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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

EXPLICIT PHYSICS ALGORITHMS↗
DOE OSTI2022

Skyfall: Signal Fusion from a Smartphone Falling from the Stratosphere

A smartphone plummeted from a stratospheric height of 36 km, providing a near-real-time record of its rapid descent and ground impact. An app recorded and streamed useful internal multi-sensor data at high sample rates. Signal fusion with external and internal sensor systems permitted a more detailed reconstruction of the Skyfall chronology, including its descent speed, rotation rate, and impact deceleration. Our results reinforce the potential of smartphones as an agile and versatile geophysical data collection system for environmental and disaster monitoring IoT applications. We discuss mobile environmental sensing capabilities and present a flexible data model to record and stream signals of interest. The Skyfall case study can be used as a guide to smartphone signal processing methods that are transportable to other hardware platforms and operating systems.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

Bhutan Water Resources II: Comparing Phenology, Precipitation, and Temperature Data in Bhutan to Assist the Himalayan Environmental Rhythm Observation and Evaluation System (HEROES) Project

Bhutan is vulnerable to climate fluctuations that can affect vegetation phenology patterns. Changes in the climate have raised concerns from local farmers about altered growing seasons. In response, the DEVELOP team assessed annual vegetation phenology trends across Bhutan from 1981-2014 by comparing vegetation phenology-derived data and meteorological data. The project assessed phenology change using Vegetation Index and Phenology (VIP) Normalized Difference Vegetation Index (NDVI) products from the Advanced Very High-Resolution Radiometer (AVHRR) and the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. We also used Climate Hazards Center Infrared Precipitation with Station (CHIRPS) precipitation data and Famine Early Warning System Network Land Data Assimilation System (FLDAS) temperature data to assess climate trends in the country. The team assessed VIP phenology data for 1981-2014 to assess trends for the start of season, day of peak, and length of season. For the main growing season, the results indicated that the start of season and day of peak were delayed, while the length of season increased by 22 days. Analysis of temperature and precipitation data for the early 1980s to present indicted that Bhutan’s temperature has become warmer and precipitation has increased. Satellite-based precipitation and temperature data were compared to in situ precipitation and temperature data, yielding high correlations for both precipitation (R=0.85) and temperature (R=0.9). The project results and methods were shared with the Ugyen Wangchuck Institute for Conservation and Environmental Research (UWICER) to help assess climate change impacts in Bhutan.

DEVELOP Tech Paper↗
NASA NTRS2011

Multipoint Observations of Coronal Mass Ejection and Solar Energetic Particle Events on Mars and Earth During November 2001

Multipoint spacecraft observations provide unique opportunities to constrain the propagation and evolution of interplanetary coronal mass ejections (ICMEs) throughout the heliosphere. Using Mars Global Surveyor (MGS) data to study both ICME and solar energetic particle (SEP) events at Mars and OMNI and Geostationary Operational Environmental Satellite (GOES) data to study ICMEs and SEPs at Earth, we present a detailed study of three CMEs and flares in late November 2001. In this period, Mars trailed Earth by 56deg solar longitude so that the two planets occupied interplanetary magnetic field lines separated by only approx.25deg. We model the interplanetary propagation of CME events using the ENLIL version 2.6 3-D MHD code coupled with the Wang-Sheeley-Arge version 1.6 potential source surface model, using Solar and Heliospheric Observatory (SOHO) Large Angle and Spectrometric Coronagraph (LASCO) images to determine CME input parameters. We find that multipoint observations are essential to constrain the simulations of ICME propagation, as two very different ICMEs may look very similar in only one observational location. The direction and width of the CME as parameters essential to a correct estimation of arrival time and amplitude of the ICME signal. We find that these are problematic to extract from the analysis of SOHO/LASCO images commonly used for input to ICME propagation models. We further confirm that MGS magnetometer and electron reflectometer data can be used to study not only ICME events but also SEP events at Mars, with good results providing a consistent picture of the events when combined with near-Earth data.

Falkenberg, T. V.↗
NASA NTRS1974

An operational application of ERTS-1 imagery to the environmental inventory process

A discussion is presented of how The Engineer Agency for Resources Inventories utilized ERTS remotely sensed imagery as a/supplement to airphotos and collateral data for an environmental impact study of the Atchafalaya Basin for the New Orleans engineer district. This single overall inventory permitted a systematic approach and substantial economy for a number of engineering projects for which environmental impact statements would be required. The study area covered approximately 25,000 square miles and included all or part of 36 parishes in Louisiana and 8 counties in Mississippi. It was concluded that as a supplementary source, used in conjunction with airphotos, ERTS had proven itself as a significant means of economy. As a primary source, the Engineer Agency is not yet ready to accept ERTS for their own particular applications.

