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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A satellite data processing and analysis software system for earth's atmosphere and surface research

The OASIS (Oceanic and Atmospheric Satellite Imaging System) is a satellite data processing and analysis software system being developed by the California Space Institute (Cal Space) for support of interdisciplinary and integrated earth sciences research programs. The system's software applications are integrated under a common executive, NASA's Transportable Application Executive (TAE). In this paper, TAE and the system software and hardware are described, and specific techniques used for ingesting, processing, analyzing, and graphically displaying data from many of the sensors presently being flown are presented. Scientific uses of these capabilities that are, or will shortly be, running under TAE at Cal Space are described.

Dealy, B.↗
NASA NTRS1992

HIRIS, the instrument and its science

The High Resolution Imaging Spectrometer (HIRIS) is a facility instrument slated for flight on the second EOS series AM platforms. HIRIS is designed to acquire 24 km wide, 30 m pixel images in 192 spectral bands simultaneously in the 0.4-2.45 micron wavelength region. With pointing mirrors it can sample any place on Earth, except the poles, every 2 days. HIRIS operates at the intermediate scale between the human and the global and therefore links studies of Earth surface processes to global monitoring carried out by lower resolution instruments. So far, over 50 science data products from HIRIS images have been identified in the fields of atmospheric gases, clouds, snow and ice, water, vegetation, and rocks and soils. The key attribute of imaging spectrometry that makes it possible to derive quantitative information from the data is the large number of contiguous, spectral bands. Therefore, spectrum-matching techniques can be applied. Such techniques are not possible with present-day, multispectral scanner data.

Goetz, Alexander F. H.↗
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
NASA NTRS1995

Geophysical phenomena classification by artificial neural networks

Space science information systems involve accessing vast data bases. There is a need for an automatic process by which properties of the whole data set can be assimilated and presented to the user. Where data are in the form of spectrograms, phenomena can be detected by pattern recognition techniques. Presented are the first results obtained by applying unsupervised Artificial Neural Networks (ANN's) to the classification of magnetospheric wave spectra. The networks used here were a simple unsupervised Hamming network run on a PC and a more sophisticated CALM network run on a Sparc workstation. The ANN's were compared in their geophysical data recognition performance. CALM networks offer such qualities as fast learning, superiority in generalizing, the ability to continuously adapt to changes in the pattern set, and the possibility to modularize the network to allow the inter-relation between phenomena and data sets. This work is the first step toward an information system interface being developed at Sussex, the Whole Information System Expert (WISE). Phenomena in the data are automatically identified and provided to the user in the form of a data occurrence morphology, the Whole Information System Data Occurrence Morphology (WISDOM), along with relationships to other parameters and phenomena.

Gough, M. P.↗
NASA NTRS2002

Advanced Thin Ionization Calorimeter (ATIC) Update

The Advanced Thin Ionization Calorimeter (ATIC) experiment is designed to measure the composition and energy spectra of Z = 1 to 28 cosmic rays over the energy range of approximately 10 GeV - 100 TeV. ATIC is comprised of an eight-layer, 18 radiation length deep Bismuth Germanate (BGO) calorimeter, downstream of a 0.75 nuclear interaction length graphite target and an approximately 1 sq m finely segmented silicon charge detector. Interleaved with the graphite layers are three scintillator strip hodoscopes for pre-triggering and tracking. ATIC flew for the first time on a Long Duration Balloon (LDB) launched from McMurdo, Antarctica in January 2001. During its 16-day flight ATIC collected more than 30 million science events, along with housekeeping, calibration, and rate data. This presentation will describe the ATIC data processing, including calibration and efficiency corrections, and show results from analysis of this dataset. The next launch is planned for December 2002.

Ahn, H. S.↗
NASA NTRS1998

High Performance Parallel Architectures

Traditional remote sensing instruments are multispectral, where observations are collected at a few different spectral bands. Recently, many hyperspectral instruments, that can collect observations at hundreds of bands, have been operational. Furthermore, there have been ongoing research efforts on ultraspectral instruments that can produce observations at thousands of spectral bands. While these remote sensing technology developments hold great promise for new findings in the area of Earth and space science, they present many challenges. These include the need for faster processing of such increased data volumes, and methods for data reduction. Dimension Reduction is a spectral transformation, aimed at concentrating the vital information and discarding redundant data. One such transformation, which is widely used in remote sensing, is the Principal Components Analysis (PCA). This report summarizes our progress on the development of a parallel PCA and its implementation on two Beowulf cluster configuration; one with fast Ethernet switch and the other with a Myrinet interconnection. Details of the implementation and performance results, for typical sets of multispectral and hyperspectral NASA remote sensing data, are presented and analyzed based on the algorithm requirements and the underlying machine configuration. It will be shown that the PCA application is quite challenging and hard to scale on Ethernet-based clusters. However, the measurements also show that a high- performance interconnection network, such as Myrinet, better matches the high communication demand of PCA and can lead to a more efficient PCA execution.

