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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
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Framework for Land Cover Classification Using Discrete Return LiDAR Data: Adopting Pseudo-Waveform and Hierarchical Segmentation

Acquiring current, accurate land-use information is critical for monitoring and understanding the impact of anthropogenic activities on natural environments.Remote sensing technologies are of increasing importance because of their capability to acquire information for large areas in a timely manner, enabling decision makers to be more effective in complex environments. Although optical imagery has demonstrated to be successful for land cover classification, active sensors, such as light detection and ranging (LiDAR), have distinct capabilities that can be exploited to improve classification results. However, utilization of LiDAR data for land cover classification has not been fully exploited. Moreover, spatial-spectral classification has recently gained significant attention since classification accuracy can be improved by extracting additional information from the neighboring pixels. Although spatial information has been widely used for spectral data, less attention has been given to LiDARdata. In this work, a new framework for land cover classification using discrete return LiDAR data is proposed. Pseudo-waveforms are generated from the LiDAR data and processed by hierarchical segmentation. Spatial featuresare extracted in a region-based way using a new unsupervised strategy for multiple pruning of the segmentation hierarchy. The proposed framework is validated experimentally on a real dataset acquired in an urban area. Better classification results are exhibited by the proposed framework compared to the cases in which basic LiDAR products such as digital surface model and intensity image are used. Moreover, the proposed region-based feature extraction strategy results in improved classification accuracies in comparison with a more traditional window-based approach.

Light Detection & Ranging (LIDAR)↗
NASA NTRS2018

Data Assimilation of Terrestrial Water Storage to Adjust Precipitation Fluxes

The Gravity Recovery and Climate Experiment (GRACE) mission has provided unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. TWS is defined as the sum of groundwater, soil moisture, snow, surface water, ice and biomass water. Data assimilation of GRACE TWS observations has been shown to improve simulation of groundwater, streamflow, and snow water equivalent, and has also proven useful for drought monitoring and identifying human impacts on the water cycle. From a modeling perspective, the TWS components are defined as "prognostic hydrological states". Existing GRACE data assimilation schemes update these prognostic states directly. In this work, we propose an alternate approach in which precipitation fluxes are adjusted in order to achieve the desired change in the hydrological prognostic states. Limitations of such an approach include the assumption that all errors in TWS originate from errors in precipitation. Nonetheless, benefits comprise (1) the water balance is maintained, as opposed to having to add increments to the water budget components, (2) the model automatically determines how to distribute the updates among the TWS prognostic states, and (3) it is not necessary to know the exact time of the observation TWS, because the TWS change timing is determined by the precipitation forcing.

Girotto, Manuela↗
NASA NTRSDate not supplied

Observing Supraglacial Lakes Using Deep Learning and PlanetScope Imagery

Supraglacial lakes (SGL)s result from melt water accumulation in topographic depressions on the surface of glaciers. SGLs primarily affect glacial dynamics through a positive feedback loop in which the albedo-lowering effect of SGLs can escalate surface melt leading to increases in lake extent and depth, amplifying the afore mentioned albedo-lowering effect. The implications of accelerated glacial melt include increased sea level rise and modifications to ocean primary productivity. SGLs are critical indicators of surface melt and its downstream impacts and should be monitored efficiently. In situ observations and measurements of SGLs are time consuming, cost-prohibitive and difficult to scale. Earth observation data and machine learning enable scalable monitoring of SGLs through pattern detection and quantification of lake evolution over time [1]. This work presents a model developed by training a convolutional neural network with imagery and labels from NASA Operation IceBridge and predicting SGLs in high temporal and spatial resolution PlanetScope imagery.

Supraglacial lake↗
NASA NTRS2011

Probabilistic Structural Health Monitoring of the Orbiter Wing Leading Edge

A structural health monitoring (SHM) system can contribute to the risk management of a structure operating under hazardous conditions. An example is the Wing Leading Edge Impact Detection System (WLEIDS) that monitors the debris hazards to the Space Shuttle Orbiter s Reinforced Carbon-Carbon (RCC) panels. Since Return-to-Flight (RTF) after the Columbia accident, WLEIDS was developed and subsequently deployed on board the Orbiter to detect ascent and on-orbit debris impacts, so as to support the assessment of wing leading edge structural integrity prior to Orbiter re-entry. As SHM is inherently an inverse problem, the analyses involved, including those performed for WLEIDS, tend to be associated with significant uncertainty. The use of probabilistic approaches to handle the uncertainty has resulted in the successful implementation of many development and application milestones.

Yap, Keng C.↗
NASA NTRS2000

Health Monitoring System Technology Assessments: Cost Benefits Analysis

The subject of sensor-based structural health monitoring is very diverse and encompasses a wide range of activities including initiatives and innovations involving the development of advanced sensor, signal processing, data analysis, and actuation and control technologies. In addition, it embraces the consideration of the availability of low-cost, high-quality contributing technologies, computational utilities, and hardware and software resources that enable the operational realization of robust health monitoring technologies. This report presents a detailed analysis of the cost benefit and other logistics and operational considerations associated with the implementation and utilization of sensor-based technologies for use in aerospace structure health monitoring. The scope of this volume is to assess the economic impact, from an end-user perspective, implementation health monitoring technologies on three structures. It specifically focuses on evaluating the impact on maintaining and supporting these structures with and without health monitoring capability.

