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NASA NTRS1994

FAST User Guide

The Flow Analysis Software Toolkit, FAST, is a software environment for visualizing data. FAST is a collection of separate programs (modules) that run simultaneously and allow the user to examine the results of numerical and experimental simulations. The user can load data files, perform calculations on the data, visualize the results of these calculations, construct scenes of 3D graphical objects, and plot, animate and record the scenes. Computational Fluid Dynamics (CFD) visualization is the primary intended use of FAST, but FAST can also assist in the analysis of other types of data. FAST combines the capabilities of such programs as PLOT3D, RIP, SURF, and GAS into one environment with modules that share data. Sharing data between modules eliminates the drudgery of transferring data between programs. All the modules in the FAST environment have a consistent, highly interactive graphical user interface. Most commands are entered by pointing and'clicking. The modular construction of FAST makes it flexible and extensible. The environment can be custom configured and new modules can be developed and added as needed. The following modules have been developed for FAST: VIEWER, FILE IO, CALCULATOR, SURFER, TOPOLOGY, PLOTTER, TITLER, TRACER, ARCGRAPH, GQ, SURFERU, SHOTET, and ISOLEVU. A utility is also included to make the inclusion of user defined modules in the FAST environment easy. The VIEWER module is the central control for the FAST environment. From VIEWER, the user can-change object attributes, interactively position objects in three-dimensional space, define and save scenes, create animations, spawn new FAST modules, add additional view windows, and save and execute command scripts. The FAST User Guide uses text and FAST MAPS (graphical representations of the entire user interface) to guide the user through the use of FAST. Chapters include: Maps, Overview, Tips, Getting Started Tutorial, a separate chapter for each module, file formats, and system administration.

Walatka, Pamela P.↗

NASA NTRS2013

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Shen, Suhung↗

NASA NTRS2022

Information Fusion and Data Analytics for Human Lunar Exploration (CIF REPORT: Detailed PI Write-up)

The Information Fusion & Data Analytics (IFDA) project commenced in FY20, continued through FY21, and its final platform development phase continues in FY22. The objective remains the fusion and rapid accessibility of large quantities of disparate sourced human spaceflight data. IFDA is a platform tailored for NA (S&MA) to develop highly advanced operational data integration and analysis techniques. IFDA leverages the JSC ER7 modeling, simulation,and data fusion capabilities to collect, warehouse, and augment data human exploration data integration and analysis techniques. The IFDA project’s integrated data visualizations have been demonstrated in two validation scenarios in FY21, and provided the architecture and platform basis for development of a full-scale data analysis suite and storage solution useful to all JSC organizations engaged in real time operations and safety tasks. Scenarioand prototypical development including the construction of a full scale data analysis suite and storage solution, useful to all JSC organizations engaged in real time operations and safety tasks, is central to IFDA Phase 3 and provides a demonstrable pathway for the Digital Transformation Program. IFDA Phase 3 is focused on data provider, data utilizer, and SME hands-on workshops that will conclude the Dem / Valphase and deliver a program-ready data integration tool as a product.

information fusion↗

NASA NTRS2022

Information Fusion & Analytics for Human Lunar Exploration

information fusion↗

NASA NTRS1994

Interactive Visualization of Computational Fluid Dynamics using Mosaic

The Web provides new Methods for accessing Information world-wide, but the current text-and-pictures approach neither utilizes all the Web's possibilities not provides for its limitations. While the inclusion of pictures and animations in a paper communicates more effectively than text alone, It Is essentially an extension of the concept of "publication." Also, as use of the Web increases putting images and animations online will quickly load even the "Information Superhighway." We need to find forms of communication that take advantage of the special nature of the Web. This paper presents one approach: the use of the Internet and the Mosaic interface for data sharing and collaborative analysis. We will describe (and In the presentation, demonstrate) our approach: using FAST (Flow Analysis Software Toolkit), a scientific visualization package, as a data viewer and interactive tool called from MOSAIC. Our intent is to stimulate the development of other tools that utilize the unique nature of electronic communication.