El-Ghazawi, Tarek↗
NASA NTRS2006

The STEREO Mission: A New Approach to Space Weather Research

With the launch of the twin STEREO spacecraft in July 2006, a new capability will exist for both real-time space weather predictions and for advances in space weather research. Whereas previous spacecraft monitors of the sun such as ACE and SOH0 have been essentially on the sun-Earth line, the STEREO spacecraft will be in 1 AU orbits around the sun on either side of Earth and will be viewing the solar activity from distinctly different vantage points. As seen from the sun, the two spacecraft will separate at a rate of 45 degrees per year, with Earth bisecting the angle. The instrument complement on the two spacecraft will consist of a package of optical instruments capable of imaging the sun in the visible and ultraviolet from essentially the surface to 1 AU and beyond, a radio burst receiver capable of tracking solar eruptive events from an altitude of 2-3 Rs to 1 AU, and a comprehensive set of fields and particles instruments capable of measuring in situ solar events such as interplanetary magnetic clouds. In addition to normal daily recorded data transmissions, each spacecraft is equipped with a real-time beacon that will provide 1 to 5 minute snapshots or averages of the data from the various instruments. This beacon data will be received by NOAA and NASA tracking stations and then relayed to the STEREO Science Center located at Goddard Space Flight Center in Maryland where the data will be processed and made available within a goal of 5 minutes of receipt on the ground. With STEREO's instrumentation and unique view geometry, we believe considerable improvement can be made in space weather prediction capability as well as improved understanding of the three dimensional structure of solar transient events.

Kaiser, michael L.↗
NASA NTRS2006

Biology-inspired Architecture for Situation Management

Situation Management is a rapidly developing science combining new techniques for data collection with advanced methods of data fusion to facilitate the process leading to correct decisions prescribing action. Current research focuses on reducing increasing amounts of diverse data to knowledge used by decision makers and on reducing time between observations, decisions and actions. No new technology is more promising for increasing the diversity and fidelity of observations than sensor networks. However, current research on sensor networks concentrates on a centralized network architecture. We believe this trend will not realize the full potential of situation management. We propose a new architecture modeled after biological ecosystems where motes are autonomous and intelligent, yet cooperate with local neighborhoods. Providing a layered approach, they sense and act independently when possible, and cooperate with neighborhoods when necessary. The combination of their local actions results in global effects. While situation management research is currently dominated by military applications, advances envisioned for industrial and business applications have similar requirements. NASA has requirements for intelligent and autonomous systems in future missions that can benefit from advances in situation management. We describe requirements for the Integrated Vehicle Health Management program where our biology-inspired architecture provides a layered approach and decisions can be made at the proper level to improve safety, reduce costs, and improve efficiency in making diagnostic and prognostic assessments of the structural integrity, aerodynamic characteristics, and operation of aircraft.

Jones, Kennie H.↗
NASA NTRS2007

Simple, Script-Based Science Processing Archive

The Simple, Scalable, Script-based Science Processing (S4P) Archive (S4PA) is a disk-based archival system for remote sensing data. It is based on the data-driven framework of S4P and is used for data transfer, data preprocessing, metadata generation, data archive, and data distribution. New data are automatically detected by the system. S4P provides services such as data access control, data subscription, metadata publication, data replication, and data recovery. It comprises scripts that control the data flow. The system detects the availability of data on an FTP (file transfer protocol) server, initiates data transfer, preprocesses data if necessary, and archives it on readily available disk drives with FTP and HTTP (Hypertext Transfer Protocol) access, allowing instantaneous data access. There are options for plug-ins for data preprocessing before storage. Publication of metadata to external applications such as the Earth Observing System Clearinghouse (ECHO) is also supported. S4PA includes a graphical user interface for monitoring the system operation and a tool for deploying the system. To ensure reliability, S4P continuously checks stored data for integrity, Further reliability is provided by tape backups of disks made once a disk partition is full and closed. The system is designed for low maintenance, requiring minimal operator oversight.

