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NASA NTRS2008

Online Visualization and Analysis of Merged Global Geostationary Satellite Infrared Dataset

The NASA Goddard Earth Sciences Data Information Services Center (GES DISC) is home of Tropical Rainfall Measuring Mission (TRMM) data archive. The global merged IR product also known as the NCEP/CPC 4-km Global (60 degrees N - 60 degrees S) IR Dataset, is one of TRMM ancillary datasets. They are globally merged (60 degrees N - 60 degrees S) pixel-resolution (4 km) IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 and GMS). The availability of data from METEOSAT-5, which is located at 63E at the present time, yields a unique opportunity for total global (60 degrees N- 60 degrees S) coverage. The GES DISC has collected over 8 years of the data beginning from February of 2000. This high temporal resolution dataset can not only provide additional background information to TRMM and other satellite missions, but also allow observing a wide range of meteorological phenomena from space, such as, mesoscale convection systems, tropical cyclones, hurricanes, etc. The dataset can also be used to verify model simulations. Despite that the data can be downloaded via ftp, however, its large volume poses a challenge for many users. A single file occupies about 70 MB disk space and there is a total of approximately 73,000 files (approximately 4.5 TB) for the past 8 years. In order to facilitate data access, we have developed a web prototype to allow users to conduct online visualization and analysis of this dataset. With a web browser and few mouse clicks, users can have a full access to over 8 year and over 4.5 TB data and generate black and white IR imagery and animation without downloading any software and data. In short, you can make your own images! Basic functions include selection of area of interest, single imagery or animation, a time skip capability for different temporal resolution and image size. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. The prototype will be integrated into GIOVANNI and existing GIOVANNI capabilities, such as, data download, Google Earth KMZ, etc will be available. Users will also be able to access other data products in the GIOVANNI family.

Liu, Zhong↗
NASA NTRS2009

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

Wind, Galina↗
NASA NTRS2007

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

This study compares cirrus particle effective radius retrieved by a CALIPSO-like method with two similar methods using MODIS, MODI Airborne Simulator (MAS), and GOES imagery. The CALIPSO-like method uses lidar measurements coupled with the split-window technique that uses the infrared spectral information contained at the 8.65-micrometer, 11.15-micrometer and 12.05-micrometer bands to infer the microphysical properties of cirrus clouds. The two other methods, sing passive remote sensing at visible and infrared wavelengths, are the operational MODIS cloud products (referred to by its archival product identifier MOD06 for MODIS Terra) and MODIS retrievals performed by the CERES team at LaRC (Langley Research Center) in support of CERES algorithms; the two algorithms will be referred to as MOD06- and LaRC-method, respectively. The three techniques are compared at two different latitudes: (i) the mid-latitude ice clouds study uses 18 days of observations at the Palaiseau ground-based site in France (SIRTA: Site Instrumental de Recherche par Teledetection Atmospherique) including a ground-based 532 nm lidar and the Moderate Resolution Imaging Spectrometer (MODIS) overpasses on the Terra Platform, (ii) the tropical ice clouds study uses 14 different flight legs of observations collected in Florida, during the intensive field experiment CRYSTAL-FACE (Cirrus Regional Study of Tropical Anvils and cirrus Layers-Florida Area Cirrus Experiment), including the airborne Cloud Physics Lidar (CPL) and the MAS. The comparison of the three methods gives consistent results for the particle effective radius and the optical thickness, but discrepancies in cloud detection and altitudes. The study confirms the value of an active remote-sensing method (CALIPSO-like) for the study of sub-visible ice clouds, in both mid-latitudes and tropics. Nevertheless, this method is not reliable in optically very thick tropical ice clouds.

