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NASA NTRS2017

NASA Downscaling Project

A team of researchers from NASA Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, along with university partners at UCLA, conducted an investigation to explore whether downscaling coarse resolution global climate model (GCM) predictions might provide valid insights into the regional impacts sought by decision makers. Since the computational cost of running global models at high spatial resolution for any useful climate scale period is prohibitive, the hope for downscaling is that a coarse resolution GCM provides sufficiently accurate synoptic scale information for a regional climate model (RCM) to accurately develop fine scale features that represent the regional impacts of a changing climate. As a proxy for a prognostic climate forecast model, and so that ground truth in the form of satellite and in-situ observations could be used for evaluation, the MERRA and MERRA-2 reanalyses were used to drive the NU-WRF regional climate model and a GEOS-5 replay. This was performed at various resolutions that were at factors of 2 to 10 higher than the reanalysis forcing. A number of experiments were conducted that varied resolution, model parameterizations, and intermediate scale nudging, for simulations over the continental US during the period from 2000-2010. The results of these experiments were compared to observational datasets to evaluate the output.

Ferraro, Robert↗
NASA NTRS2017

OSIRIS-REx Asterod Sample Return Mission

OSIRIS-REx is NASA's third New Frontiers Program mission, following New Horizons that completed a flyby of Pluto in 2015 and the Juno mission to Jupiter that has just begun science operations. The OSIRIS-REx mission's primary objective is to collect pristine surface samples of a carbonaceous asteroid and return to Earth for analysis. Carbonaceous asteroids and comets are 'primitive' bodies that preserved remnants of the Solar System starting materials and through their study scientists can learn about the origin and the earliest evolution of the Solar System. The OSIRIS-REx spacecraft was successfully launched on September 8, 2016, beginning its seven year journey to asteroid 101955 Bennu. The robotic arm will collect 60-2000 grams of material from the surface of Bennu and will return to Earth in 2023 for worldwide distribution by the Astromaterials Curation Facility at NASA Johnson Space Center. The name OSIRIS-REx embodies the mission objectives (1) Origins: Return and analyze a sample of a carbonaceous asteroid, (2) Spectral Interpretation: Provide ground-truth for remote observation of asteroids, (3) Resource Identification: Determine the mineral and chemical makeup of a near-Earth asteroid (4) Security: Measure the non-gravitational that changes asteroidal orbits and (5) Regolith Explorer: Determine the properties of the material covering an asteroid surface. Asteroid Bennu may preserve remnants of stardust, interstellar materials and the first solids to form in the Solar System and the molecular precursors to the origin of life and the Earth's oceans. Bennu is a potentially hazardous asteroid, with an approximately 1 in 2700 chance of impacting the Earth late in the 22nd century. OSIRIS-REx collects from Bennu will help formulate the types of operations and identify mission activities that astronauts will perform during their expeditions. Such information is crucial in preparing for humanity's next steps beyond low Earthy orbit and on to deep space destinations.

Nakamura-Messinger, Keiki↗
NASA NTRS2017

Assessment of Satellite-Derived Surface Reflectances by NASA's CAR Airborne Radiometer over Railroad Valley, Nevada

