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NASA NTRS2016

In-Orbit Operation of the ASTRO-H SXS

We summarize all of the in-orbit operations of the soft x-ray spectrometer (SXS) onboard the ASTROH (Hitomi) satellite. The satellite was launched on February 17, 2016, and the communication with the satellite ceased on March 26, 2016. The SXS was still in the commissioning phase, in which the set-ups were progressively changed. This paper is intended to serve as a concise reference of the events in orbit in order to properly interpret the SXS data taken during its short lifetime and as a test case for planning the in-orbit operation for future microcalorimeter missions.

Tsujimoto, Masahiro↗

NASA NTRS2017

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.The talk will present an overview of current efforts in ESI, the role members of IEEE GRSS play, and discuss recent developments in data preservation and provenance.

Remote Sensing↗

NASA NTRS2017

Development of an Axisymmetric Afterbody Test Case for Turbulent Flow Separation Validation

As identified in the CFD Vision 2030 Study commissioned by NASA, validation of advanced RANS models and scale-resolving methods for computing turbulent flows must be supported by improvements in high-quality experiments designed specifically for CFD implementation. A new test platform referred to as the Axisymmetric Afterbody allows for a range of flow behaviors to be studied on interchangeable afterbodies while facilitating access to higher Reynolds number facilities. A priori RANS computations are reported for a risk-reduction configuration to demonstrate critical variation among turbulence model results for a given afterbody, ranging from barely-attached to mild separated flow. The effects of body nose geometry and tunnel-wall boundary condition on the computed afterbody flow are explored to inform the design of an experimental test program.

Disotell, Kevin J.↗

NASA NTRS2017

The Effectiveness of Shrouding on Reducing Meshed Spur Gear Power Loss Test Results

Gearbox efficiency is reduced at high rotational speeds due to windage drag and viscous effects on rotating, meshed gear components. A goal of NASA aeronautics rotorcraft research is aimed at propulsion technologies that improve efficiency while minimizing vehicle weight. Specifically, reducing power losses to rotorcraft gearboxes would allow gains in areas such as vehicle payload, range, mission type, and fuel consumption. To that end, a gear windage rig has been commissioned at NASA Glenn Research Center to measure windage drag on gears and to test methodologies to mitigate windage power losses. One method used in rotorcraft gearbox design attempts to reduce gear windage power loss by utilizing close clearance walls to enclose the gears in both the axial and radial directions. The close clearance shrouds result in reduced drag on the gear teeth and reduced power loss. For meshed spur gears, the shrouding takes the form of metal side plates and circumferential metal sectors. Variably positioned axial and radial shrouds are incorporated in the NASA rig to study the effect of shroud clearance on gearbox power loss. A number of researchers have given experimental and analytical results for single spur gears, with and without shrouding. Shrouded meshed spur gear test results are sparse in the literature. Windage tests were run at NASA Glenn using meshed spur gears at four shroud configurations: unshrouded, shrouded (max. axial, max. radial), and two intermediate shrouding conditions. Results are compared to available meshed spur gear power loss data analyses as well as single spur gear data analyses.

windage↗

NASA NTRS2017

Astrobee Guest Science Guide

The Astrobee Research Facility will maintain three identical free-flying Astrobee robots on the ISS. After the Astrobees are launched and commissioned in 2018, they will replace the SPHERES robots that have been operating on the ISS since 2006 (Fig. 2). Over the years, the SPHERES have been among the most-used payloads on the ISS, supporting dozens of experiments from a variety of guest scientists. In the next section, we'll talk about past SPHERES experiments as possible inspiration for your future research on Astrobee. Compared to SPHERES, the Astrobee robots will offer many new capabilities and will require less astronaut time to support, so we hope the new facility will be able to fly experiments much more often.

Benavides, Jose↗

NASA NTRS2017

Overview of NASA's MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) snow-cover Earth System Data Records

