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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 NTRS2010

Benefits of Using Remote Sensing for Health Alerts and Chronic Respiratory Exposures

Respiratory diseases such as asthma can be triggered by environmental conditions that can be monitored using Earth observing data and environmental forecast models. Frequent dust storms in the southwestern United States, the annual cycle of juniper pollen events in the spring, and increased aerosol and ozone concentrations in summer, are health concerns shared by the community at large. Being able to forecast the occurrence of these events would help the health care community prepare for increased visits to emergency rooms, as well as allow public health officials to issue alerts to affected persons. This information also is important to epidemiologists for analyzing long-term trends and impacts of these events on the health and well-being of the community. Earth observing data collected by remote sensing platforms are important for improving the performance of models that can forecast these events, and in turn, improve products and information for decision-making by public health authorities. This presentation will discuss the benefits of using remote sensing data for forecasting environmental events that can adversely affect individuals with respiratory ailments. The presentations will include a brief discussion on relevant Earth observing data, the forecast models used, and societal benefits of the resulting products and information. Several NASA-funded projects will be highlighted as examples

Luvall, J. C.↗

NASA NTRS2012

The InSAR Scientific Computing Environment

We have developed a flexible and extensible Interferometric SAR (InSAR) Scientific Computing Environment (ISCE) for geodetic image processing. ISCE was designed from the ground up as a geophysics community tool for generating stacks of interferograms that lend themselves to various forms of time-series analysis, with attention paid to accuracy, extensibility, and modularity. The framework is python-based, with code elements rigorously componentized by separating input/output operations from the processing engines. This allows greater flexibility and extensibility in the data models, and creates algorithmic code that is less susceptible to unnecessary modification when new data types and sensors are available. In addition, the components support provenance and checkpointing to facilitate reprocessing and algorithm exploration. The algorithms, based on legacy processing codes, have been adapted to assume a common reference track approach for all images acquired from nearby orbits, simplifying and systematizing the geometry for time-series analysis. The framework is designed to easily allow user contributions, and is distributed for free use by researchers. ISCE can process data from the ALOS, ERS, EnviSAT, Cosmo-SkyMed, RadarSAT-1, RadarSAT-2, and TerraSAR-X platforms, starting from Level-0 or Level 1 as provided from the data source, and going as far as Level 3 geocoded deformation products. With its flexible design, it can be extended with raw/meta data parsers to enable it to work with radar data from other platforms

geodetic imaging↗

NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗

NASA NTRSDate not supplied

Building Capacity for Policy-makers in a Virtual Setting: Providing Tools to Analyze Wildfire Smoke Plumes and Their Impacts

The NASA DEVELOP Program conducted 10-week long feasibility projects in a remote work setting, including partnering with The Nature Conservancy’s Washington Chapter and the Puget Sound Clean Air Agency to investigate wildfire smoke from 2000 - 2020 in the Pacific Northwest using satellite-derived data. The team engaged with platforms for collaboration both internally with NASA affiliates and externally with community organizations. Working from multiple states, the team members used a variety of software including Google Meet, Microsoft Teams, and Google Earth Engine to foster communication and work with data in a shared virtual environment. Throughout the project, the team learned that executing the project in a distanced work setting made it easier to reach out to scientists across the country for expertise and guidance. To study changes in air quality resulting from wildfire smoke, the team utilized data from NASA’s Fire Information from Resource Management System (FIRMS) and the ESA’s Sentinel-5 TROPOspheric Monitoring Instrument (TROPOMI). The team created a Google Earth Engine web-based tool, “Plume Hazards and Observations of Emissions by Navigating an Interactive eXplorer” (PHOENIX), to visualize changes in pollutants and aerosol optical depth after fire events. The potential relationship between plume height and fire radiative power was evaluated by using NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua and Terra satellites and NASA’s Multi-angle Imaging SpectroRadiometer (MISR) aboard Terra with the MISR INteractive eXplorer (MINX). The PHOENIX smoke assessment tool and science communication infographics will be shared electronically with the partner organizations. Furthermore, the team introduced the partners to MINX and will provide a tailored tutorial that included a recorded video and a written component with a live virtual workshop. These resources build capacity for further research and education on wildfire smoke and air quality within communities.