Kent, Renee M.↗
NASA NTRS1993

Proposal for a Universal Particle Detector Experiment

The Universal Particle Detector Experiment (UPDE), which consists of parallel planes of two diode laser beams of different wavelengths and a large surface metal oxide semiconductor (MOS) impact detector, is proposed. It will be used to perform real-time monitoring of contamination particles and meteoroids impacting the spacecraft surface with high resolution of time, position, direction, and velocity. The UPDE will discriminate between contaminants and meteoroids, and will determine their velocity and size distribution around the spacecraft environment. With two different color diode lasers, the contaminant and meteroid composition will also be determined based on laboratory calibration with different materials. Secondary particles dislodged from the top aluminum surface of the MOS detector will also be measured to determine the kinetic energy losses during energetic meteoroid impacts. The velocity range of this instrument is 0.1 m/s to more than 14 km/s, while its size sensitivity is from 0.2 microns to millimeter-sized particles. The particulate measurements in space of the kind proposed will be the first simultaneous multipurpose particulate experiment that includes velocities from very slow to hypervelocities, sizes from submicrometer- to pellet-sized diameters, chemical analysis of the particulate composition, and measurements of the kinetic energy losses after energetic impacts of meteroids. The experiment will provide contamination particles and orbital debris data that are critically needed for our present understanding of the space environment. The data will also be used to validate contamination and orbital debris models for predicting optimal configuration of future space sensors and for understanding their effects on sensitive surfaces such as mirrors, lenses, paints, and thermal blankets.

Lesho, J. C.↗
NASA NTRS2010

Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge

This viewgraph presentation reviews Structural Health Monitoring Analysis for the Orbiter Wing Leading Edge. The Wing Leading Edge Impact Detection System (WLE IDS) and the Impact Analysis Process are also described to monitor WLE debris threats. The contents include: 1) Risk Management via SHM; 2) Hardware Overview; 3) Instrumentation; 4) Sensor Configuration; 5) Debris Hazard Monitoring; 6) Ascent Response Summary; 7) Response Signal; 8) Distribution of Flight Indications; 9) Probabilistic Risk Analysis (PRA); 10) Model Correlation; 11) Impact Tests; 12) Wing Leading Edge Modeling; 13) Ascent Debris PRA Results; and 14) MM/OD PRA Results.

Yap, Keng C.↗
NASA NTRS2020

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↗
NASA NTRS2016

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

climate change↗
NASA NTRS1971

Assessment of the Impact of the California Water Project in the West Side of the San Joaquin Valley

The ability of remote sensing techniques to effectively monitor, on a continuing basis, the impact of a change in the water supply of an arid area is considered. Research involves the collection of a substantial body of information relative to both physical and biological phenomena or systems operative within the study area by concentrating on the accumulation of library materials, and field data.

Estes, J. E.↗
NASA NTRS1974

The economic impact of remote sensing data as the source of nonpoint pollution monitoring and control

Nonpoint pollution of streams with sediment as a result of runoff from alternative uses of land has become a socially unacceptable product of economic activity. This report describes a research approach to economically achieve correction of the nonpoint pollution problem. The research approach integrates the economic model with those data which may be obtainable from remotely sensed sources. The economic problem involves measurement of the direct benefits and costs associated with the changes in land management activities necessary to reduce the level of nonpoint pollution. Remotely sensed data from ERTS-1 may provide some of the information required for the economic model which indicates efficient solutions to the nonpoint pollution problem. Three classes of data (i.e., soil categories, vegetative cover, and water turbidity) have the potential to be measured by ERTS-1 systems. There is substantial research which indicates the ability of ERTS-1 to measure these classes of data under selected conditions.

Miller, W. L.↗
NASA NTRS1975

Environmental monitoring of North Merritt Island

The environmental impact of the space shuttle operation on North Merritt Island was studied mainly by means of color infrared photos and field visits. An attempt was also made to generate character maps of the Island using LANDSAT data with a view to decreasing the cost of monitoring and making the process more flexible in terms of rapid estimation of the extent of selected ground features. It seems possible that the IMAGE-100 output can be improved by using it in conjunction with software systems which are used for generating character maps. All the methods for generating maps show six main plant associations on North Merritt Island. It was shown that the six associations are related by ecological succession, merge into their neighbors in terms of component species and can be observed for changes in terms of component species.