CAR (Cloud Absorption Radiometer) is a multi-angular and multi-spectral airborne radiometer instrument, whose radiometric and geometric characteristics are well calibrated and adjusted before and after each flight campaign. CAR was built by NASA (National Aeronautics and Space Administration) in 1984. On 16 May 2008, a CAR flight campaign took place over the well-known calibration and validation site of Railroad Valley in Nevada (38.504 deg N, 115.692 deg W).The campaign coincided with the overpasses of several key EO (Earth Observation) satellites such as Landsat-7, Envisat and Terra. Thus, there are nearly simultaneous measurements from these satellites and the CAR airborne sensor over the same calibration site. The CAR spectral bands are close to those of most EO satellites. CAR has the ability to cover the whole range of azimuth view angles and a variety of zenith angles depending on altitude and, as a consequence, the biases seen between satellite and CAR measurements due to both unmatched spectral bands and unmatched angles can be significantly reduced. A comparison is presented here between CARs land surface reflectance (BRF or Bidirectional Reflectance Factor) with those derived from Terra/MODIS (MOD09 and MAIAC), Terra/MISR, Envisat/MERIS and Landsat-7. In this study, we utilized CAR data from low altitude flights (approx. 180 m above the surface) in order to minimize the effects of the atmosphere on these measurements and then obtain a valuable ground-truth data set of surface reflectance. Furthermore, this study shows that differences between measurements caused by surface heterogeneity can be tolerated, thanks to the high homogeneity of the study site on the one hand, and on the other hand, to the spatial sampling and the large number of CAR samples. These results demonstrate that satellite BRF measurements over this site are in good agreement with CAR with variable biases across different spectral bands. This is most likely due to residual aerosol effects in the EO derived reflectances.

calibration↗
NASA NTRS2017

Kepler Certified False Positive Table

This document describes the Kepler Certied False Positive table hosted at the Exoplanet Archive1, herein referred to as the CFP table. This table is the result of detailed examination by the Kepler False Positive Working Group (FPWG) of declared false positives in the Kepler Object of Interest (KOI) tables (see, for example, Batalha et al. (2012); Burke et al.(2014); Rowe et al. (2015); Mullally et al. (2015); Coughlin et al. (2015b)) at the Exoplanet Archive. A KOI is considered a false positive if it is not due to a planet orbiting the KOI's target star. The CFP table contains all KOIs in the Exoplanet Archive cumulative KOI table. The purpose of the CFP table is to provide a list of certified false positive KOIs. A KOI is certified as a false positive when, in the judgement of the FPWG, there is no plausible planetary interpretation of the observational evidence, which we summarize by saying that the evidence for a false positive is compelling. This certification process involves detailed examination using all available data for each KOI, establishing a high-reliability ground truth set. The CFP table can be used to estimate the reliability of, for example, the KOI tables which are created using only Kepler photometric data, so the disposition of individual KOIs may differ in the KOI and CFP tables. Follow-up observers may find the CFP table useful to avoid observing false positives.

Kepler↗
NASA NTRS2017

Robust Exploration and Commercial Missions to the Moon Using LANTR Propulsion and Lunar Liquid Oxygen Derived from FeO-Rich Pyroclastic Deposits

Studies conducted by NASA and its contractors (early 1980s early 1990s) indicated a substantial benefit from using lunar-derived propellants specifically lunar-derived LO2 (LLO2) or LUNOX in a lunar space transportation system (LTS). With a LTS using LO2/LH2 chemical rockets, approx. 6 kilograms (kg) of mass in low Earth orbit (LEO) is required to place 1 kg of payload on the lunar surface (LS). Of this 6 kg, approx. 70% (4.2 kg) is propellant and 6/7th of this mass (3.6 kg) is oxygen assuming an O/H MR 6:1. Since the cost of placing a kilogram of mass on the LS is approx. 6X the cost of delivering it to LEO, the ability to produce and utilize LUNOX or lunar-derived LO2 and hydrogen (LLH2) from lunar polar ice (LPI) deposits can provide significant mission leverage. Providing LUNOX for use in fuel cells, life support systems and LO2/LH2 chemical rockets used on lunar landing vehicles (LLVs), can allow high value cargo (people, manufacturing and scientific equipment, etc.) to be transported to LEO, then to the Moon instead of bulk LO2 propellant. Oxygen is abundant in the lunar regolith (approx. 43% by mass) and can be extracted using a variety of techniques, such as hydrogen reduction of ilmenite (FeOTiO2) or FeO-rich volcanic glass (orange soil) discovered during the Apollo 17 mission to Taurus-Littrow. While considerable interest has been expressed about mining and processing LPI for rocket propellant, ground truth must first be established to quantify the physical state of the ice (e.g., its vertical thickness and areal extent, levels of soil contamination, etc.) and the deep, extremely cold (approx. 26-100 K) permanently shadowed craters where the ice resides.