Knowledge of the distribution, extent, duration and timing of snowmelt is critical for characterizing the Earth's climate system and its changes. As a result, snow cover is one of the Global Climate Observing System (GCOS) essential climate variables (ECVs). Consistent, long-term datasets of snow cover are needed to study interannual variability and snow climatology. The NASA snow-cover datasets generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua spacecraft and the Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) are NASA Earth System Data Records (ESDR). The objective of the snow-cover detection algorithms is to optimize the accuracy of mapping snow-cover extent (SCE) and to minimize snow-cover detection errors of omission and commission using automated, globally applied algorithms to produce SCE data products. Advancements in snow-cover mapping have been made with each of the four major reprocessings of the MODIS data record, which extends from 2000 to the present. MODIS Collection 6 (C6) and VIIRS Collection 1 (C1) represent the state-of-the-art global snow cover mapping algorithms and products for NASA Earth science. There were many revisions made in the C6 algorithms which improved snow-cover detection accuracy and information content of the data products. These improvements have also been incorporated into the NASA VIIRS snow cover algorithms for C1. Both information content and usability were improved by including the Normalized Snow Difference Index (NDSI) and a quality assurance (QA) data array of algorithm processing flags in the data product, along with the SCE map.The increased data content allows flexibility in using the datasets for specific regions and end-user applications.Though there are important differences between the MODIS and VIIRS instruments (e.g., the VIIRS 375m native resolution compared to MODIS 500 m), the snow detection algorithms and data products are designed to be as similar as possible so that the 16C year MODIS ESDR of global SCE can be extended into the future with the S-NPP VIIRS snow products and with products from future Joint Polar Satellite System (JPSS) platforms.These NASA datasets are archived and accessible through the NASA Distributed Active Archive Center at the National Snow and Ice Data Center in Boulder, Colorado.

Earth System Data Record↗

NASA NTRS2016

Airship Industry Study

There is an ongoing Government interest in the potential of airships for cargo transport; Conducting vertical or near-vertical airlift of heavy, outsized freight with little or no ground infrastructure is an attractive cargo transport option. USTRANSCOM wanted to understand the principal issues that are holding back commercial development of airship transports. NASA Ames Research Center was commissioned by USTRANSCOM to study the airship industry’s ability to design, develop, and operate cargo airships. Principal study objectives were to identify: (1) Current and near term state of the cargo airship industry; (2) Roadblocks hindering cargo airship development; (3) Steps needed to remove impediments to cargo airship deployment.

Hochstetler, Ron↗

NASA NTRS2017

Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): Data and Tools for Dynamic Management and Decision Support

The Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organizations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adelie) and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year.Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

Humphries, G. R. W.↗

NASA NTRS2017

The CHARIS High-Contrast Integral-Field Spectrograph

One of the leading direct Imaging techniques, particularly in ground-based imaging, uses a coronagraphic system and integral field spectrograph (IFS). The Coronagraphic High Angular Resolution Imaging Spectrograph (CHARIS) is an IFS that has been built for the Subaru telescope. CHARIS has been delivered to the observatory and now sits behind the Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system. CHARIS has 'high' and 'low' resolution operating modes. The "high-resolution" mode is used to characterize targets in J, H, and K bands at ~R70. The "low-resolution" prism is meant for discovery and spans J+H+K bands (1.15-2.37 microns) with a spectral resolution of ~R18. This discovery mode has already proven better than 15-sigma detections of HR8799c,d,e when combining ADI+SDI. Using SDI alone, planets c and d have been detected in a single 24 second image. The CHARIS team is optimizing instrument performance and refining ADI+SDI recombination to maximize our contrast detection limit. In addition to the new observing modes, CHARIS has demonstrated a design with high robustness to spectral crosstalk. CHARIS is in the final stages of commissioning, with the instrument open for science observations beginning February 2017. Here we review the science case, design, on-sky performance, engineering observations of exoplanet and disk targets, and specific lessons learned for extremely high contrast imagers. Key design aspects that will be demonstrated are crosstalk optimization, wavefront correction using the IFS image, lenslet tolerancing, the required spectral resolution to fit exoplanet atmospheres, and the utility of the spectrum in achieving higher contrast detection limits.

Groff, Tyler D.↗

NASA NTRS2018

Star & Planet Formation Studies and Opportunities with SOFIA

Star formation, the most fundamental process in the universe, is linked to planet formation and thus to the origin and evolution of life. We have a general outline of how planets and stars form, yet unraveling the details of the physics and chemistry continues to challenge us. The infrared and submillimeter part of the spectrum hold the most promise for studying the beginnings of star formation. The observational landscape recently shaped by Spitzer, Herschel and ALMA, continues to challenge our current theories. SOFIA, the Stratospheric Observatory for Infrared Astronomy, equipped with state-of-the-art infrared instrumentation to a vantage point at 45,000 feet (13.7 kilometers) flight altitude that is above 99.9 percent of the Earth's water vapor, enables observations in the infrared through terahertz frequencies not possible from the ground. SOFIA is a community observatory, about to start its sixth annual observing cycle. My talk will focus on recent results in advancing star and planet formation processes using SOFIAʼs imaging and polarimetric capabilities, and the upcoming science enabled by the 3rd generation instrument High-Resolution Mid-Infrared Spectrometer (HIRMES) to be commissioned in 2019. I will show how mid-infrared imaging is used to test massive star formation theories, how far-infrared polarimetry on sub-parsec scales is directly testing the role of magnetic fields in molecular clouds, and how velocity-resolved high-resolution spectroscopy will push forward our understanding of proto-planetary disk science. I will also summarize upcoming opportunities with the SOFIA observatory. For the latest news about your flying observatory, see https://sofia.usra.edu/.

