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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗
NASA NTRS2012

QuakeSim 2.0

QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data has proved useful for mid-term forecasting of earthquakes, and for detecting subtle changes in crustal deformation. The GPS time series analysis has also proved useful as a data-quality tool, enabling the discovery of station anomalies and data processing and distribution errors. Improved visualization tools enable more efficient data exploration and understanding. Tools provide flexibility to science users for exploring data in new ways through download links, but also facilitate standard, intuitive, and routine uses for science users and end users such as emergency responders.

Donnellan, Andrea↗
NASA NTRS2020

Pacific Northwest Health & Air Quality - Utilizing NASA Earth Observations to Analyze Air Quality Impacts from Wildfires in the Pacific Northwest

The Pacific Northwest region of the United States and Canada has become more vulnerable to intense wildfire regimes due to years of fire suppression and climatic changes. Smoke from fires exposes communities to hazardous aerosols and pollutants known to trigger asthma symptoms and exacerbate other respiratory and cardiovascular diseases. In partnership with The Nature Conservancy’s Washington Chapter and the Puget Sound Clean Air Agency, NASA DEVELOP investigated the impacts of wildfire smoke on air quality from 2008 to 2020 using NASA Earth observations. To explore the various dimensions of smoke and its relation to air quality, the team looked at the vertical extent of smoke plumes and the resulting changes in air quality. The team evaluated the potential relationship between plume height of wildfire smoke and fire radiative power using the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites and Terra’s Multi-angle Imaging SpectroRadiometer (MISR) using the MISR INteractive eXplorer (MINX). The team determined that there was no regional relationship between fire radiative power and smoke plume height. To investigate changes in air quality resulting from wildfire smoke, the team utilized data from NASA’s Fire Information for Resource Management System, from the European Space Agency’s Sentinel-5P Tropospheric Monitoring Instrument (TROPOMI), and true color imagery from Landsat 8 Operational Land Imager (OLI). The team created a Google Earth Engine-based (GEE) web tool to visualize changes in atmospheric pollutants and aerosol optical depth. Results of case study fires showed varying increases in pollutant concentrations when compared to a baseline map. The end products provided the partners with tools to quantify plume height using MINX and to visualize recent air quality patterns relating to variations in wildfire extent and severity in the Pacific Northwest

Ani Matevosian↗
NASA NTRSDate not supplied

Entwine Point Tiles for 3D Visualization and Querying of ICESat-2

Point Cloud data from non-optical sensors present challenges in scientific computing in both volume of data and files, even for cloud services environments. As part of the Multi-Mission Algorithm and Analysis Platform (MAAP), a joint open science platform for global biomass modelling, we’ve developed a cloud optimized workflow for using ATL08 (ICESat-2) data as a point cloud. For MAAP, the ATL08 data product is published as Entwine Point Tiles (EPT), allowing users to visualize and query the full extent of this collection interactively without pre-downloading, or preprocessing. The EPT format is a cloud-optimized point cloud data format which re-organizes points into a cloud friendly spatially indexed data structure. MAAP uses AWS S3 to store these point clouds and serves them over OGC specified APIs, 3DTiles for visualization, and WFS for querying. This workflow allows for interactive 3D visualizations in a web browser, including notebook environments and facilitates on the fly subsetting for interactive data exploration, all of which can be applied to other similar sensors.

Alex Mandel↗
NASA NTRS2016

Interactive Visualization of Near Real Time and Production Global Precipitation Measurement (GPM) Mission Data Online Using CesiumJS

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, prerendered animations, or cumbersome geoservers. These methods can limit interactivity andor place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite-observed them on and above the Earths surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

satellite precipitation measurement↗
NASA NTRS2014

Creating a Prototype Web Application for Spacecraft Real-Time Data Visualization on Mobile Devices