NASA DEVELOP↗

NASA NTRS1994

Comment on 'Intercalibration of solar wind instruments during the International Magnetospheric Study' by S. M. Petrinec and C. T. Russell

In their paper Petrinec and Russell (PR) (1993) claim to have developed a 'more homogeneous and accurate set of solar wind data' by 'correcting' the reported ion densities from three plasma instruments: the Los Alamos National Laboratory (LANL) ion electrostatic analyzer on ISEE 3 and the LANL electrostatic analyzer and the Massachusetts Institute of Technology (MIT) Faraday cup plasma instrument on Interplanetary Monitoring Platform 8 (IMP 8). Their data manipulation techniques are examined. The foundations on which their data set are built, are discussed. Reanalysis by MIT on the MIT instrument (IMP 8) was done. Initial results have been issued. The Petrinec & Russell (1993) (PR) paper does not provide accurate density estimates and is an exercise that will only bring confusion to users of the data. The results of PR should be treated with skepticism.

Paularena, K. I.↗

NASA NTRS2013

RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers

RUSHMAPS is a new onboard data reduction scheme that gives real-time access to key science parameters (e.g. moments) of a class of heliophysics science and/or solar system exploration investigation that includes plasma particle spectrometers (PPS), but requires moments reporting (density, bulk-velocity, temperature, pressure, etc.) of higher-level quality, and tolerates a lowpass (variable quality) spectral representation of the corresponding particle velocity distributions, such that telemetry use is minimized. The proposed methodology trades access to the full-resolution velocity distribution data, saving on telemetry, for real-time access to both the moments and an adjustable-quality (increasing quality increases volume) spectral representation of distribution functions. Traditional onboard data storage and downlink bandwidth constraints severely limit PPS system functionality and drive cost, which, as a consequence, drives a limited data collection and lower angular energy and time resolution. This prototypical system exploit, using high-performance processing technology at GSFC (Goddard Space Flight Center), uses a SpaceCube and/or Maestro-type platform for processing. These processing platforms are currently being used on the International Space Station as a technology demonstration, and work is currently ongoing in a new onboard computation system for the Earth Science missions, but they have never been implemented in heliospheric science or solar system exploration missions. Preliminary analysis confirms that the targeted processor platforms possess the processing resources required for realtime application of these algorithms to the spectrometer data. SpaceCube platforms demonstrate that the target architecture possesses the sort of compact, low-mass/power, radiation-tolerant characteristics needed for flight. These high-performing hybrid systems embed unprecedented amounts of onboard processing power in the CPU (central processing unit), FPGAs (field programmable gate arrays), and DSP (digital signal processing) elements. The fundamental computational algorithm de constructs 3D velocity distributions in terms of spherical harmonic spectral coefficients (which are analogous to a Fourier sine-cosine decomposition), but uses instead spherical harmonics Legendre polynomial orthogonal functions as a basis for the expansion, portraying each 2D angular distribution at every energy or, geometrically, spherical speed-shell swept by the particle spectrometer. Optionally, these spherical harmonic spectral coefficients may be telemetered to the ground. These will provide a smoothed description of the velocity distribution function whose quality will depend on the number of coefficients determined. Successfully implemented on the GSFC-developed processor, the capability to integrate the proposed methodology with both heritage and anticipated future plasma particle spectrometer designs is demonstrated (with sufficiently detailed design analysis to advance TRL) to show specific science relevancy with future HSD (Heliophysics Science Division) solar-interplanetary, planetary missions, sounding rockets and/or CubeSat missions.

Figueroa-Vinas, Adolfo↗

NASA NTRS2011

Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials

Composite structures are gaining importance for use in the aerospace industry. Compared to metallic structures their behavior is less well understood. This lack of understanding may pose constraints on their use. One possible way to deal with some of the risks associated with potential failure is to perform in-situ monitoring to detect precursors of failures. Prognostic algorithms can be used to predict impending failures. They require large amounts of training data to build and tune damage model for making useful predictions. One of the key aspects is to get confirmatory feedback from data as damage progresses. These kinds of data are rarely available from actual systems. The next possible resource to collect such data is an accelerated aging platform. To that end this paper describes a fatigue cycling experiment with the goal to stress carbon-carbon composite coupons with various layups. Piezoelectric disc sensors were used to periodically interrogate the system. Analysis showed distinct differences in the signatures of growing failures between data collected at conditions. Periodic X-radiographs were taken to assess the damage ground truth. Results after signal processing showed clear trends of damage growth that were correlated to damage assessed from the X-ray images.