Chiriaco, M.↗
NASA NTRS2000

BOREAS TE-6 Multiband Vegetation Imager Data

The BOREAS TE-6 team collected data in support of its efforts to examine the influence of vegetation and climate on the major carbon fluxes in boreal tree species. A newly developed ground-based canopy imaging system called an MVI was tested and used by the BOREAS TE-06 team to collect measurements of the canopy crap fraction (sky fraction), canopy gap-size distribution (size and frequency of gaps between foliage in canopy), branch architecture, and leaf angle distribution (fraction of leaf area in specific leaf inclination classes assuming azimuthal symmetry). Measurements of the canopy gap-size distribution are used to derive canopy clumping indices that can be used to adjust indirect LAI measurements made in nonrandom forests. These clumping factors will also help to describe the radiation penetration in clumped canopies more accurately by allowing for simple adjustments to Beer's law. Measurements of the above quantities were obtained at BOREAS NSA-OJP site in IFC-2 in 1994, at the SSA-OA in July 1995, and at the SSA-OBS and SSA-OA sites in IFC-2 in 1996. Modeling studies were also performed to further validate MVI measurements and to gain a more complete understanding of boreal forest canopy architecture. By using MVI measurements and Monte Carlo simulations, clumping indices as a function of zenith angle were derived for the three main boreal species studied during BOREAS. The analyzed data are stored in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distrobuted Activity Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS1992

Oregon transect: Comparison of leaf-level reflectance with canopy-level and modelled reflectance

The Oregon Transect Ecosystem Research (OTTER) project involves the collection of a variety of remotely-sensed and in situ measurements for characterization of forest biophysical and biochemical parameters. The project includes nine study plots located along an environmental gradient in west-central Oregon, extending from the Pacific coast inland approximately 300km. These plots represent a broad range in ecosystem structure and function. Within the OTTER project, the sensitivity of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) signal to absorption by foliar biochemicals is being examined. AVIRIS data were acquired over all plots in conjunction with the four OTTER Multi-sensor Aircraft Campaigns spanning the growing season. Foilage samples were gathered during each campaign for biochemical determination (at Ames Research Center), to estimate stand-level constituency at each plot. Directional-hemispheric leaf reflectance throughout the 400-2400nm region was measured in the laboratory as an aid to interpreting concurrent AVIRIS data. Obtaining leaf spectra in this manner reduces or eliminates the confounding influences of atmosphere, canopy architecture, and reflectance by woody components, understory, and exposed soils which are present in airborne observations. These laboratory spectra were compared to simulated spectra derived by inverting the PROSPECT leaf-level canopy reflectance derived from AVIRIS data by use of the LOWTRAN-7 atmospheric radiative-transfer model.

Johnson, Lee F.↗
NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗
NASA NTRSDate not supplied

Quantitative Phenotypic Analysis of Arabidopsis Thaliana Grown in Microgravity Using Soap, an Applied Artificial Intelligence

Phenotypic analysis is an essential step in studying the gravitropic responses and gravitational stress experienced by plants grown in microgravity. Many of the phenotypic traits analyzed in gravitropism studies, such as root length, leaf area, secondary root count, and number of root hairs, currently rely upon manual measurement methods for quantification. However, new advances in data analysis technology using artificial intelligence offer an opportunity for more efficient phenotypic analysis and a reduction of time spent in the data collection phase. In this project, the ability of a new artificially intelligent data collection software, SOAP (Simple Object Access Protocol), to collect and quantify phenotypic traits of Arabidopsis thaliana will be assessed. This project will test the measurements taken by an initial draft of the software. SOAP will take measurements of shoot length, a key phenotype used to assess A. thaliana stress response when grown in microgravity conditions. Shoot length measurements made by SOAP will be compared against a series of manual shoot length measurements. The comparison between the two methods of data measurement will provide valuable insight into the relative accuracy of SOAP and the margin of human error when conducting lab measurements.