Oneal, J. D.↗
DOE OSTI2022

Disentangling error structures of precipitation datasets using decision trees

Characterizing error structures in precipitation products not only facilitates their proper applications for scientific and practical purposes but also helps improve their retrieval algorithms and processing methods. Despite the fact that multiple precipitation products have been assessed in the literature, factors that affect their error structures remain inadequately addressed. By interpreting 60 binary decision trees, this study disentangles the error characteristics of precipitation products in terms of their spatiotemporal patterns and geographical factors. Three independent precipitation products - two satellite-based and one reanalysis datasets: the Integrated Multi-satellitE Retrievals for GPM (Global Precipitation Measurement) late run (IMERG-L), Soil Moisture to Rain-Advanced SCATterometer (SM2RAIN-ASCAT), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 uncorrected precipitation output (MERRA2-UC), are evaluated across the contiguous United States from 2010 to 2019. Here, the ground-based Stage IV precipitation dataset is used as the ground truth. Results indicate that the MERRA2-UC outperforms the IMERG-L and SM2RAIN-ASCAT with higher accuracy and more stable interannual patterns for the analysis period. Decision trees cross-assess three spatiotemporal factors and find that the underestimation of MERRA2-UC occurs in the east of the Rocky Mountains, and SM2RAIN-ASCAT underestimates precipitation over high latitudes, especially in winter. Additionally, the decision tree method ascribes system errors to nine different geographical characteristics, of which the distance to the coast, soil type, and DEM are the three dominant features. On the other hand, the land cover type, topography position index, and aspect are three relatively weak factors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Genomad v1.0

Genomad aims to identify mobile genetic elements (namely, viruses and plasmids) from DNA sequence data. It uses a combination of marker gene identification and machine learning models to find likely virus/plasmid candidates in environmental DNA sequencing data. It has an improved classification performance over similar tools.

Camargo, Antonio↗
NASA NTRS1989

Reflectance characteristics and surface processes in stabilized dune environments

Analysis of multitemporal TM data for three environmentally related field areas yields information on the response characteristics of stabilized dunes and desert-fringe environments. The three field sites studied include dune fields in Egypt, Mali, and Botswana, ranging in climate from hyperarid to semiarid, and may be classed as an environmental series relating surface processes under Saharan, Sahelian, and Savanna conditions. Sites were field mapped and monitored with TM data for lengths of time up to a year. The complexity of spectral response characteristics is greatest where vegetation is dense and diverse, but study of the three environments together places constraints on the importance of vegetation to spectral response as well as to mechanisms of sand transport. In both Mali and Botswana, the Sahelian and Savanna environments, contrast reversals occur on dune crests and reflectance patterns change through the dry season to resemble the response curves of the hyperarid study site in Egypt. In these analyses, overall surface brightness is controlled by sand composition, while spectral features are controlled by vegetation dynamics.

Jacobberger, P. A.↗
NASA NTRS2000

NOAA-L

The National Oceanic and Atmospheric Administration (NOAA) and the National Aeronautics and Space Administration (NASA) have jointly developed a valuable series of polar-orbiting Earth environmental observation satellites since 1978. These satellites provide global data to NOAA's short- and long-range weather forecasting systems. The system consists of two polar-orbiting satellites known as the Advanced Television Infrared Observation Satellites (TIROS-N) (ATN). Operating as a pair, these satellites ensure that environmental data, for any region of the Earth, is no more than six hours old. These polar-orbiting satellites have not only provided cost-effective data for very immediate and real needs but also for extensive climate and research programs. The weather data (including images seen on television news programs) has afforded both convenience and safety to viewers throughout the world. The satellites also support the SARSAT (Search and Rescue Satellite Aided Tracking) part of the COSPAS-SARSAT constellation. Russia provides the COSPAS (Russian for Space Systems for the Search of Vessels in Distress) satellites. The international COSPAS-SARSAT system provides for the detection and location of emergency beacons for ships, aircraft, and people in distress and has contributed to the saving of more than 10,000 lives since its inception in 1982.

McCain, Harry G.↗
NASA NTRSDate not supplied

NASA's Professional DEVELOPment - Evaluating 10 Weeks of Capacity Building

Under NASA’s Applied Sciences, the NASA DEVELOP Program is centered on dual capacity building. Projects bring together partners and participants to learn how Earth observation data can enhance environmental decision-making practices and inform action. During their time with DEVELOP, participants build technical skills around remotely sensed data and professional skills through interactions with team members, science advisors, and partners. To further refine the participant experience, DEVELOP explores which technical and professional skills individuals report improving during the 10-week program. An analysis of self-reported assessments from 2018 to 2021 included projects that were conducted in-person and virtually. Participants consistently indicated a strong improvement in technical and professional skills yet there was clear variation between in-person and virtual opportunities. When comparing between 2019 and 2021, self-reporting showed a higher percentage of participants reporting an increase in networking in the virtual environment and an increase in building professional relationships with project partners virtually. This analysis suggests that professional opportunities available in the virtual environment may in fact bolster early career scientists’ networking abilities. This presentation will identify DEVELOP’s approach to monitoring and evaluation, highlight interesting trends introduced by the pandemic, and lessons learned.

