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At least 307 records · Page 17

Planning applications in image analysis

We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

Boddy, Mark↗

Pilot land data system

During the fall of 1983, the Information Systems Office of NASA's Office of Space Science and Applications assembled a Working Group to develop initial plans for a Pilot Land Data System (PLDS). Workshops coordinated planning and concept development activities between land-related and computer science disciplines, and examined land research requirements, information science technology requirements, PLDS architecture, and methodologies for system evaluation. The PLDS will be a limited-scale distributed information system to explore scientific, technical and management approaches to satisfy land science research needs. PLDS will pave the way for a Land Data System to improve data access, processing, transfer and analysis, fostering an environment in which land science information synthesis can occur on a scale not previously possible owing to limits to data assembly and access and efficiency of processing.

Cressy, P. J.↗

Matrix evaluation of science objectives

The most fundamental objective of all robotic planetary spacecraft is to return science data. To accomplish this, a spacecraft is fabricated and built, software is planned and coded, and a ground system is designed and implemented. However, the quantitative analysis required to determine how the collection of science data drives ground system capabilities has received very little attention. This paper defines a process by which science objectives can be quantitatively evaluated. By applying it to the Cassini Mission to Saturn, this paper further illustrates the power of this technique. The results show which science objectives drive specific ground system capabilities. In addition, this process can assist system engineers and scientists in the selection of the science payload during pre-project mission planning; ground system designers during ground system development and implementation; and operations personnel during mission operations.

Wessen, Randii R.↗

Geographic science: Executive summary

The role that TM and MSS data play in the analysis of spatial patterns for land use/land cover, geomorphology studies, and the development of cartographic products is discussed. Tables listing geographic science data gaps, mission data requirements, and possible future remote sensing missions are included.

Source record↗

Earth science information: Planning for the integration and use of global change information

Activities and accomplishments of the first six months of the Consortium for International Earth Science Information Network (CIESIN's) 1992 technical program have focused on four main missions: (1) the development and implementation of plans for initiation of the Socioeconomic Data and Applications Center (SEDAC) as part of the EOSDIS Program; (2) the pursuit and development of a broad-based global change information cooperative by providing systems analysis and integration between natural science and social science data bases held by numerous federal agencies and other sources; (3) the fostering of scientific research into the human dimensions of global change and providing integration between natural science and social science data and information; and (4) the serving of CIESIN as a gateway for global change data and information distribution through development of the Global Change Research Information Office and other comprehensive knowledge sharing systems.

Lousma, Jack R.↗

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

Tilmes, Curt↗

Ancillary Data Services of NASA's Planetary Data System

JPL's Navigation and Ancillary Information Facility (NAIF) has primary responsibility for design and implementation of the SPICE ancillary information system, supporting a wide range of space science mission design, observation planning and data analysis functions/activities. NAIF also serves as the geometry and ancillary data node of the Planetary Data System (PDS). As part of the PDS, NAIF archives SPICE and other ancillary data produced by flight projects. NAIF then distributes these data, and associated data access software and high-level tools, to researchers funded by NASA's Office of Space Science. Support for a broader user community is also offered to the extent resources permit. This paper describes the SPICE system and customer support offered by NAIF.

Navigation and Ancillary Information Facility NAIF↗

The GLAS physical inversion method for analysis of TIROS N data

The Goddard Laboratory for Atmospheric Sciences approach to temperature sounding from satellite observations is fundamentally different from that of NESS in that heavy reliance is placed on the ability to model accurately the instrumental response to atmospheric and surface conditions, while no use is made of statistical relationships between satellite observations and atmospheric temperature profiles. The method involves starting with a guess set of atmospheric and surface conditions from which expected brightness temperatures for the satellite observations are computed. Then, iterative relaxation of atmospheric and surface conditions is performed according to the difference between observed and computed brightness temperatures until sufficient agreement is reached. In the absence of sufficient agreement, no retrieval is produced for that location.

Susskind, J.↗

Catalog of solar wind events identified from observations by ISTP spacecraft

The ISTP Science Planning and Operations Facility (SPOF), in collaboration with ISTP investigators, is developing a catalog of solar wind events and features. The catalog is primarily based on plasma and magnetic field observations from the WIND and IMP-8 spacecraft. Interplanetary events that may trigger magnetospheric activity are included as well as features of interest for using the solar wind as a plasma laboratory. Catalog coverage begins on September 8, 1992, the start of ISTP science data collection. The catalog is based on Key Parameter data sets (preliminary summary data at approximately 1 min time resolution produced quickly for survey purposes) and as such has limited citability in formal scientific work. Its primary intent is to serve as a reference for identifying candidate periods for further study, such as may be the focus of coordinated data analysis efforts during ISTP and/or IACG Science Campaigns. To facilitate access by members of the ISTP and wider space physics communities, the catalog will be available on the World Wide Web. The contents of the catalog will be described, and samples of catalog information will be presented.