Poonai, P.↗
NASA NTRS2001

TRMM: Status of Precipitation Estimates and Science Highlights

As a part of NASA's Earth System Enterprise, the Tropical Rainfall Measuring Mission (TRMM) seeks to understand the mechanisms through which changes in tropical rainfall influence global circulation. Over the past 3 years, TRMM has contributed significantly towards reducing uncertainty in satellite estimates of rainfall in the Tropics, where almost 67% of the Earth's rain falls. TRMM has provided knowledge related to the climatology, seasonality, and variation of tropical rainfall; the mesoscale structure of rain-producing systems; and the physics of precipitation. An overview of these results will be presented. Additionally, a summary of research highlights will be presented focusing on application of TRMM data to topics such as hurricane monitoring, climate analysis, forecasting, microphysics, environmental impacts, and El Nino/La Nina. Examples and plans for operational use of TRMM data in tropical cyclone monitoring and other applications will also be given.

Shepherd, J. Marshall↗
NASA NTRS1996

X-Ray Imaging Study

The space environment in which the Space Station Freedom and other space platforms will orbit is truly a hostile environment. For example, the currently estimated integral fluence for electrons above 1 Mev at 2000 nautical miles is above 2 x 1O(exp 10) electrons/sq cm/day and the proton integral fluence is above 1 x 10(exp 9) protons/sq cm/day. At the 200 - 400 nautical miles, which is more representative of the altitude which will provide the environment for the Space Station, each of these fluences will be proportionally less; however, the data indicates that the radiation environment will obviously have an effect on structural materials exposed to the environment for long durations. The effects of this combined environment is the issue which needs to be understood for the long term exposure of structures in space. At the same time, there will be substantial potential for collisions between the space platforms and space debris. The current NASA catalogue contains over 4500 objects floating in space which are not considered payloads. This debris can have significant effects on collision with orbiting spacecraft. In order to better understand the effect of these hostile phenomena on spacecraft, several types of studies are being performed to simulate at some level the effect of the environment. In particular the study of debris clouds produced by hypervelocity impact on the various surfaces anticipated on the Space Station is very important at this point in time. The need to assess the threat of such debris clouds on space structures is an on-going activity. The Space Debris Impact facility in Building 4612 provides a test facility to monitor the types of damage produced with hypervelocity impact. These facilities are used to simulate space environmental effects from energetic particles. Flash radiography or x-ray imaging has traditionally provided such information and as such has been an important tool for recording damage in situ with the event. The proper operation of the system can provide much useful information with respect to parametric analysis of the hypervelocity experiment. The following report outlines the procedures developed to optimize the operation of the x-ray imaging system and its operational characteristics.

OBrien, Susan K.↗
NASA NTRS2016

Unveiling Clues from Spacecraft Missions to Comets and Asteroids through Impact Experiments

The Deep Impact Spacecraft mission was the first to boldly face the challenge of impacting the surface of a comet, 9P/Tempel 1, to investigate surface and subsurface 'pristine' materials. The Stardust mission to Comet 81P/Wild 2 brought back an exciting surprise: shocked minerals which were likely altered during the comet's lifetime. Signatures of shock in meteorites also suggest that the violent past of the solar system has left our small bodies with signatures of impacts and collisions. These results have led to the question: How have impacts affected the evolutionary path taken by comets and asteroids, and what signatures can be observed? A future planetary mission to a near-Earth asteroid is proposing to take the next steps toward understanding small bodies through impacts. The mission would combine an ESA led AIM (Asteroid Impact Mission) with a JHU/APL led DART (Double Asteroid Redirect Mission) spacecraft to rendezvous with binary near-Earth asteroid 65803 Didymus (1996 G2). DART would impact the smaller asteroid, 'Didymoon' while AIM would characterize the impact and the larger Didymus asteroid. With these missions in mind, a suite of experiments have been conducted at the Experimental Impact Laboratory (EIL) at NASA Johnson Space Center to investigate the effects that collisions may have on comets and asteroids. With the new capability of the vertical gun to cool targets in the chamber through the use of a cold jacket fed by liquid nitrogen, the effects of target temperature have been the focus of recent studies. Mg-rich forsterite and enstatite (orthopyroxene), diopside (monoclinic pyroxene) and magnesite (Mg-rich carbonate) were impacted. Target temperatures ranged from 25 deg to -100 deg, monitored by connecting thermocouples to the target container. Impacted targets were analyzed with a Fourier Transform Infrared Spectrometer (FTIR) and Transmission Electron Microscope (TEM). Here we present the evidence for impact-induced shock in the minerals through both spectra and TEM imaging and compare with unshocked samples.

Lederer, Susan M.↗
NASA NTRS1977

Remote sensing of environmental impact of land use activities

The capability to monitor land cover, associated in the past with aerial film cameras and radar systems, was discussed in regard to aircraft and spacecraft multispectral scanning sensors. A proposed thematic mapper with greater spectral and spatial resolutions for the fourth LANDSAT is expected to usher in new environmental monitoring capability. In addition, continuing improvements in image classification by supervised and unsupervised computer techniques are being operationally verified for discriminating environmental impacts of human activities on the land. The benefits of employing remote sensing for this discrimination was shown to far outweigh the incremental costs of converting to an aircraft-satellite multistage system.

Paul, C. K.↗