Arabidopsis↗
NASA NTRSDate not supplied

LIPA: Lunar Ice Perception Algorithm

Introduction: The highest concentration of Lu-nar water-ice stores exists within the Permanently Shadowed Regions (PSRs) of the Lunar South Pole [1-3]. As such, the ability to locate in situ water-ice stores in an accurate, systematic, and safe manner will prove vital for future Lunar activities which rely on hydrogen-based resources. Here we show how the strong absorptive properties of ice can be exploited so that surface ice located in PSRs can be easily differentiated from the surrounding frozen regolith. Testbeds which simulate an icy lunar landscape were created and then systematically imaged using a mid-wave infrared (MWIR) camera system. Testbeds were imaged under two filter modes (1) high-absorption (high-abs) mode: whereby imagery captured were confined to a single central wave-length (CWL) of 3.15 ± 0.03 μm and (2) low-absorption (low-abs) mode: whereby imagery cap-tured were confined to a single CWL of 3.80 ± 0.04 μm (Figure 1). High- and low-absorption modes are related to the absorptive properties of ice at each selected wavelength, respectively. Corresponding images from each filter mode were differenced (i.e., pixels were subtracted) to enhance contrast between ice-bearing and non-ice-bearing pixels, and then fed into a semantic segmen-tation model. The model was trained to detect and differentiate between water, ice, shadows, and lunar regolith. Results: Modeling results accurately discrimi-nated ice from other materials (such as frozen lunar regolith) and were used to visually resolve the spa-tial extent of surface ice. Further, outputs produced through semantic segmentation were used to estimate water-ice contents in collected imagery [(Pixels with Class = “Water Ice”)/(Sum of Pixels)*100]. Summary: These works prove promising for future in situ resource utilization (ISRU) missions which employ robotics in combination with infrared camera systems to advance science objectives (e.g., locate water-ice in frozen regolith) on the lunar sur-face. References: [1] Cannon K. M., Deutsch A. N., Head J. W., and Britt D. T. (2020) Geophysical Re-search Letters, 46, e2020GL088920. [2] Honniball C. I. et al. (2021) Nature Astronomy 5, no. 2, 121-127. [3] Li S. et al. (2018) Proceedings of the National Academy of Sciences, 115(36), 8907-8912.

A. Slabic↗
NASA NTRS2017

Viscous Three-Dimensional Simulation of Flow in an Axial Low Pressure Compressor at Engine Icing Operating Points

Viscous three-dimensional simulations of the Honeywell ALF502R-5 low pressure compressor (sometimes called a booster) using the NASA Glenn code GlennHT have been carried out. A total of ten simulations were produced. Five operating points are investigated, with each point run with two different wall thermal conditions. These operating points are at, or near, points where engine icing has been determined to be likely. In the future, the results of this study will be used for further analysis such as predicting collection efficiency of ice particles and ice growth rates at various locations in the compressor. A mixing plane boundary condition is used between each blade row, resulting in convergence to steady state within each blade row. The k-omega turbulence model of Wilcox, combined with viscous grid spacing near the wall on the order of one, is used to resolve the turbulent boundary layers. For each of the operating points, heat transfer coefficients are generated on the blades and walls. The heat transfer coefficients are produced by running the operating point with two different wall thermal conditions and then solving simultaneously for the heat transfer coefficient and adiabatic wall temperature at each point. Average Nusselt numbers are calculated for the most relevant surfaces. The values are seen to scale with Reynolds number to approximately a power of 0.7. Additionally, images of surface distribution of Nusselt number are presented. Qualitative comparison between the five operating points show that there is relatively little change in the character of the distribution. The dominant observed effect is that of an overall scaling, which is expected due to Reynolds number differences. One interesting aspect about the Nusselt number distribution is observed on the casing (outer diameter) downstream of the exit guide vanes (EGVs). The Nusselt number is relatively high between the pairs of EGVs, with two lower troughs downstream of each EGV trailing edge. This is of particular interest since rather complex ice shapes have been observed in that region.

compressor↗
NASA NTRS2016

Derivation of Physical and Optical Properties of Midlatitude Cirrus Ice Crystals for a Size-Resolved Cloud Microphysics Model