Peredo, M.↗

Earth science research

The analysis of ground-truth data from the boreal forest plots in the Superior National Forest, Minnesota, was completed. Development of statistical methods was completed for dimension analysis (equations to estimate the biomass of trees from measurements of diameter and height). The dimension-analysis equations were applied to the data obtained from ground-truth plots, to estimate the biomass. Classification and analyses of remote sensing images of the Superior National Forest were done as a test of the technique to determine forest biomass and ecological state by remote sensing. Data was archived on diskette and tape and transferred to UCSB to be used in subsequent research.

Botkin, Daniel B.↗

Plasma electron analysis: Voyager plasma science experiment

The Plasma Science Experiment (PLS) on the Voyager spacecraft provide data on the plasma ions and electrons in the interplanetary medium and the magnetospheres of the giant planets Jupiter and Saturn. A description of the analysis used to obtain electron parameters (density, temperature, etc.) from the plasma science experiment PLS electron measurements which cover the energy range from 10 eV to 5950 eV is presented. The electron sensor (D cup) and its transmission characteristics are described. A derivation of the fundamental analytical expression of the reduced distribution function F(e) is given. The electron distribution function F(e), used in the moment integrations, can be derived from F(e). Positive ions produce a correction current (ion feedthrough) to the measured electron current, which can be important to the measurements of the suprathermal electron component. In the case of Saturn, this correction current, which can either add to or subtract from the measured electron current, is less than 20% of the measured signal at all times. Comments about the corrections introduced by spacecraft charging to the Saturn encounter data, which can be important in regions of high density and shadow when the spacecraft can become negatively charged are introduced.

Sittler, E. C., Jr.↗

Global 3D Data Visualization and Analysis Platform with Advanced Machine Learning Capabilities in Support of Lunar Exploration

Introduction: The science goals for NASA’s Artemis program include: a) Understanding the character and origin of lunar polar volatiles, b) Conducting experimental science in the lunar environment and c) Investigating and mitigating exploration risks. The permanently shadowed regions (PSRs) on the Lunar south pole are expected to host large quantities of water-ice and volatiles that are important for sustainable Lunar exploration. There are several missions such as onboard Korea Pathfinder Lunar Orbiter (KPLO: Korean name Danuri) with onboard ShadowCam camera, Astrobotic Peregrine Mission One [4], and other efforts underway to obtain high resolution topographic, minerals, volatiles and other information on the moon. We envision a need in immediate future for platforms to integrate these data sets, provide rendering and visualization capabilities in the context of a 3D Lunar globe for easier information access and analysis. NASA's Celestial Mapping System (CMS) is developed to address the need for 3D tools for planetary science investigations, mission planning, in-situ operations, in a 3D-first design constructed around a unified view of a planetary globe. At present CMS provides many critical functionalities that include: 1) equipment planning and optimized placement on Lunar surface 2) line-of-sight (LOS) analysis 3) powerful measurement tools based on 3D terrain with realistic 3D models to represent rovers, astronauts and equipment 4) visualization of derived mapping products (e.g. resource maps), and 5) a data engine for hosting new observations that are not available in other contemporary lunar data tools. Planetary Data Ingestion: CMS can consume and analyze data from locally hosted and external third party sources. It is compatible with Open Geospatial Consortium (OGC) data and file standards and currently integrates datasets from the Astrogeology Science Center of USGS. This includes global and local data acquired from NASA (LRO, Clementine, Lunar Orbiter) and JAXA (SELENE/Kaguya), with capability of integrating more datasets. In addition, users can specify other WMS-hosted data endpoints, which CMS can then query and stream data from automatically. To set-up an automated process for ingestion and accurate rendering, visualization and analysis of external 3rd party planetary datasets within CMS, we initiated the process of ingesting unique dataset of super-enhanced images of the permanently shadowed regions (PSRs) at the lunar poles which were produced by the Hyper-effective nOise Removal U-net Software (HORUS) tool. This tool was developed to enhance the extremely low-light images of the interior of PSRs and provide the ability to see within these regions at and discern surface features (i.e. boulders and craters) down to 3 meters in size. We focused on the Nobile region on the Lunar south pole, selected site for VIPER mission and stitched several images to create a high-resolution map within one of the PSR of Nobile crater. Figure 1 shows the dark PSR zone form the original NAC layer of LRO as the base layer (left image) and the illuminated areas within that crater (center) which was created by ingesting and merging several of HORUS generated images. At present we employ a semi-automated process to ensure spatial accuracy and merger of several overlapping zones. However, we are in the process of completely automating this process by employing AI based techniques that would rank, sort, and stack the images based on their information density. The georectification of the images would employ selected features. Analysis on Ingested Planetary Datasets: Once an external planetary data-set is successfully ingested, georectified and merged seamlessly as a data-layer; CMS’ numerous analysis tools can be used on this data. A Line of Sight (LOS) tool has been developed for CMS which analyzes terrain profiles and obstructions to determine visibility for remote observers. Figure 1 (right image) shows the viewshed analysis on the same PSR in the Nobile region. The yellow pin shows the observer location outside the PSR. The yellow area shows the visible part of PSR. The obstructed area with no visibility for the observer is shown in red. The Measurements tool allows the user to take area and distance measurements of features on the terrain using various shapes. Measurement type can be specified in a number of ways: Line, Path, Polygon, Circle, Ellipse, Square, Rectangle or Freehand. Once the shape is specified, elevation information can then be extracted along each of these shapes. Figure 2 (left) shows the measurements performed on a crater n illuminated PSR in Nobile region. The equipment placement tool allows the user to place a 3D equipment model at a desired location and analyze its coverage area. The equipment placement tool is coupled with LOS to determine the coverage. Figure 2 (right) shows an equipment placed on the Lunar terrain and it’s coverage area. The red rays are blocked sight lines and the green rays are non-obstructed sight lines with the cyan lines showing the point of intersection with the terrain. More details are provided in the video demonstrations in Reference 5. Overcoming Polar Distortions: 3D geospatial applications exhibit significant distortions in polar imagery due to several reasons: 1) distortions in the source imagery, 2) incompatible tessellation algorithms at the poles, and 3) map projections. We are leveraging new tessellation algorithms and reprojecting data using projections that are better suited for Lunar poles. The goal is to seamlessly switch to polar projections while maintaining 3D view and navigation.