Mobile devices (smart phones, tablets) have become commonplace among almost all sectors of the workforce, especially in the technical and scientific communities. These devices provide individuals the ability to be constantly connected to any area of interest they may have, whenever and wherever they are located. The Huntsville Operations Support Center (HOSC) is attempting to take advantage of this constant connectivity to extend the data visualization component of the Payload Operations and Integration Center (POIC) to a person's mobile device. POIC users currently have a rather unique capability to create custom user interfaces in order to view International Space Station (ISS) payload health and status telemetry. These displays are used at various console positions within the POIC. The Software Engineering team has created a Mobile Display capability that will allow authenticated users to view the same displays created for the console positions on the mobile device of their choice. Utilizing modern technologies including ASP.net, JavaScript, and HTML5, we have created a web application that renders the user's displays in any modern desktop or mobile web browser, regardless of the operating system on the device. Additionally, the application is device aware which enables it to render its configuration and selection menus with themes that correspond to the particular device. The Mobile Display application uses a communication mechanism known as signalR to push updates to the web client. This communication mechanism automatically detects the best communication protocol between the client and server and also manages disconnections and reconnections of the client to the server. One benefit of this application is that the user can monitor important telemetry even while away from their console position. If expanded to the scientific community, this application would allow a scientist to view a snapshot of the state of their particular experiment at any time or place. Because the web application renders the displays that can currently be created with the POIC ground system, the user can tailor their displays for a particular device using tools that they are already trained to use.

Lang, Jeremy S.↗
NASA NTRS2012

Giovanni: The Bridge between Data and Science

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a web-based remote sensing and model data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional data sets, covering atmospheric dynamics, atmospheric chemistry, hydrology, oceanographic, and land surface. Data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. Visualization options enable comparisons of multiple variables and easier refinement. Recently, new features have been developed, such as interactive scatter plots and maps. The performance is also being improved, in some cases by an order of magnitude for certain analysis functions with optimized software. We are working toward merging current Giovanni portals into a single omnibus portal with all variables in one (virtual) location to help users find a variable easily and enhance the intercomparison capability

Shen, Suhung↗
NASA NTRS2019

Web-based Decision Support System Tools: the Soil and Water Assessment Tool Online Visualization and Analyses (SWATOnline) and NASA Earth Observation Data Downloading and Reformatting Tool (NASAaccess)

The current influx of climate related information required scientists to communicate their findings to decision makers in governments, disaster preparedness organizations, and the general public. The Soil and Water Assessment Tool (SWAT) is a powerful modelling tool that allows scientists to simulate many of the physical processes involved in the water cycle. This article presents the design, methods and development efforts to overcome some of the limitations of the previously developed SWAT visualization software programs by creating a set of modular web applications that can be duplicated, customized, and run. Moreover, this article features a web application development tool for climate data retrieval. The NASAaccess fetches, extracts and reformats climate data from the National Aeronautics and Space Administration servers and outputs data compatible with hydrological models. This work has the potential to increase the SWAT's model impact on non-technically trained stakeholders and decision makers charged with water and climate management.

Tethys↗
NASA NTRS2005

Statistical Considerations of Data Processing in Giovanni Online Tool

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Suhung, Shen↗
NASA NTRS2013

Advanced Query and Data Mining Capabilities for MaROS

The Mars Relay Operational Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay network. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. As part of MaROS, the innovators have developed and implemented a feature set that operates on several levels of the software architecture. This new feature is an advanced querying capability through either the Web-based user interface, or through a back-end REST interface to access all of the data gathered from the network. This software is not meant to replace the REST interface, but to augment and expand the range of available data. The current REST interface provides specific data that is used by the MaROS Web application to display and visualize the information; however, the returned information from the REST interface has typically been pre-processed to return only a subset of the entire information within the repository, particularly only the information that is of interest to the GUI (graphical user interface). The new, advanced query and data mining capabilities allow users to retrieve the raw data and/or to perform their own data processing. The query language used to access the repository is a restricted subset of the structured query language (SQL) that can be built safely from the Web user interface, or entered as freeform SQL by a user. The results are returned in a CSV (Comma Separated Values) format for easy exporting to third party tools and applications that can be used for data mining or user-defined visualization and interpretation. This is the first time that a service is capable of providing access to all cross-project relay data from a single Web resource. Because MaROS contains the data for a variety of missions from the Mars network, which span both NASA and ESA, the software also establishes an access control list (ACL) on each data record in the database repository to enforce user access permissions through a multilayered approach.