Lynnes, Christopher↗
NASA NTRS2012

The Algorithm Theoretical Basis Document for Level 1A Processing

The first process of the Geoscience Laser Altimeter System (GLAS) Science Algorithm Software converts the Level 0 data into the Level 1A Data Products. The Level 1A Data Products are the time ordered instrument data converted from counts to engineering units. This document defines the equations that convert the raw instrument data into engineering units. Required scale factors, bias values, and coefficients are defined in this document. Additionally, required quality assurance and browse products are defined in this document.

Jester, Peggy L.↗
NASA NTRSDate not supplied

NASA's Earthdata Forum: Bringing the Science Community Together

The Earthdata Forum is an actively maintained and operational user forum for all participating NASA EOSDIS Distributed Active Archive Centers (DAACs) and GCMD. The Forum serves as a cross-DAAC platform from which user communities can obtain authoritative information relating to NASA Earth Science. The Atmospheric Science Data Center (ASDC) DAAC takes on the role of both Project Manager and Hosting Organization. As Project Manager, the ASDC leads and facilitates the project's efforts. The Forum launched February 2020 with five participating DAACs: Atmospheric Science Data Center (ASDC), Crustal Dynamics Data Information System (CDDIS), Goddard Earth Science Data and Information Services Center (GES DISC), Global Hydrology Resource Center (GHRC), and Land Processes DAAC (LP DAAC). Since February 2020, the of Level 1 and Atmosphere Archive and Distribution System DAAC (LAADS), the Ocean Biology DAAC (OBDAAC) and Global Change Master Directory (GCMD) have also joined the Forum. The Forum assumes both a proactive and reactive approach to NASA products scientific queries, allowing the scientific community to ask questions about NASA's products, tools, and services and receive announcements and news regarding products, new data releases, and such. In this presentation, we will describe the Earthdata Forum approach to support the scientific community in detail and discuss the successes and challenges of this approach.

Ingrid Garcia-Solera↗
NASA NTRS2016

Euclid Near Infrared Spectro Photometer instrument concept and first test results obtained for different breadboards models at the end of phase C

The Euclid mission objective is to understand why the expansion of the Universe is accelerating through by mapping the geometry of the dark Universe by investigating the distance-redshift relationship and tracing the evolution of cosmic structures. The Euclid project is part of ESA's Cosmic Vision program with its launch planned for 2020 (ref [1]). The NISP (Near Infrared Spectrometer and Photometer) is one of the two Euclid instruments and is operating in the near-IR spectral region (900- 2000nm) as a photometer and spectrometer. The instrument is composed of: - a cold (135K) optomechanical subsystem consisting of a Silicon carbide structure, an optical assembly (corrector and camera lens), a filter wheel mechanism, a grism wheel mechanism, a calibration unit and a thermal control system - a detection subsystem based on a mosaic of 16 HAWAII2RG cooled to 95K with their front-end readout electronic cooled to 140K, integrated on a mechanical focal plane structure made with molybdenum and aluminum. The detection subsystem is mounted on the optomechanical subsystem structure - a warm electronic subsystem (280K) composed of a data processing / detector control unit and of an instrument control unit that interfaces with the spacecraft via a 1553 bus for command and control and via Spacewire links for science data This presentation describes the architecture of the instrument at the end of the phase C (Detailed Design Review), the expected performance, the technological key challenges and preliminary test results obtained for different NISP subsystem breadboards and for the NISP Structural and Thermal model (STM).

