts observed while viewing the Moon can be attributed to the sensor’s degradation. Thus, the VIIRS lunar calibration is used to track the RSB on-orbit changes, especially to provide an accurate long-term baseline. Due to the non-uniformity of the lunar surface, the lunar irradiance, instead of the lunar radiance, is used to calibrate the RSBs. The lunar irradiance strongly depends on lunar view geometry and it is still a challenge to accurately characterize the geometric effects associated with the lunar measurements and any residual errors can induce seasonal oscillations in the derived calibration coefficients. The errors of the geometric dependence correction induce seasonal oscillations in the derived RSB lunar calibration coefficients. In this paper, the algorithms for the view geometric effect correction are significantly improved, resulting in a significant reduction in the seasonal oscillations observed in the calibration coefficient time-series. The lunar and SD/SDSM calibration results are properly incorporated to generate a set of hybrid calibration coefficients and implementation of these coefficients is shown to significantly improve the long-term stability of the VIIRS SDR. This is of fundamental importance in making accurate Earth observations from which reliable and high quality science products are generated. The consequent improvements in SNPP VIIRS RSB SDRs and EDRs are shown and discussed. The lunar calibration methodology can be directly applied to follow-on VIIRS instruments.

Junqiang Sun↗
NASA NTRS1998

A Multi-Scale Sampling Strategy for Detecting Physiologically Significant Signals in AVIRIS Imagery

Models of photosynthetic production at ecosystem and global scales require multiple input parameters specifying physical and physiological surface features. While certain physical parameters (e.g., absorbed photosynthetically active radiation) can be derived from current satellite sensors, other physiologically relevant measures (e.g., vegetation type, water status, carboxylation capacity, or photosynthetic light-use efficiency), are not generally directly available from current satellite sensors at the appropriate geographic scale. Consequently, many model parameters must be assumed or derived from independent sources, often at an inappropriate scale. An abundance of ecophysiological studies at the leaf and canopy scales suggests strong physiological control of vegetation-atmosphere CO2 and water vapor fluxes, particularly in evergreen vegetation subjected to diurnal or seasonal stresses. For example hot, dry conditions can lead to stomatal closure, and associated "downregulation" of photosynthetic biochemical processes, a phenomenon often manifested as a "midday photosynthetic depression". A recent study with the revised simple biosphere (SiB2) model demonstrated that photosynthetic downregulation can significantly impact global climate. However, at the global scale, the exact significance of downregulation remains unclear, largely because appropriate physiological measures are generally unavailable at this scale. Clearly, there is a need to develop reliable ways of extracting physiologically relevant information from remote sensing. Narrow-band spectrometers offer many opportunities for deriving physiological parameters needed for ecosystem and global scale photosynthetic models. Experimental studies on the ground at the leaf- to stand-scale have indicated that several narrow-band features can be used to detect plant physiological status. One physiological signal is caused by xanthophyll cycle pigment activity, and is often expressed as the Photochemical Reflectance Index (PRI). Because the xanthophyll cycle pigments are photoregulatory pigments closely linked to photosynthetic function, this index can be used to derive relative photosynthetic rates. An additional signal with physiological significance is the 970 nm water absorption band, which provides a measure of liquid water content. This feature has been quantified both using a simple 2-band ratio (900/970 nm, here referred to as the "Water Band Index" or WBI;), and using the "continuum removal" method. Current atmospheric correction methods for AVIRIS imagery also obtain quantitative expressions of surface liquid water absorption based on the 970 nm water band and may be comparable to ground-based estimates of water content using this feature. However, physiological interpretations of both the PRI and the WBI are best understood at the leaf and canopy scales, where complications of atmospheric interference and complex stand and landscape features can be minimized, and where experimental manipulations can be readily applied. Currently it is not known whether these physiological indices can be used to derive meaningful physiological information from AVIRIS imagery. In addition to the problem of atmospheric interference, another challenge is that any simple physiological index can be confounded by multiple factors unrelated to physiology, and this problem can become more severe at progressively larger spatial scales. For example, previous work has suggested that both the PRI and the WBI, are strongly correlated with other optical measures of canopy structure (e.g., the Normalized Difference Vegetation Index or green vegetation fraction), indicating a confounding effect of structure on physiological signals at the larger, landscape scale. Furthermore, the normal operating mode of most imaging spectrometers does not allow simultaneous, ground truthing at a level of detail needed for physiological sampling. Additionally, manipulative experiments of physiology are difficult to apply at a geographic scale suitable for comparison with remote imagery, which often works at spatial scales that are several orders of magnitude larger than those typically used for physiological studies. These limitations require the consideration of alternative approaches to validating physiological information derived from AVIRIS data. In this report, we present a multi-scale sampling approach to detecting physiologically significant signals in narrow-band spectra. This approach explores the multi-dimensional data space provided by narrow-band spectrometry, and combines AVIRIS imagery at a large scale, with ground spectral sampling at an intermediate scale, and detailed ecophysiological measurements at a fine scale, to examine seasonally and spatially changing relationships between multiple structural and physiological variables. Examples of this approach are provided by simultaneous sampling of the Normalized Difference Vegetation Index (NDVI), an index of fractional PAR interception and green vegetation cover, the Water Band Index (WBI, an index of liquid water absorption, and the Photochemical Reflectance Index (PRI, an index of xanthophyll cycle pigment activity and photosynthetic light-use efficiency. By directly linking changing optical properties sampled on the ground with measurable physiological states, we hope to develop a basis for interpreting similar signals in AVIRIS imagery.