Maps↗

Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data

The accurate calculation of phonons and vibrational spectra remains a significant challenge, requiring highly precise evaluations of interatomic forces. Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. Emerging universal machine learning interatomic potentials (uMLIPs) offer a transformative alternative by employing pre-trained neural network surrogates to predict interatomic forces directly from atomic coordinates. This approach dramatically reduces computation time and minimizes the need for technical knowledge. In this paper, we produce a phonon database comprising nearly 5000 inorganic crystals to benchmark the performance of several leading uMLIPs. We further assess these models in real-world applications by using them to analyze experimental inelastic neutron scattering data collected on a variety of materials. Through detailed comparisons, we identify the strengths and limitations of these uMLIPs, providing insights into their accuracy and suitability for fast calculations of phonons and related properties, as well as the potential for real-time interpretation of neutron scattering spectra. Our findings highlight how the rapid advancement of AI in science is revolutionizing experimental research and data analysis.

inelastic neutron scattering↗

Onboard Data Analysis for the Planetary Instrument for X-Ray Lithography

Imaging spectrometers are invaluable instruments for robotic science exploration, enabling quantitative maps of physical and chemical properties at high spatial resolution. This is particularly valuable in remote missions to other planetary bodies like Mars. The PIXL instrument on the Mars 2020 rover will deploy an arm-mounted X-Ray fluorescence spectrometer to map chemical composition at sub-millimeter scales. Its high resolution places dramatic new demands on instrument placement accuracy and measurement time. We address these challenges using novel on board data analysis strategies inspired by FRC science autonomy research.

Thompson, David R.↗

Data Integrity Challenges in NASA Giovanni

The Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) is an online tool developed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers (DAACs) to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several well-known NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). There are twenty-two plots provided by Giovanni that can be used to analyze, compare, and explore Earth data across disciplines. Results can be shared with colleagues and downloaded for further analysis. Giovanni has helped publish over 3000 referral papers over the years. As open science policies roll in, data integrity has become a major challenge for Giovanni and other tools. For integrity, both data and workflows must be transparent. FAIR-compliant data, including input, intermediate, and result products, as well as their associated statistics, metadata, and information, are needed. The NASA Data Product Development Guide for Data Producers provides a key resource on how to develop FAIR-compliant data products. Data quality information is also needed from data producers and analysis services like Giovanni. The workflow part is quite challenging and requires workflow management improvements, such as recording workflows and making them available to users. In this presentation, we will discuss the data integrity challenges in Giovanni.

data analysis, visualization↗

Astrophysics science operations in the Great Observatories era

Plans for Astrophysics science operations during the decade of the nineties are described from the point of view of a scientist who wishes to make a space-borne astronomical observation or to use archival astronomical data. 'Science Operations' include the following: proposal preparation, observation planning and execution, data collection, data processing and analysis, and dissemination of results. For each of these areas of science operations, we derive technology requirements for the next ten to twenty years. The scientist will be able to use a variety of services and infrastructure, including the 'Astrophysics Data System.' The current status and plans for these science operations services are described.

Riegler, Guenter R.↗

Sizing the science data processing requirements for EOS

The methodology used in the compilation and synthesis of baseline science requirements associated with the 30 + EOS (Earth Observing System) instruments and over 2,400 EOS data products (both output and required input) proposed by EOS investigators is discussed. A brief background on EOS and the EOS Data and Information System (EOSDIS) is presented, and the approach is outlined in terms of a multilayer model. The methodology used to compile, synthesize, and tabulate requirements within the model is described. The principal benefit of this approach is the reduction of effort needed to update the analysis and maintain the accuracy of the science data processing requirements in response to changes in EOS platforms, instruments, data products, processing center allocations, or other model input parameters. The spreadsheets used in the model provide a compact representation, thereby facilitating review and presentation of the information content.

Wharton, Stephen W.↗