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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 163 records · Page 9

Assessing Alaskan boreal forest landcover affected by climate-wildfire interactions from ground truth surveys and NASA airborne remote sensing

Alaska’s boreal forest is facing unprecedented challenges under rapid climate warming (increasingly severe fires, droughts, pest/disease outbreaks) that may destabilize its function as a global carbon sink. Forests near Fairbanks may be especially vulnerable, impacting air quality and ecosystem services. We combined GT (ground truthing) with Airborne Visible InfraRed Imaging Spectrometer (AVIRIS-NG) images collected by the NASA Arctic-Boreal Vulnerability Experiment (ABoVE) program (2017-2019) to assess landcover change at five recently burned sites (2001-2019) of different fire severities and moisture regimes within 30 miles of Fairbanks. GT included tree seedling counts, understory % cover and >50% leaf canopy color assessment. 36 circular plots (1/30 ha radius) including 6 moderate to severely burned plots were selected across sites. 31 additional sites including 12 burned sites were geotagged in photos. AVIRIS images were processed from 29 spectral bands selected to identify changes in chlorophyll and water content. Images were segmented into natural boundaries (polygons) using ENVI 5.5 software. A spectral library of 8 AVIRIS bands with high between-class/low within-class variation was used in two random forest models to predict vegetation classes (model 1: 12 classes, model 2: 14 classes) in each AVIRIS scene, using 20% of the data as training data. Model 2 classified 20% more polygons overall, but only 42% of GT/geotagged polygons were correctly classified by both models. More forest sites were correctly classified (63%) than open vegetation (32%) or post-fire sites (46%). 50% of aspen forest and post-fire polygons were misclassified as shrubland. GT revealed that post-fire plots supported 134,000 (± 48,000) tree seedlings and saplings ha-1 (0.2 - 4 m height, 64% deciduous) versus 2500 (± 2100) shrubs ha-1 (1-6 m height). > 50% canopy browning was observed in conifer forest (8 plots) with no signs of insect infestation. Canopy herbivory > 50% (leaf miner, leaf beetle) and moose herbivory of tree bark was seen across aspen sites. Our study suggests: 1) low canopy vegetation presents challenges for improved landcover classification, and 2) aspen forest should be differentiated in vegetation maps which would aid in tracking herbivory.

Alaska↗

Dissipating Step Bunches during Crystallization under Transport Control

In studies of crystal formation by the generation and spreading of layers, equidistant step trains are considered unstable---bunches and other spatiotemporal patterns of the growth steps are viewed as ubiquitous. We provide an example to the opposite. We monitor the spatiotemporal dynamics of steps and the resulting step patterns during crystallization of the proteins ferritin and apoferritin using the atomic force microscope. The variations in step velocity and density are not correlated, indicating the lack of a long-range attraction between the steps. We show that (i) because of its coupling to bulk transport, nucleation of new layers is chaotic and occurs at the facet edges, where the interfacial supersaturation is higher; (ii) step bunches self-organize via the competition for supply from the solution; and, (iii) bunches of weakly interacting steps decay as they move along the face. Tests by numerical modeling support the conclusions about the mechanisms underlying our observations. The results from these systems suggest that during crystallization controlled by transport, with weakly or noninteracting growth steps, the stable kinetic state of the surface is an equidistant step train, and step bunches only arise during nucleation of new layers. Since nucleation only occurs at a few sites on the surface, the surface morphology may be controllably patterned or smoothened by locally controlling nucleation.

Lin, Hong↗

Space-Borne Cloud-Native Satellite-Derived Bathymetry (SDB) Models Using ICESat-2 And Sentinel-2

Shallow nearshore coastal waters provide a wealth of societal, economic and ecosystem services, yet their topographic structure is poorly mapped due to a reliance upon expensive and time intensive methods. Space‐borne bathymetric mapping has helped address these issues, but has remained largely dependent upon in situ measurements. Here we fuse ICESat‐2 lidar data with Sentinel‐2 optical imagery, within the Google Earth Engine cloud platform, to create openly available spatially continuous high‐resolution bathymetric maps at regional‐to‐national scales in Florida, Crete and Bermuda. ICESat‐2 bathymetric classified photons are used to train three Satellite Derived Bathymetry (SDB) methods, including Lyzenga, Stumpf and Support Vector Regression algorithms. For each study site the Lyzenga algorithm yielded the lowest RMSE (approx. 10‐15%) when compared with validation data. We demonstrate a means of using ICESat‐2 for both model calibration and validation, thus cementing a pathway for fully space‐borne estimates of nearshore bathymetry in shallow, clear water environments.