Nuclear Thermal Propulsion↗
NASA NTRS2017

Testing the Accuracy of Data-Driven MHD Simulations of Active Region Evolution

Models for the evolution of the solar coronal magnetic field are vital for understanding solar activity, yet the best measurements of the magnetic field lie at the photosphere, necessitating the development of coronal models which are "data-driven" at the photosphere. We present an investigation to determine the feasibility and accuracy of such methods. Our validation framework uses a simulation of active region (AR) formation, modeling the emergence of magnetic flux from the convection zone to the corona, as a ground-truth data set, to supply both the photospheric information and to perform the validation of the data-driven method. We focus our investigation on how the accuracy of the data-driven model depends on the temporal frequency of the driving data. The Helioseismic and Magnetic Imager on NASA's Solar Dynamics Observatory produces full-disk vector magnetic field measurements at a 12-minute cadence. Using our framework we show that ARs that emerge over 25 hours can be modeled by the data-driving method with only approximately 1 percent error in the free magnetic energy, assuming the photospheric information is specified every 12 minutes. However, for rapidly evolving features, under-sampling of the dynamics at this cadence leads to a strobe effect, generating large electric currents and incorrect coronal morphology and energies. We derive a sampling condition for the driving cadence based on the evolution of these small-scale features, and show that higher-cadence driving can lead to acceptable errors. Future work will investigate the source of errors associated with deriving plasma variables from the photospheric magnetograms as well as other sources of errors, such as reduced resolution, instrument bias, and noise.

Leake, James E.↗
NASA NTRS2018

Coordinated Satellite Observations of the Very Low Frequency Transmission Through the Ionospheric D Layer at Low Latitudes, Using Broadband Radio Emissions from Lightning

Both ray theory and full-wave models of very low frequency transmission through the ionospheric D layer predict that the transmission is greatly suppressed near the geomagnetic equator. We use data from the low-inclination Communication/Navigation Outage Forecast System satellite to test this semiquantitatively, for broadband very low frequency emissions from lightning. Approximate ground-truthing of the incident wavefields in the Earth-ionosphere waveguide is provided by the World Wide Lightning Location Network. Observations of the wavefields at the satellite are provided by the Vector Electric Field Instrument aboard the satellite. The data set comprises whistler observations with the satellite at magnetic latitudes<26deg. Thus, our conclusions, too, must be limited to the near-equatorial region and are not necessarily predictive of midlatitude whistler properties. We find that in most broadband recordings of radio waves at the satellite, very few of the lightning strokes result in a detectable radio pulse at the satellite. However, in a minority of the recordings, there is enhanced transmission of very low frequency lightning emissions through the D layer, at a level exceeding model predictions by at least an order of magnitude. We show that kilometric-scale D-layer irregularities may be implicated in the enhanced transmission. This observation of sporadic enhancements at low magnetic latitude, made with broadband lightning emissions, is consistent with an earlier review of D-layer transmission for transmission from powerful man-made radio beacons.

Jacobson, Abram R.↗
NASA NTRS2018

Instrumentation for Lunar Volatile Analysis

Understanding the available lunar resources is key to incorporating their availability into exploration architectures. Previous lunar missions have provided insight into the potential resources on the moon as an initial step enabling in-situ resource utilization (ISRU). Orbiting missions, such as Clementine and Lunar Prospector, have mapped the lunar polar region and found enhanced hydrogen signals on kilometer-scale resolution. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission provided the first direct measurement of water ice in a permanently shadowed region. Future missions will provide ground truth data to measure and quantify lunar volatiles.One approach to exploration capitalizes on commercial partnerships for Class D risk aware missions. Partnerships with commercial partners enable rapid design cycles, leveraging the investment of the commercial industry in instrument development. Modified Commercial off the Shelf (COTS) hardware can be utilized to enhance capabilities in exploration missions. The hardware under development at the Kennedy Space Center for availability within the Commercial Lunar Payload Services opportunities capitalizes on modified COTS, enabling an aggressive delivery schedule and low-cost development. The modified hardware has been integrated and tested in a thermal vacuum environment, with final flight modifications currently in work. The use of a modified COTS instruments will be discussed for space applications.