Single-crystal images collected in mid-latitude cirrus are analyzed to provide internally consistent ice physical and optical properties for a size-resolved cloud microphysics model, including single-particle mass, projected area, fall speed, capacitance, single-scattering albedo, and asymmetry parameter. Using measurements gathered during two flights through a widespread synoptic cirrus shield, bullet rosettes are found to be the dominant identifiable habit among ice crystals with maximum dimension (Dmax) greater than 100μm. Properties are therefore first derived for bullet rosettes based on measurements of arm lengths and widths, then for aggregates of bullet rosettes and for unclassified (irregular) crystals. Derived bullet rosette masses are substantially greater than reported in existing literature, whereas measured projected areas are similar or lesser, resulting in factors of 1.5-2 greater fall speeds, and, in the limit of large Dmax, near-infrared single-scattering albedo and asymmetry parameter (g) greater by approx. 0.2 and 0.05, respectively. A model that includes commonly imaged side plane growth on bullet rosettes exhibits relatively little difference in microphysical and optical properties aside from approx. 0:05 increase in mid-visible g primarily attributable to plate aspect ratio. In parcel simulations, ice size distribution, and g are sensitive to assumed ice properties.

asymmetry↗
NASA NTRSDate not supplied

Low Temperature Formation of Carbonaceous Grains from Hydrocarbons and PAHs with the COSmIC Facility

Complex carbon molecules and ions are ubiquitous in space and form the building blocks of the carbonaceous components of cosmic dust grains, ultimately contributing to the formation of planets. We report experimental investigations of the low temperature chemical pathways leading to the formation of cosmic grain analogs from gas phase molecular precursors to better understand the evolution of cosmic carbon. The study of the formation of dust is essential to understand and to quantify the budget of extraterrestrial organic molecules. Although dust plays an important role in the evolution of interstellar chemistry and in the formation of organic molecules, little is known on the formation and destruction processes of carbonaceous dust. The experiments were performed using the Cosmic Simulation Chamber (COSmIC) to generate and characterize solid grains formed from gas phase precursors under controlled conditions representative of astrophysical environments [1]. Using COSmIC, it is possible to investigate the evolution of cosmic carbon from the formation of neutral and ionized hydrocarbons and PAHs in the gas phase [2], to solid carbon grains [3, 4, 5]. This is achieved by using a pulsed slit discharge nozzle to produce an adiabatic jet expansion and cool down Ar-hydrocarbon and PAH gas mixtures to astrophysically relevant temperature before inducing chemistry by generating a plasma discharge in the stream of the expansion. This plasma induced chemistry results in the formation of complex molecules and solid particles, analogs of cosmic grains in situ in the plasma expansion (i.e., without wall effects) that are carried by the accelerated gas in the expansion, and collected on substrates placed a few centimeters downstream of the electrodes. The results of a preliminary solid phase ex-situ analysis of cosmic grain analogs produced from a series of gas mixtures including hydrocarbons such as CH4 and C2H2 [3] and PAHs [4, 5] found in circumstellar ejecta of late C stars will be discussed. SEM imaging was used to provide insight on the impact of the precursors on the morphology and growth structure of the grains produced [3]. Laser desorption mass spectrometry was used to identify the molecules making up the main structures within the condensed grains [4] while X-ray irradiation and X-ray photoemission spectroscopy were used to investigate the impact the impact of stellar X-rays on cosmic dust.

Carbonaceous Grains↗
NASA NTRS2009

Development of a Modified Vacuum Cleaner for Lunar Surface Systems

The National Aeronautics and Space Administration (NASA) mission to expand space exploration will return humans to the Moon with the goal of maintaining a long-term presence. One challenge that NASA will face returning to the Moon is managing the lunar regolith found on the Moon's surface, which will collect on extravehicular activity (EVA) suits and other equipment. Based on the Apollo experience, the issues astronauts encountered with lunar regolith included eye/lung irritation, and various hardware failures (seals, screw threads, electrical connectors and fabric contamination), which were all related to inadequate lunar regolith mitigation. A vacuum cleaner capable of detaching, transferring, and efficiently capturing lunar regolith has been proposed as a method to mitigate the lunar regolith problem in the habitable environment on lunar surface. In order to develop this vacuum, a modified "off-the-shelf" vacuum cleaner has been used to determine detachment efficiency, vacuum requirements, and optimal cleaning techniques to ensure efficient dust removal in habitable lunar surfaces, EVA spacesuits, and air exchange volume. During the initial development of the Lunar Surface System vacuum cleaner, systematic testing was performed with varying flow rates on multiple surfaces (fabrics and metallics), atmospheric (14.7 psia) and reduced pressures (10.2 and 8.3 psia), different vacuum tool attachments, and several vacuum cleaning techniques to determine the performance requirements for the vacuum cleaner. The data recorded during testing was evaluated by calculating percent removal, relative to the retained simulant on the tested surface. In addition, Scanning Electron Microscopy (SEM) imaging was used to determine particle size distribution retained on the surface. The scope of this paper is to explain the initial phase of vacuum cleaner development, including historical Apollo mission data, current state-of-the-art vacuum cleaner technology, and vacuum cleaner testing that has focused on detachment capabilities varying pressure environments.