Clucas, Jean↗

NASA NTRS2020

An Update on Global Satellite-Based Precipitation Products and Services at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is home to major NASA satellite precipitation measurement missions including the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) as well as other NASA projects. Accurate and timely available global and regional precipitation products play an important role in research and applications around the world. The GES DISC provides near-real-time, near-global precipitation products (e.g.IMERG) to support a wide variety of interdisciplinary research and operational activities including flood modeling, landslides, crop monitoring and assessment, vector-borne diseases, etc. Climate data record products (e.g.GPCP3) are essential for climate research, assessment, model evaluation and applications. To facilitate data access and exploration, the GES DISC has developed data services such asGiovanni, an online visualization and analysis tool for easy access to over 2000 satellite- and model-based variables. Established in the mid 1980s, the GES DISC also distributes data in other disciplines including hydrology, atmospheric chemistry, atmospheric dynamics, etc. In this presentation, we will present an update on global precipitation products and data services including the new IMERG V06B suite, the latest version of GPCP (Version 3) and value-added data subsetting services (L34RS, L2S).

Liu, Zhong↗

NASA NTRS2014

Proto-Examples of Data Access and Visualization Components of a Potential Cloud-Based GEOSS-AI System

Once a research or application problem has been identified, one logical next step is to search for available relevant data products. Thus, an early component of a potential GEOSS-AI system, in the continuum between observations and end point research, applications, and decision making, would be one that enables transparent data discovery and access by users. Such a component might be effected via the systems data agents. Presumably, some kind of data cataloging has already been implemented, e.g., in the GEOSS Common Infrastructure (GCI). Both the agents and cataloging could also leverage existing resources external to the system. The system would have some means to accept and integrate user-contributed agents. The need or desirability for some data format internal to the system should be evaluated. Another early component would be one that facilitates browsing visualization of the data, as well as some basic analyses.Three ongoing projects at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provide possible proto-examples of potential data access and visualization components of a cloud-based GEOSS-AI system. 1. Reorganizing data archived as time-step arrays to point-time series (data rods), as well as leveraging the NASA Simple Subset Wizard (SSW), to significantly increase the number of data products available, at multiple NASA data centers, for production as on-the-fly (virtual) data rods. SSWs data discovery is based on OpenSearch. Both pre-generated and virtual data rods are accessible via Web services. 2. Developing Web Feature Services to publish the metadata, and expose the locations, of pre-generated and virtual data rods in the GEOSS Portal and enable direct access of the data via Web services. SSW is also leveraged to increase the availability of both NASA and non-NASA data.3.Federating NASA Giovanni (Geospatial Interactive Online Visualization and Analysis Interface), for multi-sensor data exploration, that would allow each cooperating data center, currently the NASA Distributed Active Archive Centers (DAACs), to configure its own Giovanni deployment, while also allowing all the deployments to incorporate each others data. A federated Giovanni comprises Giovanni Virtual Machines, which can be run on local servers or in the cloud.

access↗

NASA NTRS2011

Online Time Series Analysis of Land Products over Asia Monsoon Region via Giovanni

Time series analysis is critical to the study of land cover/land use changes and climate. Time series studies at local-to-regional scales require higher spatial resolution, such as 1km or less, data. MODIS land products of 250m to 1km resolution enable such studies. However, such MODIS land data files are distributed in 10ox10o tiles, due to large data volumes. Conducting a time series study requires downloading all tiles that include the study area for the time period of interest, and mosaicking the tiles spatially. This can be an extremely time-consuming process. In support of the Monsoon Asia Integrated Regional Study (MAIRS) program, NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) has processed MODIS land products at 1 km resolution over the Asia monsoon region (0o-60oN, 60o-150oE) with a common data structure and format. The processed data have been integrated into the Giovanni system (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) that enables users to explore, analyze, and download data over an area and time period of interest easily. Currently, the following regional MODIS land products are available in Giovanni: 8-day 1km land surface temperature and active fire, monthly 1km vegetation index, and yearly 0.05o, 500m land cover types. More data will be added in the near future. By combining atmospheric and oceanic data products in the Giovanni system, it is possible to do further analyses of environmental and climate changes associated with the land, ocean, and atmosphere. This presentation demonstrates exploring land products in the Giovanni system with sample case scenarios.