Captain, J.↗
NASA NTRS2015

CubeSat with Nanostructured Sensing Instrumentation for Planetary Exploration

This report provides a summary of the work performed under NIAC Phase I award NNX15AL86G entitled "CubeSat with Nanostructured Sensing Instrumentation for Planetary Exploration". The objective of this research is to investigate the feasibility of an innovative, low cost, CubeSat based planetary mission concept for in situ "ground truth"analysis of small asteroids and comets. The project includes an instrument study and a mission/spacecraft design study. The instrument study concerns with the development of anew TiO2 nanotube sensor with integrated compound semiconductor nanowires to determine surface composition element via neutron activated analysis (NAA). The mission/spacecraft design study concerns with the development of CubeSat based lander to small asteroids and comets. The Phase I study suggests that our concept is feasible and could provide significant benefit to NASA's future planetary missions. This research was carried out at the University of Southern California and the University of Utah.

Satellites↗
NASA NTRS2018

Weathering in the Forelands of Two Rapidly Retreating Alpine Glaciers of Volcanic Bedrock in the Three Sisters, Oregon, USA

The glaciers of the Three Sisters volcanoes in Cascadia have retreated dramatically over the past century. In order to understand ongoing chemical weathering and solute transport in the proglacial valleys, waters were sampled from glacier outwash streams, local snowmelt, and proglacial springs and lakes at Collier and Diller Glaciers. To understand weathering and transport processes in the proglacial plains, infrared orbital remote sensing data was used to map compositional variability and highlight weathering products, which were then ground-truthed with laboratory mineralogical and chemical analyses of sediments. The hydrochemistry is significantly affected by a sub- and proglacial mafic weathering system lacking carbonate minerals. Here we report major ion concentrations in meltwaters for the summer 2016 and 2017 melt seasons. Total cation concentrations range from 3 to 250 μeq/l and dissolved bicarbonate concentrations range from 2 to 200 μeq/l. Other dissolved anions are negligible compared to bicarbonate. Dissolved silica concentrations range from 2 to 260 μmol/l, comparable to total dissolved cation concentrations. The highest cation and silica concentrations were measured in moraine-sourced springs. Compositional remote sensing analysis identified alteration zones in the proglacial plains at both Collier and Diller indicating potential hydrated silica. This analysis is consistent with laboratory analysis of sediment samples, which indicate the presence of poorly crystalline phases weathering products, including hydrated silica. Weathered materials are preferentially deposited on moraines due to aeolian and glacial transport, as well as intra-moraine alteration, and at abandoned stream terraces due to fluvial transport. Geochemical measurements indicate that the predominant form of chemical weathering in these periglacial mafic systems is the carbonation of feldspar as well as reactive volcanic glass. The presence of poorly crystalline silicates, as indicated by remote sensing datasets and laboratory analysis, is consistent with rapid weathering of feldspars and glass and formation of Fe-Al-Si-bearing mineraloids in these proglacial valleys. This weathering regime has wide-ranging implications for atmospheric CO2 drawdown due to cold-climate volcanic rock weathering.