Maciaszek, Thierry↗
NASA NTRSDate not supplied

Swift Mission Gyro Patch and Re-Calibration Without A Calibration Campaign

The Swift spacecraft has three Two-Axis-Rate-Assemblies (TARAs) (designated as TARA 1, TARA 2, and TARA 3, and generically referred to as gyros) which until March of 2024 were all used in rate estimation as an operational workaround (dubbed “corrector-gyro”) of a software defect discovered in 2007. TARA 1 performance degraded throughout 2023 and 2024, making it an unreliable rate source. It was determined that shifting TARA 1 to be the corrector-gyro and using mainly TARAs 2 and 3, with the existing flight software (FSW) defect, would not meet performance requirements for science operations. Rather the FSW was patched to remove the defect found in 2007. This patch was delivered by the vendor in 2009, but was not fully tested or installed at that time. A decision was made in 2024 to install the patch despite limited simulation and testing capabilities. The problem facing the team was to come up with a set of alignment parameters that would work with the new patch, using data from the spacecraft operating normally in the old configuration. Calibration activities would have been possible in either the old or new FSW configuration, but were ultimately deemed unnecessary, saving staff time and pre-serving time on the spacecraft for science data collection. This paper describes the old and new FSW configurations related to gyro processing and alignment, and how the raw gyro and star tracker data from normal operation were used with a multidimensional unconstrained nonlinear minimization in MATLAB (Nelder-Mead1) to produce a fully calibrated set of gyro alignment parameters compatible with the patched FSW. Flight data is presented showing that not only did the process work, it improved performance significantly, rivaling the best slew performance of the mission to date.

MATLAB↗
NASA NTRS2017

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing; Pattern Recognition↗
NASA NTRS2018

Planetary Crater Detection and Registration Using Marked Point Processes, Multiple Birth and Death Algorithms, and Region-Based Analysis

Because of the large variety of sensors and spacecraft collecting data, planetary science needs to integrate various multi-sensor and multi-temporal images. These multiple data represent a precious asset, as they allow the study of targets spectral responses and of changes in the surface structure; because of their variety, they also require accurate and robust registration. A new crater detection algorithm, used to extract features that will be integrated in an image registration framework, is presented. A marked point process-based method has been developed to model the spatial distribution of elliptical objects (i.e. the craters) and a birth-death Markov chain Monte Carlo method, coupled with a region-based scheme aiming at computational efficiency, is used to find the optimal configuration fitting the image. The extracted features are exploited, together with a newly defined fitness function based on a modified Hausdorff distance, by an image registration algorithm whose architecture has been designed to minimize the computational time.

Image Processing:Pattern Recognition↗
NASA NTRS2006

Rapid, Repeat-sample Monitoring of Crustal Deformations and Environmental Phenomena with the Uninhabited Aerial Vehicle Synthetic Aperture Radar

The Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) is a precision repeat-pass Interferometric Synthetic Aperture Radar (InSAR) mission being developed by the Jet Propulsion Laboratory and the Dryden Flight Research Center in support of NASA s Science Mission Directorate. UAVSAR's unique ability to fly a repeatable flight path, along with an electronically steerable array, allows interferometric data to be obtained with accuracies measured in millimeters. Deploying the radar on an airborne platform will also allow for radar images to be collected and compared with images from the same area taken hours or even years later - providing for long-term trending and near real-time notification of changes and deformations. UAVSAR s data processing algorithms will provide for near-real time data reduction providing disaster planning and response teams with highly accurate data to aid in the prediction of, and response to, natural phenomena. UAVSAR data can be applied to increasing our understanding of the processes behind solid earth, cryosphere, carbon cycle and other areas of interest in earth science. Technologies developed for UAVSAR may also be applicable to a future earth-orbiting InSAR mission and possibly for missions to the Moon or Mars. The UAVSAR is expected to fly on a Gulfstream III aircraft this winter, followed by a flight test program lasting until the second half of 2007. Following radar calibration and data reduction activities, the platform will be ready for science users in the summer of 2008.

Smith, Robert C.↗
NASA NTRSDate not supplied

Language Model For Earth Science: Exploring Potential Downstream Applications As Well As Current Challenges

The use of deep learning techniques to build transformer language models such as SciBERT and GPT3 have transformed the natural language technology (NLT) landscape. These new NLTs are being used in speech to text and vice versa, auto-mated text classification, sentiment analysis, topic modeling, text summarization, and cognitive assistants. While Earth science has no shortage of unstructured data such as journal and conference papers, little efforts have focused on harnessing NLTs for knowledge extraction and supporting the scientific process. This paper surveys the use of language models in different science. BERT-E, a new Earth science-specific language model, is presented. BERT-E is generated using a transfer learning solution. A language model that has already been trained for general Science (SciBERT) is fine-tuned using abstracts and full text extracted from various Earth science-related articles. A downstream keywords classification application is used for evaluation, and the use of BERT-E shows improved performance. The need to develop a robust set of benchmarks in evaluating the language model such as BERT-E is discussed. Finally, example applications are presented to inspire additional ideas for applications using domain-specific language models.

R Ramachandran↗