Gamon, John A.↗
NASA NTRS2016

Forward Skirt Structural Testing on the Space Launch System (SLS) Program

Structural testing was performed to evaluate heritage forward skirts from the Space Shuttle program for use on the Space Launch System (SLS) program. One forward skirt is located in each solid rocket booster. Heritage forward skirts are aluminum 2219 welded structures. Loads are applied at the forward skirt thrust post and ball assembly. Testing was needed because SLS ascent loads are roughly 40% higher than Space Shuttle loads. Testing objectives were to determine margins of safety, demonstrate reliability, and validate analytical models. Two forward skirts were structurally tested using the test configuration. The test stand applied loads to the thrust post. Four hydraulic actuators were used to apply axial load and two hydraulic actuators were used to apply radial and tangential loads. The first test was referred to as FSTA-1 (Forward Skirt Structural Test Article) and was performed in April/May 2014. The purpose of FSTA-1 was to verify the ultimate capability of the forward skirt subjected to ascent ultimate loads. Testing consisted of two liftoff load cases taken to 100% limit load followed by an ascent load case taken to 110% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The second test was referred to as FSTA-2 and performed in July/August of 2014. The purpose of FSTA-2 was to verify the ultimate capability of the forward skirt subjected to liftoff ultimate loads. Testing consisted of six liftoff load cases taken to 100% limit load followed by the six liftoff cases taken to 140% limit load. Two ascent load cases were then tested to 100% limit load. The forward skirt was unloaded to no load after each test case. Lastly, the forward skirt was tested to 140% limit and then to failure using the ascent loads. The forward skirts on FSTA-1 and FSTA-2 successfully carried all applied liftoff and ascent load cases. Both FSTA-1 and FSTA-2 were tested to failure by increasing the ascent loads. Failure occurred in the forward skirt thrust post radius. The forward skirts on FSTA-1 and FSTA-2 had nearly identical failure modes. FSTA-1 failed at 1.72 times limit load and FSTA-2 failed at 1.62 times limit load. This difference is primarily attributed to variation in material properties in the thrust post region. Test data were obtained from strain gages, deflection gages, ARAMIS digital strain measurement, acoustic emissions, and high-speed video. Strain gage data and ARAMIS strain were compared to finite element (FE) analysis predictions. Both the forward skirt and tooling were modeled. This allows the analysis to simulate the loading as close as possible to actual test configuration. FSTA-1 and FSTA-2 were instrumented with over 200 strain gages to ensure all possible failure modes could be captured. However, it turned out that three gages provided critical strain data. One was located in the post bore and two on the post radius. More gages were not specified due to space limitations and the desire to not interfere with the use of the ARAMIS system on the post radius. Measured strains were compared to analysis results for the load cycle to failure. Note that FSTA-1 gages were lost before failure was reached. FSTA-2 gages made it to the failure load but one of the radius gages was lost before testing began. This gage was not replaced because of the time and cost associated with disassembly of the test structure. Correlation to analysis was excellent for FSTA-1. FSTA-2 was not quite as good because there was more residual strain from previous load cycles. FSTA-2 was loaded and unloaded with 12 liftoff cases and two ascent cases before taking the skirt to failure. FSTA-1 only had two liftoff cases and one ascent case before taking the skirt to failure. The ARAMIS system was used to determine strain at the post radius by processing digital images of a speckled paint pattern. Digital cameras recorded images of the speckled paint pattern. ARAMIS strain results for FSTA-2 just prior to failure. Note a high strain location develops near the left side. This high strain compares well to analysis prediction for both FSTA-1 and FSTA-2. The strain at this location was also plotted versus limit load. Both FSTA-1 and FSTA-2 had excellent correlation between ARAMIS and analysis strains. Acoustic emission (AE) sensors were used to monitor for damage formation that may occur during testing (e.g., crack formation and growth or propagation). AE was very important because after disassembly of FSTA-1, a crack was observed in the ball fitting radius. The ball fitting did not crack on FSTA-2. AE data was used to reconstruct when the crack occurred. The AE energy versus time plot for FSTA. The energy increased considerably at 850 seconds (152% limit load), indicating a crack could have formed at this point. The only visual evidence found that could have corresponded to this was the crack that initiated in the ball fitting. The cracks in the forward skirt aluminum structures would likely have been lower energy due to a lower modulus and all that were found after failure correlated to occurring after the initial crack in the post radius. This was verified by high-speed cameras used to record the failure.

Lohrer, J. D.↗