Rutledge, Alicia M.↗
NASA NTRS2018

Enriching the Twitter Stream Increasing Data Mining Yield and Quality Using Machine Learning

Social media data streams are important sources of real-time and historical global information for science applications. At the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), we are exploring the Twitter data stream for its potential in augmenting the validation program of NASA Earth science missions, specifically the Global Precipitation Measurement (GPM) mission. We have implemented a tweet processing infrastructure that outputs classified precipitation tweets. Inputs are "passive" tweets, along with a smaller number of tweets from "active" participants, i.e., those knowingly contributing to our effort. The "active" tweets, presumably of higher quality, enrich the Twitter stream. "Active" sources include data scraped from other social media (e.g., public Facebook posts) and data from existing crowdsourcing programs (e.g., mPING reports). In addition, there is likely relevant precipitation information in images and documents that are the end points of links often included in tweets. Information derived from these "active" sources could then be tweeted into the Twitter stream, thus enriching its quality. The objective of our current work is to mine these tweet­ linked images and documents, using neural networks, to increase the information content and quality related to precipitation. For images, we classified them as either precipitation-related or not. For training and validation, we used images obtained via the Google custom search API. We created two models: (1) by training a simple Convolutional Neural Network and (2) by using transfer learning principles to adapt a pre-trained object recognition model. For documents, both those linked to tweets and the tweet contents, we trained Hierarchical Attention Networks to determine precipitation occurrence, type, and intensity. For training and validation, we used a keyword-filtered tweet data set labelled with ground truth data from Dark Sky (an API to retrieve weather-related labels) and the National Severe Storms Laboratory's Multi­ Radar/Multi-Sensor (MRMS) system. Our results demonstrated the efficacy of our machine learning approaches for enriching the Twitter stream, to derive information potentially useful for validation of earth science satellite data.

Albayrak, Arif↗
NASA NTRS2015

Demonstrating Autonomous Mission Operations Onboard the International Space Station

The NASA Autonomous Mission Operations (AMO) project conducted an experiment to turn over operation and management of selected International Space Station (ISS) sys- tems to the on-board crew. ISS crews managed two different spacecraft systems: the Total Organic Carbon Analyzer (TOCA), a water quality analyzer, and Station Support Com- puters (SSC) laptops, which are non-critical crew computer systems. These systems were selected because they are representative of systems a future crew may need to operate au- tonomously during a deep space mission. The crew autonomously operated these systems, taking on mission operations functions traditionally performed by support teams on the ground, using new software tools that provide decision support algorithms for planning, monitoring and fault management, hardware schematics, system briefs, and data displays that are normally unavailable to the crew. The experiment lasted seven months, during which ISS crews managed TOCA and SSCs on 22 occasions. The AMO software processed data from TOCA and SSCs continuously during this seven month period. The combined performance of the software and crew achieved a 88 success rate on managing TOCA activity, the system for which ground-truth was available.

Autonomous Mission Operations↗
NASA NTRS2017

Planetary Crater Detection and Registration Using Marked Point Processes, Graph Cut Algorithms, and Wavelet Transforms

This paper addresses the problem of semi-automatic image registration on planetary images. A joint feature-based and area-based approach is proposed. Firstly, the most relevant craters are extracted from the two images to register, and then, registration is performed in two steps. The first step matches the craters extracted from the images based on a generalized Hausdorff distance. In the second step, the mutual information between the two images is maximized to achieve high registration accuracy. Craters are detected by a stochastic-geometry approach based on a marked point process model and of a multiple-birth-and-cut energy minimization algorithm. The experimental validation is carried out with 13 images for the crater extraction stage, and with 20 semi-synthetic pairs of images with ground truth and several images extracted from actual multi-temporal lunar scenes for the registration phase.