Sarah Payne↗
NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗
DOE OSTI2023

A General Spatiotemporal Imputation Framework for Missing Sensor Data

Many applications from precision agriculture, environmental monitoring and transportation networks rely on data collected across space and time over a large geographic area. Missing data poses a significant challenge for any data-driven inference and control tasks. Data imputation or the estimation of missing data can help fill these gaps by utilizing inherent spatial relationships and temporal patterns. A variety of spatiotemporal imputation models have been developed to address missing data in spatiotemporal datasets. However, these classical methods rely on the assumption that the underlying data follows a smooth trend and fail to provide accurate estimates when there is a large number of missing points in the data. Even though there are machine learning driven tensor completion approaches such as convolutional neural network based tensor completion (CoSTCo) that capture the non-linear relationships in the dataset, the transductive nature makes the algorithm less scalable. Thus, existing approaches for estimating the missing information do not effectively capture all dimensions of the spatiotemporal data structure, resulting in erroneous predictions and poor performance. The main contributions of this paper are: (1) We propose a novel inductive framework (G-LSTM) for missing data imputation that integrates a graph neural network with LSTMs to effectively capture both spatial and temporal dependencies. (2) Experimental results on a traffic dataset demonstrate that the proposed GNN integrated with an LSTM framework achieves improved imputation and maintains steady performance even when there are extreme missing conditions in comparison with the state-of-the-art imputation framework (i.e, CoSTCo). (3) The simulation results on a traffic network show up to 69% reduction in mean absolute error and 61% reduction in root mean square error when compared to CoSTCo.

Tharzeen, Aabila↗
DOE OSTI2020

Association of residential energy efficiency retrofits with indoor environmental quality, comfort, and health: A review of empirical data

This paper reviews empirical data from evaluations of the influence of residential energy efficiency retrofits on indoor environmental quality conditions and self-reported thermal comfort and health. The data were extracted from 36 studies described in 44 papers plus two reports. Nearly all reviewed studies were performed in Europe or United States. Most studies evaluated retrofits of homes with low-income occupants. Indoor radon and formaldehyde concentrations tended to increase after retrofits that did not add whole-house mechanical ventilation. Study-average indoor concentrations of nitrogen dioxide and volatile organic compounds other than formaldehyde increased and decreased with approximately equal frequency. Average indoor temperatures during winter typically increased after retrofits, usually by less than 1.5 °C. Dampness and mold, usually based on occupant's reports, almost always decreased after retrofits. Subjectively reported thermal comfort, thermal discomfort, non-asthma respiratory symptoms, general health, and mental health nearly always improved after retrofits. For asthma symptoms, the evidence of improvement slightly outweighed the evidence of worsening. There was insufficient evidence to determine whether changes in thermal comfort and health outcomes varied depending on the type of energy efficiency retrofit. The published research has numerous limitations including a lack of data from retrofits in warm-humid climates and minimal data on changes in objective health outcomes. Suggestions for future research are provided.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Data-Driven Co-optimization of Energy Efficiency and Indoor Environmental Quality in Commercial Buildings

In this paper, we use publicly available data of a highly instrumented building to estimate how zonal temperature and carbon dioxide (CO2) concentration are related to some key operational and environmental measurements. Subsequently, we have developed, simulated, and evaluated an optimization framework for minimizing the energy consumption of the central heating, ventilation and air conditioning (HVAC) unit while meeting zonal temperature and indoor air quality (IAQ) standards. Finally, we have evaluated the achievable energy savings for our proposed approach as compared to a baseline approach and reported significant savings potential.

Naqvi, Syed Ahsan Raza↗
NASA NTRS2007

The Application of NASA Technology to Public Health

NASA scientists have a history of applying technologies created to handle satellite data to human health at various spatial scales. Scientists are now engaged in multiple public health application projects that integrate NASA satellite data with measures of public health. Such integration requires overcoming disparities between the environmental and the health data. Ground based sensors, satellite imagery, model outputs and other environmental sources have inconsistent spatial and temporal distributions. The MSFC team has recognized the approach used by environmental scientists to fill in the empty places can also be applied to outcomes, exposures and similar data. A revisit to the classic epidemiology study of 1854 using modern day surface modeling and GIS technology, demonstrates how spatial technology can enhance and change the future of environmental epidemiology. Thus, NASA brings to public health, not just a set of data, but an innovative way of thinking about the data.

Rickman, Douglas L.↗