Shen, Suhung↗

NASA NTRS1995

The CCD/Transit Instrument (CTI) data-analysis system

The automated software system for archiving, analyzing, and interrogating data from the CCD/Transit Instrument (CTI) is described. The CTI collects up to 450 Mbytes of image-data each clear night in the form of a narrow strip of sky observed in two colors. The large data-volumes and the scientific aims of the project make it imperative that the data are analyzed within the 24-hour period following the observations. To this end a fully automatic and self evaluating software system has been developed. The data are collected from the telescope in real-time and then transported to Tucson for analysis. Verification is performed by visual inspection of random subsets of the data and obvious cosmic rays are detected and removed before permanent archival is made to the optical disc. The analysis phase is performed by a pair of linked algorithms, one operating on the absolute pixel-values and the other on the spatial derivative of the data. In this way both isolated and merged images are reliably detected in a single pass. In order to isolate the latter algorithm from the effects of noise spikes a 3x3 Hanning filter is applied to the raw data before the analysis is run. The algorithms reduce the input pixel-data to a database of measured parameters for each image which has been found. A contrast filter is applied in order to assign a detection-probability to each image and then x-y calibration and intensity calibration are performed using known reference stars in the strip. These are added to as necessary by secondary standards boot-strapped from the CTI data itself. The final stages involve merging the new data into the CTI Master-list and History-list and the automatic comparison of each new detection with a set of pre-defined templates in parameter-space to find interesting objects such as supernovae, quasars and variable stars. Each stage of the processing from verification to interesting image selection is performed under a data-logging system which both controls the pipe-lining of data through the system and records key performance monitor parameters which are built into the software. Furthermore, the data from each stage are stored in databases to facilitate evaluation, and all stages offer the facility to enter keyword-indexed free-format text into the data-logging system. In this way a large measure of certification is built into the system to provide the necessary confidence in the end results.

Cawson, M. G. M.↗

NASA NTRS1993

Geologic mapping using integrated AIRSAR, AVIRIS, and TIMS data

The multi-sensor aircraft campaign called the 'Geologic Remote Sensing Field Experiment' (GRSFE), conducted during 1989 in the southwestern United States, collected multiple airborne remote sensing data sets and associated field and laboratory measurements. The GRSFE airborne data sets used in this study include the airborne Synthetic Aperture Radar (AIRSAR), the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), and the Thermal Infrared Multispectral Scanner (TIMS). Each sensor's unique characteristics were used for this study in a combined analysis scheme for geologic mapping. AIRSAR was used to map structures and landforms, AVIRIS was used to map mineralogy, and TIMS was used to map lithology. Visual data integration using IHS transforms and combined numerical analysis using derived geophysical and geologic parameters with 'multispectral' techniques resulted in improved geologic mapping over that possible using each data set individually.

Kruse, Fred A.↗

NASA NTRS2019

New Era, New Opportunity, Is GES DISC Ready for Big Data Challenge?

The new era of Big Data has opened doors for many new opportunities, as well as new challenges, for both Earth science research/application and data communities. As one of the twelve NASA data centers - Goddard Earth Sciences Data and Information Services Center (GES DISC), one of our great challenges has been how to help research/application community efficiently (quickly and properly) accessing, visualizing and analyzing the massive and diverse data in natural hazard research, management, or even prediction. GES DISC has archived over 2000 TB data on premises and distributed over 23,000 TB of data since 2010. Our data has been widely used in every phase of natural hazard management and research, i.e. long term risk assessment and reduction, forecasting and predicting, monitoring and detection, early warning, damage assessment and response. The big data challenge is not just about data storage, but also about data discoverability and accessibility, and even more, about data migration/mirroring in the cloud. This paper is going to demonstrate GES DISC’s efforts and approaches of evolving our overall Web services and powerful Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) tool into further improving data discoverability and accessibility. Prototype works will also be presented.