N. Thomas↗

Advancing Methodologies for Applying Machine Learning and Evaluating Spatiotemporal Models of Fine Particulate Matter (PM 2.5 ) Using Satellite Data Over Large Regions

Reconstructing the distribution of fine particulate matter (PM 2.5 ) in space and time, even far from ground monitoring sites, is an important exposure science contribution to epidemiologic analyses of PM 2.5 health impacts. Flexible statistical methods for prediction have demonstrated the integration of satellite observations with other predictors, yet these algorithms are susceptible to overfitting the spatiotemporal structure of the training datasets. We present a new approach for predicting PM 2.5 using machine-learning methods and evaluating prediction models for the goal of making predictions where they were not previously available. We apply extreme gradient boosting (XGBoost) modeling to predict daily PM 2.5 on a 1 x 1 km 2 resolution for a 13 state region in the Northeastern USA for the years 2000–2015 using satellite-derived aerosol optical depth and implement a recursive feature selection to develop a parsimonious model. We demonstrate excellent predictions of withheld observations but also contrast an RMSE of 3.11 μg/m 3 in our spatial cross-validation withholding nearby sites versus an overfit RMSE of 2.10 μg/m 3 using a more conventional random ten-fold splitting of the dataset. As the field of exposure science moves forward with the use of advanced machine-learning approaches for spatiotemporal modeling of air pollutants, our results show the importance of addressing data leakage in training, overfitting to spatiotemporal structure, and the impact of the predominance of ground monitoring sites in dense urban sub-networks on model evaluation. The strengths of our resultant modeling approach for exposure in epidemiologic studies of PM 2.5 include improved efficiency, parsimony, and interpretability with robust validation while still accommodating complex spatiotemporal relationships.

air pollution↗

Teaching/learning principles

The potential remote sensing user community is enormous, and the teaching and training tasks are even larger; however, some underlying principles may be synthesized and applied at all levels from elementary school children to sophisticated and knowledgeable adults. The basic rules applying to each of the six major elements of any training course and the underlying principle involved in each rule are summarized. The six identified major elements are: (1) field sites for problems and practice; (2) lectures and inside study; (3) learning materials and resources (the kit); (4) the field experience; (5) laboratory sessions; and (6) testing and evaluation.

Hankins, D. B.↗

A Comprehensive and Cost-Effective Computer Infrastructure for K-12 Schools

Since 1993, NASA Langley Research Center has been developing and implementing a low-cost Internet connection model, including system architecture, training, and support, to provide Internet access for an entire network of computers. This infrastructure allows local area networks which exceed 50 machines per school to independently access the complete functionality of the Internet by connecting to a central site, using state-of-the-art commercial modem technology, through a single standard telephone line. By locating high-cost resources at this central site and sharing these resources and their costs among the school districts throughout a region, a practical, efficient, and affordable infrastructure for providing scale-able Internet connectivity has been developed. As the demand for faster Internet access grows, the model has a simple expansion path that eliminates the need to replace major system components and re-train personnel. Observations of optical Internet usage within an environment, particularly school classrooms, have shown that after an initial period of 'surfing,' the Internet traffic becomes repetitive. By automatically storing requested Internet information on a high-capacity networked disk drive at the local site (network based disk caching), then updating this information only when it changes, well over 80 percent of the Internet traffic that leaves a location can be eliminated by retrieving the information from the local disk cache.

Warren, G. P.↗

Variables in automatic classification over extended remote sensing test sites.

Four major causes of variation in response of multispectral scanner data were examined utilizing data from two large test sites. In one case, data throughout a 70-mile flightline was automatically classified with a high degree of accuracy (98%), utilizing training samples from a single small segment of the data. In the second case, spectral data for wheat and other cover types were calibrated and utilized to train the computer, resulting in data up to 90 miles away being classified with an acceptable degree of accuracy (91%), although significant changes in solar illumination and ground cover conditions existed.