Toon, Katherine P.↗
NASA NTRS2011

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Platnick, Steven E.↗
NASA NTRS2020

Medical Data Architecture Platform and Recommended Requirements for A Medical Data System for Exploration Missions

Minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions.In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗
NASA NTRS2020

Medical Data Architecture Platform and Recommended Requirements for a Medical Data System for Exploration Missions

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically- relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm of medical data management on the International Space Station. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products derived from the third MDA prototype development will directly inform exploration medical system requirements for Level of Care IV in Gateway missions. In fiscal year 2019, the MDA project developed Test Bed 3, the third iteration in a series of prototypes, that featured integrations with cognition tool data, ultrasound image analytics and core Flight Software (cFS). Maintaining a layered architecture design, the framework implemented a plug-in, modular approach in the integration of these external data sources. An early version of MDA Test Bed 3 software was deployed and operated in a simulated analog environment that was part of the Next Space Technologies for Exploration Partnerships (NextSTEP) Gateway tests of multiple habitat prototypes. In addition, the MDA team participated in the Gateway Test and Verification Demonstration, where the MDA cFS applications was integrated with Gateway-in-a-Box software to send and receive medically relevant data over a simulated vehicle network. This software demonstration was given to ExMC and Gateway Program stakeholders at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Also, the integrated prototypes served as a vehicle to provide Level 5 requirements for the Crew Health and Performance Habitat Data System for Gateway Missions (Medical Level of Care IV). In the upcoming fiscal year, the MDA project will continue to provide systems engineering and vertical prototypes to refine requirements for medical Level of Care IV and inform requirements for Level of Care V.

Krihak, M.↗
NASA NTRS2013

Multitemporal Cross-Calibration of the Terra MODIS and Landsat 7 ETM+ Reflective Solar Bands

In recent years, there has been a significant increase in the use of remotely sensed data to address global issues. With the open data policy, the data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) sensors have become a critical component of numerous applications. These two sensors have been operational for more than a decade, providing a rich archive of multispectral imagery for analysis of mutitemporal remote sensing data. This paper focuses on evaluating the radiometric calibration agreement between MODIS and ETM+ using the near-simultaneous and cloud-free image pairs over an African pseudo-invariant calibration site, Libya 4. To account for the combined uncertainties in the top-of-atmosphere (TOA) reflectance due to surface and atmospheric bidirectional reflectance distribution function (BRDF), a semiempirical BRDF model was adopted to normalize the TOA reflectance to the same illumination and viewing geometry. In addition, the spectra from the Earth Observing-1 (EO-1) Hyperion were used to compute spectral corrections between the corresponding MODIS and ETM+ spectral bands. As EO-1 Hyperion scenes were not available for all MODIS and ETM+ data pairs, MODerate resolution atmospheric TRANsmission (MODTRAN) 5.0 simulations were also used to adjust for differences due to the presence or lack of absorption features in some of the bands. A MODIS split-window algorithm provides the atmospheric water vapor column abundance during the overpasses for the MODTRAN simulations. Additionally, the column atmospheric water vapor content during the overpass was retrieved using the MODIS precipitable water vapor product. After performing these adjustments, the radiometric cross-calibration of the two sensors was consistent to within 7%. Some drifts in the response of the bands are evident, with MODIS band 3 being the largest of about 6% over 10 years, a change that will be corrected in Collection 6 MODIS processing.