Li, A.↗

NASA NTRS2011

Estimating Contrail Climate Effects from Satellite Data

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Minnis, Patrick↗

NASA NTRS2007

Boundary Layer Development on a Turbine Blade in a Linear Cascade

Several different boundary-layer development patterns for flow over the suction surface of a turbine airfoil in a linear cascade were studied and documented using a sliding surface hot-film sensor. The state of the boundary layer, whether laminar, transitional or turbulent, was determined at numerous locations along the airfoil suction surface from leading to trailing edge. Boundary-layer transition from laminar to turbulent flow through laminar separation and turbulent reattachment, or through a combination of bypass transition and strong and weak separation and turbulent reattachment, or through solely bypass transition without separation, was observed and benchmark data were recorded. Surface flow visualization and numerical boundary-layer analysis results are consistent with the hot-film data. Flow and geometry information necessary for nmerical code operation is available.

Halstead, Dave↗

NASA NTRS1991

Four dimensional reconstruction and analysis of plume images

A number of methods have been investigated and are under current investigation for monitoring the health of the Space Shuttle Main Engine (SSME). Plume emission analysis has recently emerged as a potential technique for correlating the emission characteristics with the health of an engine. In order to correlate the visual and spectral signatures of the plume emission with the characteristic health monitoring features of the engine, the plume emission data must be acquired, stored, and analyzed in a manner similar to flame emission spectroscopy. The characteristic visual and spectral signatures of the elements vaporized in exhaust plume along with the features related to their temperature, pressure, and velocity can be analyzed once the images of plume emission are effectively acquired, digitized, and stored on a computer. Since the emission image varies with respect to time at a specified planar location, four dimensional visual and spectral analysis need to be performed on the plume emission data. In order to achieve this objective, feasibility research was conducted to digitize, store, analyze, and visualize the images of a subsonic jet in a cross flow. The jet structure was made visible using a direct injection flow visualization technique. The results of time-history based three dimensional reconstruction of the cross sectional images corresponding to a specific planar location of the jet structure are presented. The experimental set-up to acquire such data is described and three dimensional displays of time-history based reconstructions of the jet structure are discussed.

Dhawan, Atam P.↗

NASA NTRS2019

GeneLab: Overview of Challenges and Opportunities

The NASA GeneLab project capitalizes on multi-omic technologies to maximize the return on spaceflight experiments. To do this, GeneLab maintains a publicly accessible database (GLDS) that houses spaceflight and spaceflight relevant multi-omics data, and collaborates with NASA principal investigators and projects to generate additional omics data. GeneLab houses more than 200 transcriptomic, proteomic, metabolomic and epigenomic datasets from plant, animal and microbial experiments, with a growing number of these having been produced by the GeneLab sample processing lab. The GLDS contains rich metadata about each experiment and has recently integrated radiation dosimetery data from experiments flown on the Space Shuttle. GeneLab has also recently implemented an effort to present processed data in the GLDS in addition to the raw omics data. The processed data will enable interpretation of the data by a larger group of students, scientists and the general public. Standard pipelines for the transformation of raw data into visualizations were developed by four GeneLab Analysis Working Groups (animals, plants, microbes, multi-omics) comprised of over 100 scientists from NASA and academia. These pipelines are now being used by a group of bioinformatics interns to provide standard basic analysis of the data for incorporation into GLDS.

Galazka, Jonathan M.↗

NASA NTRS2019

GeneLab: Open Science for Life in Space

Galazka, Jonathan M.↗

NASA NTRS1975

Remote sensing and urban public health

The applicability of remote sensing in the form of aerial photography to urban public health problems is examined. Environmental characteristics are analyzed to determine if health differences among areas could be predicted from the visual expression of remote sensing data. The analysis is carried out on a socioeconomic cross-sectional sample of census block groups. Six morbidity and mortality rates are the independent variables while environmental measures from aerial photographs and from the census constitute the two independent variable sets. It is found that environmental data collected by remote sensing are as good as census data in evaluating rates of health outcomes.

Rush, M.↗

NASA NTRS1977

The application of remote sensing to the development and formulation of hydrologic planning models

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

Fowler, T. R.↗