Hoffer, R. M.↗

Automated thematic mapping and change detection of ERTS-A images

There are no author-identified significant results in this report. This investigation is concerned with the development of automated interpretation techniques for the recognition and identification of earth resources. The resources will be identified by using both multispectral and spatial signatures. Ground truth data and aircraft underflight photography will be used to train the recognition algorithms. The data processed will be RBV and MSS images acquired by ERTS-1 satellite, over six test sites located in the vicinities of: Phoenix, Arizona; Weslaco, Texas; Cascade Mountains, Washington; New Orleans, Louisiana; Salt Lake City, Utah; and Salton Sea, California. The processed data will be thematic maps of resources consisting of annotated and outlined images. The seasonal changes of hydrologic and agricultural resources will also be identified. The results are expected to be applicable to a future automatic system of resource inventory and management.

Gramenopoulos, N.↗

Operational support considerations in Space Shuttle prelaunch processing

This paper presents an overview of operational support for Space Shuttle payload processing at the John F. Kennedy Space Center. The paper begins with a discussion of the Shuttle payload processing operation itself. It discusses the major organizational roles and describes the two major classes of payload operations: Spacelab mission payload and vertically-installed payload operations. The paper continues by describing the Launch Site Support Team and the Payload Processing Test Team. Specific areas of operational support are then identified including security and access, training, transport and handling, documentation and scheduling. Specific references for further investigatgion are included.

Schuiling, Roelof L.↗

Challenger Anniversary Resource Tape

This commemorative video marks the tenth anniversary, January 28, 1986, of the ninth Challenger flight and the seven astronauts onboard who died when the Challenger exploded 73 seconds into flight. The flight crew was comprised of Cmdr. Francis R. Scobee, Pilot Michael J. Smith, and Mission Specialists Judith A. Resnik, Ellison S. Onizuka, Ronald E. McNair, Gregory Jarvis (Hughes Aircraft representative), and S. Christie McAuliffe (teacher). The flight crew is shown performing preflight training, physiological tests, environmental tests, press conferences, prelaunch activities, and launch activities. The Challenger explosion is shown from both the launch site and from the control center. Various rescue operations, news coverage, and shots of the wreckage after salvage are also presented. President Ronald Reagan is shown giving a tribute at the memorial service for the flight crew. The video ends with a flyby salute and pictures of each of the members of the Challenger.

Source record↗

Rapid motor learning in the translational vestibulo-ocular reflex

Motor learning was induced in the translational vestibulo-ocular reflex (TVOR) when monkeys were repeatedly subjected to a brief (0.5 sec) head translation while they tried to maintain binocular fixation on a visual target for juice rewards. If the target was world-fixed, the initial eye speed of the TVOR gradually increased; if the target was head-fixed, the initial eye speed of the TVOR gradually decreased. The rate of learning acquisition was very rapid, with a time constant of approximately 100 trials, which was equivalent to <1 min of accumulated stimulation. These learned changes were consolidated over >or=1 d without any reinforcement, indicating induction of long-term synaptic plasticity. Although the learning generalized to targets with different viewing distances and to head translations with different accelerations, it was highly specific for the particular combination of head motion and evoked eye movement associated with the training. For example, it was specific to the modality of the stimulus (translation vs rotation) and the direction of the evoked eye movement in the training. Furthermore, when one eye was aligned with the heading direction so that it remained motionless during training, learning was not expressed in this eye, but only in the other nonaligned eye. These specificities show that the learning sites are neither in the sensory nor the motor limb of the reflex but in the sensory-motor transformation stage of the reflex. The dependence of the learning on both head motion and evoked eye movement suggests that Hebbian learning may be one of the underlying cellular mechanisms.

Non-NASA Center↗

Pre-Launch Mission Operation Report: San Marco B

On or about April 23, 1967, the Italian Space Commission of the National Council of Research (I.S.C.) will launch the San Marco B satellite from the I.S.C. launch range located off the coast of Kenya, Africa. It is planned that the spacecraft will be placed into an equatorial orbit by the four-stage Scout vehicle, number S-153. The San Marco program is a joint NASA-I.S.C. effort being carried out in accordance with a Memorandum of Understanding dated 31 May 1962. Under this agreement the I .S.C. has established the equatorial launch site, has designed and fabricated the satellite, and will conduct the launch operation. The NASA has provided the Scout launch vehicle, training for I.S.C. personnel, technical consultation,and tracking and data acquisition for the operational satellite.