Image Processing; Pattern Recognition↗
NASA NTRS2014

Planetary Rover Localization Within Orbital Maps

This paper introduces an advanced rover localization system suitable for autonomous planetary exploration in the absence of Global Positioning System (GPS) infrastructure. Given an existing terrain map (image and elevation) obtained from satellite imagery and the images provided by the rover stereo camera system, the proposed method determines the best rover location through visual odometry, 3D terrain and hori- zon matching. The system is tested on data retrieved from a 3 km traverse of the Basalt Hills quarry in California where the GPS track is used as ground truth. Experimental results show the system presented here reduces by over 60 the localization error obtained by wheel odometry.

localization↗
NASA NTRS2019

The CAESAR New Frontiers Mission: 1. Expected Nature of the Returned Comet Sample

Comets are time capsules from the birth of our Solar System that record pre-solar history, the initial stages of planet formation, and the sources of prebiotic organics and volatiles for the origin of life. These capsules can only be opened in laboratories on Earth. CAESAR (Comet Astrobiology Exploration Sample Return)’s sample analysis objectives are to understand the nature of Solar System starting materials and how these components came together to form planets and give rise to life. Examination of these comet nucleus surface samples in laboratories around the world will also provide ground truth to remote observations of the innumerable icy bodies of the Solar System.

Lauretta, D. S.↗
NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗
NASA NTRS2018

The Apollo Sample Suite: 50 Years of Solar System Insight

The Apollo program was undoubtable a crowning achievement in human history. In addition to the obvious cultural significance, scientific results from the Apollo program had a lasting impression on a range of scientific fields, none more so that the effect the samples had on the fields of geology and cosmochemistry. The six Apollo missions collected 382 kg of rock, regolith, and core samples from geologically diverse locations on the Moon. In the nearly 50 years since the first samples were returned, there have been over 3000 different requests for samples, each yielding insights into fields as disparate as biology, medicine, astronomy, engineering, material science, and of course geology. Early studies of the Apollo samples revealed primary insights into the origin and evolution of the Moon, and of the Earth-Moon system, but the results also had implications for bodies throughout the solar system, e.g., defining crater counting rates. Over the decades, continued study of the Apollo samples by new generations of scientists using new instruments have continued to yield significant new discoveries, including the presence of endogenous water in the Moon and the possible presence of a lunar cataclysm, that in turn has contributed to new models of solar system formation and evolution. The Apollo samples have often been used as a proxy for studying other bodies like Mercury or asteroids. The Apollo samples have also directly contributed to the interpretation of remotely sensed data sets, including their use as ground truth for both Clementine and Lunar Prospector global geochemical maps. Despite the Apollo samples being a static collection, recent efforts will ensure that investigators continue to have access to new samples. For example, there was a recent solicitation for study of previously unopened Apollo samples in vacuum-sealed containers, as well as new access to samples stored frozen or in a He atmosphere. Similarly, the use of X-ray computed tomography as part of the curation process is identifying new clasts within polymict breccias that are available for study. Finally, the MoonDB project is putting all previously published lunar geochemical analyses into a searchable database, which should facilitate new investigations.

Zeigler, Ryan↗
NASA NTRS2017

Vegetation Classification of Coffea on Hawaii Island using Worldview-2 Satellite Imagery

Coffee is an important crop in tropical regions of the world; about 125 million people depend on coffee agriculture for their livelihoods. Understanding the spatial extent of coffee fields is useful for management and control of coffee pests such as Hypothenemus hampei and other pests that use coffee fruit as a host for immature stages such as the Mediterranean fruit fly, for economic planning, and for following changes in coffee agroecosystems over time. We present two methods for detecting Coffea arabica fields using remote sensing and geospatial technologies on WorldView-2 high-resolution spectral data of the Kona region of Hawaii Island. The first method, a pixel-based method using a maximum likelihood algorithm, attained 72% producer accuracy and 69% user accuracy (68% overall accuracy) based on analysis of 104 ground truth testing polygons. The second method, an object-based image analysis (OBIA) method, considered both spectral and textural information and improved accuracy, resulting in 76% producer accuracy and 94% user accuracy (81% overall accuracy) for the same testing areas. We conclude that the OBIA method is useful for detecting coffee fields grown in the open and use it to estimate the distribution of about 1050 hectares under coffee agriculture in the Kona region in 2012.

Gaertner, Julie↗