composites↗

NASA NTRS2017

Applications of Satellite Data to Support Improvements in Irrigation and Groundwater Management in California

In agricultural regions around the world, threats to water supplies from drought and groundwater depletion are driving increased demand for tools to advance agricultural water use efficiency and support sustainable groundwater management. Satellite mapping of evapotranspiration (ET) from irrigated agricultural lands can provide agricultural producers and water resource managers with information that can be used to both optimize ag water use and improve estimates of groundwater withdrawals for irrigation. We describe the development of two remote sensing-based tools for ET mapping in California, including important lessons in terms of system design, partnership development, and transition to operations. For irrigation management, the integration of satellite data and surface sensor networks to provide timely delivery of information on crop water requirements can make irrigation scheduling more practical, convenient, and accurate.Developed through a partnership between NASA and the CA Department of Water Resources, the Satellite Irrigation Management Support (SIMS) framework integrates satellite data with information from agricultural weather networks to map crop canopy development and crop water requirements at the scale of individual fields. Information is distributed to agricultural producers and water managers via a web-based interface and web data services. SIMS also provides an API that facilitates integration with other irrigation decision support tools, such as CropManage and IrriQuest. Field trials using these integrated tools have shown that they can be used to sustain yields while improving water use efficiency and nutrient management. For sustainable groundwater management, the combination of satellite-derived estimates of ET and data on surface water deliveries for irrigation can increase the accuracy of estimates of groundwater pumping. We are developing an OpenET platform to facilitate access to ET data from multiple models and accelerate operational use of ET data in support of a range of water management applications, including implementation of the Sustainable Groundwater Management Act in CA. By providing a shared basis for decision making, we anticipate that the OpenET platform will accelerate implementation of solutions for sustainable groundwater management.

Satellite↗

NASA NTRS2024

Big Cypress Water Resources: Using Earth Observations to Assess Water Quality in Big Cypress Reservation, FL

Upstream agricultural development and runoff are driving harmful algal blooms in the Big Cypress Reservation. The Seminole Tribe of Florida Environmental Resource Management Department monitors water quality in the Big Cypress Reservation, located on the north end of Big Cypress National Preserve. The Environmental Resource Management Department aims to incorporate Earth observations into its investigative approach, which consists of Geographic Information Systems and in situ water sampling. We assessed the feasibility of using Earth observations to measure harmful algal blooms over time and identify vulnerable areas. We analyzed data from multiple remote sensing platforms and sensors, including Landsat 8 Thermal Infrared Spectrometer(TIRS), Landsat 9 TIRS-2, Landsat 9 Operational Land Imager 2, Sentinel-2 MultiSpectral Instrument, and Sentinel-3 Ocean and Land Color Instrument. We determined that it was challenging to use Sentinel-3, Landsat 8, and Landsat 9 imagery for monitoring the canals within the Reservation, and that Sentinel-2 was the most capable platform for the study area. Using Sentinel-2, we created spectral indices for the detection of algal blooms. We used these indices to measure algal blooms at 8 stations across the Big Cypress Reservation. We then created time series and seasonal decompositions of in situ water sample data and indices to visualize relationships between datasets, along with correlation matrices. Our correlations were not conclusive. However, we found that the spectral indices have the potential to detect algal blooms. Lastly, we evaluated Maxar WorldView-3 imagery and found that using data from sensors with higher spatial resolutions would improve results.

Remote sensing↗

NASA NTRS2001

Integrated Component-based Data Acquisition Systems for Aerospace Test Facilities

The Multi-Instrument Integrated Data Acquisition System (MIIDAS), developed by the NASA Langley Research Center, uses commercial off the shelf (COTS) products, integrated with custom software, to provide a broad range of capabilities at a low cost throughout the system s entire life cycle. MIIDAS combines data acquisition capabilities with online and post-test data reduction computations. COTS products lower purchase and maintenance costs by reducing the level of effort required to meet system requirements. Object-oriented methods are used to enhance modularity, encourage reusability, and to promote adaptability, reducing software development costs. Using only COTS products and custom software supported on multiple platforms reduces the cost of porting the system to other platforms. The post-test data reduction capabilities of MIIDAS have been installed at four aerospace testing facilities at NASA Langley Research Center. The systems installed at these facilities provide a common user interface, reducing the training time required for personnel that work across multiple facilities. The techniques employed by MIIDAS enable NASA to build a system with a lower initial purchase price and reduced sustaining maintenance costs. With MIIDAS, NASA has built a highly flexible next generation data acquisition and reduction system for aerospace test facilities that meets customer expectations.