Source record↗

Port-O-Sim Object Simulation Application

Port-O-Sim is a software application that supports engineering modeling and simulation of launch-range systems and subsystems, as well as the vehicles that operate on them. It is flexible, distributed, object-oriented, and realtime. A scripting language is used to configure an array of simulation objects and link them together. The script is contained in a text file, but executed and controlled using a graphical user interface. A set of modules is defined, each with input variables, output variables, and settings. These engineering models can be either linked to each other or run as standalone. The settings can be modified during execution. Since 2001, this application has been used for pre-mission failure mode training for many Range Safety Scenarios. It contains range asset link analysis, develops look-angle data, supports sky-screen site selection, drives GPS (Global Positioning System) and IMU (Inertial Measurement Unit) simulators, and can support conceptual design efforts for multiple flight programs with its capacity for rapid six-degrees-of-freedom model development. Due to the assembly of various object types into one application, the application is applicable across a wide variety of launch range problem domains.

Lanzi, Raymond J.↗

NEEMO 20: Science Training, Operations, and Tool Development

The 20th mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated evaluation of operational protocols and tools designed to enable future exploration beyond low-Earth orbit. NEEMO 20 was conducted from the Aquarius habitat off the coast of Key Largo, FL in July 2015. The habitat and its surroundings provide a convincing analog for space exploration. A crew of six (comprised of astronauts, engineers, and habitat technicians) lived and worked in and around the unique underwater laboratory over a mission duration of 14-days. Incorporated into NEEMO 20 was a diverse Science Team (ST) comprised of geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center (JSC), as well as marine scientists from the Department of Biological Sciences at Florida International University (FIU). This team trained the crew on the science to be conducted, defined sampling techniques and operational procedures, and planned and coordinated the science focused Extra Vehicular Activities (EVAs). The primary science objectives of NEEMO 20 was to study planetary sampling techniques and tools in partial gravity environments under realistic mission communication time delays and operational pressures. To facilitate these objectives two types of science sites were employed 1) geoscience sites with available rocks and regolith for testing sampling procedures and tools and, 2) marine science sites dedicated to specific research focused on assessing the photosynthetic capability of corals and their genetic connectivity between deep and shallow reefs. These marine sites and associated research objectives included deployment of handheld instrumentation, context descriptions, imaging, and sampling; thus acted as a suitable proxy for planetary surface exploration activities. This abstract briefly summarizes the scientific training, scientific operations, and tool development conducted during NEEMO 20 with an emphasis on the primary lessons learned.

Graff, T.↗

Automated thematic mapping and change detection of ERTS-A images

The author has identified the following significant results. This investigation is concerned with the development of automated interpretation techniques for the recognition and identification of earth resources. The resources will be identified by using both multispectral and spatial signatures. Ground truth data and aircraft underflight photography will be used to train the recognition algorithms. The data processed will be RBV and MSS images acquired by the ERTS-1 satellite, over six tests sites located in the vicinities of: Phoenix, Arizona; Weslaco, Texas; Cascade Mountains, Washington; New Orleans, Louisiana; Salt Lake, Utah; and Salton Sea, California. The processed data will be thematic maps of resources consisting of annotated and outlined images. The seasonal changes of hydrologic and agricultural resources will also be identified. The results are expected to be applicable to a future automatic system of resource inventory and management.

Gramenopoulos, N.↗

A multidisciplinary study of earth resources imagery of Australia, Antarctica and Papua, New Guinea

The author has identified the following significant results. A thirteen category recognition map was prepared, showing forest, water, grassland, and exposed rock types. Preliminary assessment of classification accuracies showed that water, forest, meadow, and Niobrara shale were the most accurately mapped classes. Unsatisfactory results, were obtained in an attempt to discrimate sparse forest cover over different substrates. As base elevation varied from 7,000 to 13,000 ft, with an atmospheric visibility of 48 km, no changes in water and forest recognition were observed. Granodiorite recognition accuracy decreased monotonically as base elevation increased, even though the training set location was at 10,000 ft elevation. For snow varying in base elevation from 9400 to 8420 ft, recognition decreases from 99% at the 9400 ft training set elevation to 88% at 8420 ft. Calculations of expected radiance at the ERTS sensor from snow reflectance measured at the site and from Turner model calculations of irradiance, transmission and path radiance, reveal that snow signals should not be clipped, assuming that calculations and ERTS calibration constants were correct.