Star formation↗

NASA NTRS2018

Total and Spectral Solar Irradiance Sensor (TSIS) Project Status

TSIS-1 studies the Sun's energy input to Earth and how solar variability affects climate. TSIS-1 will measure both the total amount of light that falls on Earth, known as the total solar irradiance (TSI), and how that light is distributed among ultraviolet, visible and infrared wavelengths, called solar spectral irradiance (SSI). TSIS-1 will provide the most accurate measurements of sunlight and continue the long-term climate data record. TSIS-1 includes two instruments: the Total Irradiance Monitor (TIM) and the Spectral Irradiance Monitor (SIM), integrated into a single payload on the International Space Station (ISS). The TSIS-1 TIM and SIM instruments are upgraded versions of the two instruments that are flying on the Solar Radiation and Climate Experiment (SORCE) mission launched in January 2003. NASA Goddard's TSIS project responsibilities include project management, system engineering, safety and mission assurance, and engineering oversight for TSIS-1. TSIS-1 was installed on the International Space Station in December 2017. At the end of the 90-day commissioning phase, responsibility for TSIS-1 operations transitions to the Earth Science Mission Operations (ESMO) project at Goddard for its 5-year operations. NASA contracts with the University of Colorado Laboratory for Atmospheric and Space Physics (LASP) for the design, development and testing of TSIS-1, support for ISS integration, science operations of the TSIS-1 instrument, data processing, data evaluation, calibration and delivery to the Goddard Earth Science Data and Information Services Center (GES DISC).

TSIS↗

NASA NTRS2017

Nominal 30-M Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, is a starting point to develop high-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based Geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015-2016. These composites were generated using a median-mosaic of five bands (blue, green, red, near-infrared, NDVI) during each of the two periods (period 1: January-June 2016 and period 2: July-December 2015) plus a 30-m slope layer derived from the Shuttle Radar Topographic Mission (SRTM) elevation dataset. Second, we selected Cropland/Non-cropland training samples (sample size 9791) from various sources in GEE to create pixel-based classifications. As supervised classification algorithm, Random Forest (RF) was used as the primary classifier because of its efficiency, and when over-fitting issues of RF happened due to the noise of input training data, Support Vector Machine (SVM) was applied to compensate for such defects in specific areas. Third, the Recursive Hierarchical Segmentation (RHSeg) algorithm was employed to generate an object-oriented segmentation layer based on spectral and spatial properties from the same input data. This layer was merged with the pixel-based classification to improve segmentation accuracy. Accuracies of the merged 30-m crop extent product were computed using an error matrix approach in which 1754 independent validation samples were used. In addition, a comparison was performed with other available cropland maps as well as with LULC maps to show spatial similarity. Finally, the cropland area results derived from the map were compared with UN FAO statistics. The independent accuracy assessment showed a weighted overall accuracy of 94, with a producers accuracy of 85.9 (or omission error of 14.1), and users accuracy of 68.5 (commission error of 31.5) for the cropland class. The total net cropland area (TNCA) of Africa was estimated as 313 Mha for the nominal year 2015.

Cropland mapping; cropland areas; 30-m; Landsat-8;↗

NASA NTRS2018

Smallholder Crop Area Mapped with Wall-To-Wall WorldView Sub-Meter Panchromatic Image Texture: A Test Case for Tigray, Ethiopia

Global food production in the developing world occurs within sub-hectare fields that are difficult to identify with moderate resolution satellite imagery. Knowledge about the distribution of these fields is critical in food security programs. We developed a semi-automated image segmentation approach using wall-to-wall sub-meter imagery with high-performance computing to map crop area (CA) throughout Tigray, Ethiopia that encompasses over 41,000 km (exp 2). Multiple processing streams were tested to minimize mapping error while applying five unique smoothing kernels to capture differences in land surface texture associated to CA. Typically, very-small fields (mean < 2 ha) have a smooth image roughness compared to natural scrub/shrub woody vegetation at the ~1m scale and these features can be segmented in panchromatic imagery with multi-level histogram thresholding. Multi-temporal very-high resolution (VHR) panchromatic imagery with multi-spectral VHR are sufficient in extracting critical CA information needed in food security programs. A 2011 to 2015 CA map was produced, using over 3000 WorldView-1 panchromatic images wall-to-wall in 1/2 deg mosaics for Tigray, Ethiopia. CA was evaluated with nearly 3000 WorldView-2 2m multispectral 250 X 250 m image subsets by seven expert interpretations, and with in-situ global positioning system photography. CA estimates ranged from 32 to 41% in sub regions of Tigray with median maximum per bin commission and omission errors of 11% and 1% respectively, with most of the error occurring in bins <15%. This empirical, simple, and low direct cost approach via U.S. government license agreement to access commercial VHR data, could be a viable big-data high-performance computing methodology to extract wall-to-wall CA for other regions of the world that have very-small agriculture fields with similar image texture."