MODIS↗
NASA NTRSDate not supplied

Low-Temperature Production of Cosmic Grains Analogs From Gas-Phase Molecular Precursors with the NASA Ames' COSmIC Facility

Complex carbon molecules and ions are ubiquitous in space and form the building blocks of carbonaceous cosmic dust grains, ultimately contributing to the formation of planets. Here, we report the first experimental investigations of the low temperature chemical pathways leading to the production of cosmic grain analogs from gas phase molecular precursors in order to better understand the evolution of cosmic carbon. The experiments were performed using the COsmic SImulation Chamber (COSmIC) to generate and characterize grains formed from gas phase precursors under controlled conditions representative of astrophysical environments [1]. Using COSmIC, it is possible to investigate the evolution of cosmic carbon from the formation of neutral and ionized gas phase hydrocarbons and PAHs [2], to carbon grains [3, 4]. This is achieved by using a discharge nozzle to (1) produce an adiabatic jet expansion and cool down Ar-hydrocarbon/PAH gas mixtures to astrophysically relevant temperature (150 K) before inducing chemistry by generating a plasma discharge in the stream of the expansion. This plasma-induced chemistry results in the formation of complex molecules and solid particles, analogs of cosmic grains. Solid grains are produced in-situ in the plasma expansion, carried by the accelerated gas in the expansion, and collected on substrates placed a few centimeters downstream of the electrodes. The results of a preliminary solid phase ex-situ analysis of cosmic grain analogs produced at low temperature in COSmIC from gas mixtures including molecular precursors of cosmic carbon grains, i.e., such as CH4 and C2H2 found in circumstellar ejecta of late C stars [3] as well as PAHs ubiquitously detected in IR emission bands seen in galactic and extragalactic environments [4] will be discussed. Scanning Electron Microscopy imaging was used to provide insight on the morphology and growth structure of the grains produced in COSmIC, and to investigate how the precursors used to produce the grains affect these parameters [3]. Laser desorption mass spectrometry was used to identify the molecules making up the main structures within the condensed grains [4]. NIR to FIR optical properties are characterized to provide critical information (functional groups, optical constants) to the scientific community, for use in radiative transfer models in particular, and to help decipher and enhance the return data from space observations.

F. Salama↗
NASA NTRS2018

Observing Ice Sublimation From Water-Doped Lunar Simulant at Cryogenic Temperatures

NASA's Resource Prospector (RP) mission is intended to characterize the three-dimensional nature of volatiles in lunar polar and permanently shadowed regions. The Near-Infrared Volatile Spectrometer System (NIRVSS) observes while a drill penetrates to a maximum depth of 1 m. Any 10 cm increment of soil identified as containing water ice can be delivered to a heating crucible with the evolved gas delivered to a gas chromatograph / mass spectrometer. NIRVSS consists of two components; a spectrometer box (SB) and bracket assembly (BA), connected by two fiber optic cables. The SB contains separate short- and long-wavelength spectrometers, SW and LW respectively, that collectively span the 1600-3400 nm range. The BA contains an IR emitter (lamp), drill observation camera (DOC, 2048 x 2048 CMOS detector), 8 different wavelength LEDs, and a longwave calibration sensor (LCS) measuring the surface emissivity at four IR wavelengths. Tests of various RP sub-systems have been under-taken in a large cryo-vacuum chamber at Glenn Re-search Center. The chamber accommodates a tube (1.2 m high x 25.4 cm diameter) filled with lunar simulant, NU-LHT-3M, prepared with known abundances of water. Thermocouples are embedded at different depths, and also across the surface of the soil tube. In the chamber the tube is cooled with LN2 as the pressure is reduced to approx. 5-6x10(exp -6) Torr. For the May 2016 tests two soil tubes were prepared with initially 2.5 Wt.% water. The shroud surrounding the soil tube was held at different temperatures for each tube to simulate a warm and cold lunar environment. Table 1 provides a summary of experimental conditions and Figure 1 shows the nominal view of the NIRVSS components, the drill foot, and the top of the soil tube. Once the average soil temperature reached approx. 178 K, drilling commenced. During drilling activities NIRVSS was alternating between obtaining spectra and obtaining images. Here we discuss NIRVSS spectral data obtained during controlled drill percussions.

Roush, T. L.↗