Fisher, N. H.↗

Development of a Portable, Ground-based Ozone Lidar Instrument for Tropospheric Ozone Research and Educational Training

The objective of this research project is to develop a portable, eye-safe, ground-based ozone lidar instrument specialized for ozone differential absorption lidar (DIAL) measurements in the troposphere. This research project directly supports the goal of NASA's Earth Science Enterprise to understand the distribution and budget of tropospheric ozone (objective 1.5 of the Earth Science Strategic Enterprise Plan, 1998-2002). It can participate in ground validation experiments for TES, a tropospheric ozone satellite mission due to be launched in 2002. It can also be utilized for correlative ground measurements in future GTE (Global Tropospheric Experiment) and space-based ozone lidar missions, such as ORACLE. Multiple ground-based ozone lidar systems would improve the data obtained through current ozone-sonde networks. This prototype instrument could to serve as the basic unit for these and other future monitoring projects requiring multi-instrument networks, such as that proposed for the Global Tropospheric Ozone Project (GTOP). GTOP is currently being formulated by a scientific panel of the International Global Atmospheric Chemistry Project to meet its goal to better understand the processes that control the global distribution of tropospheric ozone. In order for the lidar to be widely deployed in networks, it must be fairly easy to use and maintain as well as being cost-competitive with a ground station launching ozonesondes several times a day. A second 2-year grant to continue this effort with students participating in ground tests and system improvements has been awarded by the Office of Equal Employment Opportunities (OEOP). This project also supports existing NASA lidar missions through its development of advanced, compact lidar technology. Innovations in both transmitters and receivers have been made in this project. Finally, this system could be modified in the future to probe more deeply into the stratosphere. This could be accomplished by increasing the emitted energy or optimizing the wavelengths for this purpose. In addition to NASA, this system has applications to the EPA, NOAA, and the DOD. An AFOSR grant has been awarded based on the results of this effort to fund advanced transmitter development at medium (20-40 mJ) energies. A second proposal to the DOD with a letter of support from Air Force Research Laboratory, has been submitted to extend this uv laser technology to 100 mJ levels. Thus, this project has enabled students and faculty at Hampton University to begin to develop research efforts in support of the mission of the DOD. This instrument will be based at Hampton University (HU) to meet our educational goal to train students in lidar technology as well as atmospheric ozone data analysis and interpretation. It will be also available for off-site measurement campaigns and will serve as a test bed for further instrument development. Later development beyond this grant to extend the scientific usefulness of the instrument may include incorporation of an aerosol channel and upgrading the laser to make stratospheric ozone measurements. Seven undergraduates, three graduate students, and one postdoctoral. researcher (formerly an HU student) have been active participants in this research effort.

Chyba, Thomas↗

NASA Medical Response to Human Spacecraft Accidents

Manned space flight is risky business. Accidents have occurred and may occur in the future. NASA's manned space flight programs, with all their successes, have had three fatal accidents, one at the launch pad and two in flight. The Apollo fire and the Challenger and Columbia accidents resulted in a loss of seventeen crewmembers. Russia's manned space flight programs have had three fatal accidents, one ground-based and two in flight. These accidents resulted in the loss of five crewmembers. Additionally, manned spacecraft have encountered numerous close calls with potential for disaster. The NASA Johnson Space Center Flight Safety Office has documented more than 70 spacecraft incidents, many of which could have become serious accidents. At the Johnson Space Center (JSC), medical contingency personnel are assigned to a Mishap Investigation Team. The team deploys to the accident site to gather and preserve evidence for the Accident Investigation Board. The JSC Medical Operations Branch has developed a flight surgeon accident response training class to capture the lessons learned from the Columbia accident. This presentation will address the NASA Mishap Investigation Team's medical objectives, planned response, and potential issues that could arise subsequent to a manned spacecraft accident. Educational Objectives are to understand the medical objectives and issues confronting the Mishap Investigation Team medical personnel subsequent to a human space flight accident.

Patlach, Robert↗