Wang, Paul↗
NASA NTRS2018

Interactive Planetary Visualization and Analysis with NASA's Solar System Treks Portals

NASA's Solar System Trek online portals provide web-based suites of interactive visualization and analysis tools enabling mission planners, planetary scientists, students, and the general public to explore planetary surfaces as seen through the eyes of many different instruments aboard a wide range of spacecraft. The portals present a vast collection of mapped data products from past and current missions for a growing number of planetary bodies. As web-based toolsets, the portals do not require users to purchase or install any software beyond current web browsers. The interactive and immersive capabilities of these portals are being used for site selection and analysis by NASA and a number of its international partners, supporting upcoming missions. They are also being used by formal and informal educators, students from elementary through university levels of study, and members of the public who are engaged in the excitement of solar system exploration. This presentation will provide an overview of the Solar System Treks and highlight many of the exciting new additions to the project implemented this past year.

Treks↗
NASA NTRS2013

Usage of Data-Encoded Web Maps with Client Side Color Rendering for Combined Data Access, Visualization and Modeling Purposes

Current approaches to satellite observation data storage and distribution implement separate visualization and data access methodologies which often leads to the need in time consuming data ordering and coding for applications requiring both visual representation as well as data handling and modeling capabilities. We describe an approach we implemented for a data-encoded web map service based on storing numerical data within server map tiles and subsequent client side data manipulation and map color rendering. The approach relies on storing data using the lossless compression Portable Network Graphics (PNG) image data format which is natively supported by web-browsers allowing on-the-fly browser rendering and modification of the map tiles. The method is easy to implement using existing software libraries and has the advantage of easy client side map color modifications, as well as spatial subsetting with physical parameter range filtering. This method is demonstrated for the ASTER-GDEM elevation model and selected MODIS data products and represents an alternative to the currently used storage and data access methods. One additional benefit includes providing multiple levels of averaging due to the need in generating map tiles at varying resolutions for various map magnification levels. We suggest that such merged data and mapping approach may be a viable alternative to existing static storage and data access methods for a wide array of combined simulation, data access and visualization purposes.

Pliutau, Denis↗
NASA NTRS2019

Pixel-Based Smoke Detection with Neural Network

Exposure to biomass burning has been linked to respiratory and cardiovascular illnesses in humans. Traditional satellite based visual and multispectral smoke detection methods are not scalable to capabilities of new generations of remote sensing platforms. We develop a scalable, deep learning based detection model capable of identifying smoke pixels using GOES-16 shortwave reflectance data and present a operational web-based tool to visualize smoke predictions.

Ramasubramanian, M.↗
NASA NTRS2014

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗
NASA NTRS2019

Visualization and Analysis of Data from Small-Body Missions with NASA's Solar System Treks Portals

The portals of NASA's Solar System Trek Project (SSTP) provide web-based suites of interactive visualization and analysis tools enabling mission planners, planetary scientists, students, and the general public to explore planetary surfaces as seen through the eyes of many different instruments aboard a wide range of spacecraft. The portals present a vast collection of mapped data products from past and current missions for a growing number of planetary bodies. As web-based toolsets, the portals do not require users to purchase or install any software beyond current web browsers. They feature a common user interface and are available through a single integrated website at https://trek.nasa.gov. This presentation will highlight 4 portals focusing on small bodies. We will provide an overview of established portals for (1) Ceres and (4) Vesta, and present the early capabilities for new portals being introduced for (162173) Ryugu and (101955) Bennu.

Day, Brian↗
NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

database↗
NASA NTRS2015

Open Source Mission Control for Chrome

New technology presents the possibility to evolve mission control. WARP (Web Applications for Resource Prospector) a new open source toolset for mission visualization, brings mission control to the Chrome Web Browser. WARP integrates multiple data sources into a coherent visualization toolset from which users may assemble their own software, thus giving mission controllers more flexibility. This frees us to operate based on mission needs, rather than constraints enforced by software application boundaries.

software engineering↗