Ross, Richard W.↗

NASA NTRS1973

ERTS-1 - Teaching us a new way to see.

The ERTS-1 payload is discussed, giving attention to three television cameras, which view the same area in three different spectral bands. The payload includes also a multispectral scanner subsystem and a data collection system which collects information from some 150 remote, unattended, instrumented ground platforms. Many government agencies use ERTS-1 data as integral parts of their ongoing programs. Through its EROS program, the Interior Department represents the largest single recipient and user agency of data obtained from NASA aircraft and spacecraft designed to gather repetitive information related to a wide variety of earth-science and natural-resources disciplines. Questions of environmental impact are considered together with applications in agriculture, forestry, marine resources, geography, and the survey of water resources.

Mercanti, E. P.↗

NASA NTRS1984

The NASA/JPL pilot ocean data system catalog

Data from various ground and satellite sensors collected and processed by various institutions cannot be used easily without a well planned method of determining their existence and location. The Global On-Line Data (GOLD) Catalog will provide a requestor with the ability to determine the existence of specific data holdings by specifying any combination of platform, measurement, location, or time. By this means, one can obtain details of data held at PODS and also at cooperating remote archives.

Johnson, J. A.↗

NASA NTRS1987

Impact of satellite-based data on FGGE general circulation statistics

The NASA Goddard Laboratory for Atmospheres (GLA) analysis/forecast system was run in two different parallel modes in order to evaluate the influence that data from satellites and other FGGE observation platforms can have on analyses of large scale circulation; in the first mode, data from all observation systems were used, while in the second only conventional upper air and surface reports were used. The GLA model was also integrated for the same period without insertion of any data; an independent objective analysis based only on rawinsonde and pilot balloon data is also performed. A small decrease in the vigor of the general circulation is noted to follow from the inclusion of satellite observations.

Salstein, David A.↗

NASA NTRS2000

BOREAS TE-12 SSA Leaf Water Potential Data

The Boreal Ecosystem-Atmospheric Study (BOREAS) TE-12 (Terrestrial Ecology) team collected water potential data in 1993 and 1994 from aspen, jack pine, and black spruce leaves/needles. Collections were made at the Southern Study Area Nipawin Fen Site (SSA FEN), Young Jack Pine (YJP), Young Aspen (YA), Old Aspen (OA), and Old Black Spruce (OBS) sites. Measurements were made using a pressure chamber on a platform in the field. The data are provided in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗

NASA NTRS1983

Current trends and research challenges in land remote sensing

The use of space technology to conduct repetitive global surveys of terrestrial surface conditions is reviewed. The state-of-the-art is determined by the measurement capabilities of orbital sensor systems, the maneuvering and data transmission capabilities of orbital platforms, and the sophistication of the user community. Introduction of the Landsat Thematic Mapper and SPOT sensor systems and operational use of the Space Shuttle are discussed. Research challenges of the 1980's are related to the removal of atmospheric and topographic effects in remotely sensed imagery, the extraction of information from high dimensionality data sets, and the ability to conduct meaningful ground truth surveys to support the analysis and interpretation of remotely sensed data.

Settle, M.↗

NASA NTRS1982

Attitude tracker

Line array sensors produce data which has no inherent geometrical continuity. Hence, any platform attitude variation will be evidenced as a distortion when the data lines are displayed in the normal Cartesian raster. Ancillary sensing is required to establish the platform attitude to allow geometric rectification. This is normally provided by inertial or star reference attitude sensors. However, in the absence of such sensors or if performance of them is degraded, the required attitude information is lost. A strawman sensor design is proposed which utilizes small image areas on the ground to provide a series of motion vectors with which the platform attitude can be tracked; this allows the distorted image received by the normal image line sensor to be rectified.

Billingsley, F. C.↗