Ethiopia↗

NASA NTRS2017

The Large UV/Optical/Infrared Surveyor (LUVOIR): Decadal Mission Concept Design Update

In preparation for the 2020 Astrophysics Decadal Survey, NASA has commissioned the study of four large mission concepts, including the Large Ultraviolet / Optical / Infrared (LUVOIR) Surveyor. The LUVOIR Science and Technology Definition Team (STDT) has identified a broad range of science objectives including the direct imaging and spectral characterization of habitable exoplanets around sun-like stars, the study of galaxy formation and evolution, the epoch of reionization, star and planet formation, and the remote sensing of Solar System bodies. NASA’s Goddard Space Flight Center (GSFC) is providing the design and engineering support to develop executable and feasible mission concepts that are capable of the identified science objectives. We present an update on the first of two architectures being studied: a 15-meter-diameter segmented-aperture telescope with a suite of serviceable instruments operating over a range of wavelengths between 100 nm to 2.5 microns. Four instruments are being developed for this architecture: an optical / near-infrared coronagraph capable of 10(exp -10) contrast at inner working angles as small as 2 lambda/D; the LUVOIR UV Multi-object Spectrograph (LUMOS), which will provide low- and medium-resolution UV (100 – 400 nm) multi-object imaging spectroscopy in addition to far-UV imaging; the High Definition Imager (HDI), a high-resolution wide-field-of-view NUV-Optical-IR imager; and a UV spectro-polarimeter being contributed by Centre National d’Etudes Spatiales (CNES). A fifth instrument, a multi-resolution optical-NIR spectrograph, is planned as part of a second architecture to be studied in late 2017.

Decadal Study; Astrophysics; LUVOIR↗

NASA NTRS2017

Spacecraft and Instrument Photoelectrons Measured by the Dual Electron Spectrometers on MMS

Secondary electrons are continuously generated via photoemission from sunlit spacecraft and instrument surfaces. These particles can subsequently contaminate low-energy channels of electron sensors. Spacecraft photoelectrons are measured at energies below that of a positive spacecraft potential and can be removed at the expense of energy resolution. However, fluxes of photoelectrons generated inside electron instruments are independent of spacecraft potential and must be fully characterized in order to correct electron data. Here we present observations of spacecraft and instrument photoelectron populations measured with the Dual Electron Spectrometers (DES) on NASA's Magnetospheric Multiscale (MMS) mission. We leverage observations from Earth's nightside plasma sheet taken during MMS commissioning and develop an empirical model of instrument photoelectrons. This model is used with DES velocity distribution functions to correct plasma moments and has been made publicly available on the MMS science data center for use by the scientific community.

photoelectrons↗

NASA NTRS2018

The James Webb Space Telescope: Observatory Status and Preparations for Launch

The James Webb Space Telescope (JWST) is a large (6.5 meter) segmented aperture telescope equipped with near- and mid-infrared instruments (0.6-28 microns), all of which are passively cooled to approximately 40 degrees Kelvin by a 5-layer sunshield while the mid-infrared instrument is actively cooled to 7 degrees Kelvin. The JWST telescope recently completed its cryogenic test program and the sunshield has been fully integrated and deployed. JWST is currently in the final stages of the test program at the Observatory level. The current estimated JWST performance metrics will be presented, such as the image quality, pointing stability, sensitivity, and stray light backgrounds. The JWST development status and future plans will be described for the final testing, launch, and commissioning.

McElwain, Michael↗

NASA NTRS2018

Using Reanalysis in Crop Monitoring and Forecasting Systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-imited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Reanalysis↗

NASA NTRS2017

In-orbit Operation of the Soft X-Ray Spectrometer Onboard the Hitomi Satellite

We summarize all of the in-orbit operations of the soft x-ray spectrometer (SXS) onboard the ASTRO-H (Hitomi) satellite. The satellite was launched on February 17, 2016, and the communication with the satellite ceased on March 26, 2016. The SXS was still in the commissioning phase, in which the set-ups were progressively changed. This paper is intended to serve as a concise reference of the events in orbit in order to properly interpret the SXS data taken during its short lifetime and as a test case for planning the in-orbit operation for future microcalorimeter missions.

ASTRO-H↗