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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

EdgeAI: Machine learning via direct attached accelerator for streaming data processing at high shot rate x-ray free-electron lasers

We present a case for low batch-size inference with the potential for adaptive training of a lean encoder model. We do so in the context of a paradigmatic example of machine learning as applied in data acquisition at high data velocity scientific user facilities such as the Linac Coherent Light Source-II x-ray Free-Electron Laser. We discuss how a low-latency inference model operating at the data acquisition edge can capitalize on the naturally stochastic nature of such sources. We simulate the method of attosecond angular streaking to produce representative results whereby simulated input data reproduce high-resolution ground truth probability distributions. By minimizing the mean-squared error between the decoded output of the latent representation and the ground truth distributions, we ensure that the encoding layers and resulting latent representation maintains full fidelity for any downstream task, be it classification or regression. We present throughput results for data-parallel inference of various batch sizes, some with throughput exceeding 100 k images per second. We also show in situ training below 10 s per epoch for the full encoder–decoder model as would be relevant for streaming and adaptive real-time data production at our nation’s scientific light sources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Airborne profiling of ice thickness using a short pulse radar

The acquisition and interpretation of ice thickness data from a mobile platform has for some time been a goal of the remote sensing community. Such data, once obtainable, is of value in monitoring the changes in ice thickness over large areas, and in mapping the potential hazards to traffic in shipping lanes. Measurements made from a helicopter-borne ice thickness profiler of ice in Lake Superior, Lake St. Clair and the St. Clair river as part of NASA's program to develop an ice information system are described. The profiler described is a high resolution, non-imaging, short pulse radar, operating at a carrier frequency of 2.7 GHz. The system can resolve reflective surfaces separated by as little as 10 cm. and permits measurement of the distance between resolvable surfaces with an accuracy of about 1 cm. Data samples are given for measurements both in a static (helicopter hovering), and a traverse mode. Ground truth measurements taken by an ice auger team traveling with the helicopter are compared with the remotely sensed data and the accuracy of the profiler is discussed based on these measurements.

Vickers, R. S.↗
NASA NTRS1988

Full-disk magnetograms obtained with a Na magneto-optical filter at the Mount Wilson Observatory

The first full-disk magnetograms to be obtained with the Na magneto-optical filter (MOF) which is located at the 60 foot solar tower of the Mount Wilson Observatory are presented. This MOF was employed as a longitudinal magnetograph on June 18, 19, and July 1, 1987. On those three days the MOF was combined with a large format (1024 x 1024 pixel) virtual phase change coupled device camera and a high-speed data acquisition system. The combined system was used to record both line-of-sight magnetograms and Dopplergrams which covered the entire visible solar hemisphere. The pixel size of these magnetograms and Dopplergrams was 2.3 arcseconds. On each of the three days a time series of nine pairs of magnetograms and Dopplergrams was obtained at the rate of one pair every two minutes. On the same three day longitudinal magnetograms have one arcsecond pixels were obtained with the vacuum telescope at Kitt Peak. The MOF and vacuum tower magnetograms were compared at both the JPL Multi-Mission Image Processing Laboratory and at USC and have found the two sets of images to be well correlated both in spatial distribution and strength of the measured magnetic field. The simultaneously-obtained MOF Dopplergrams to remove the crosstalk which was present between the Doppler and Zeeman shifts of the NaD lines from the magnetograms from all three days and will also describe recent improvements to the system which allowed the obtaining of full-disk magnetograms as rapidly as one every 25 seconds.

Rhodes, Edward J., Jr.↗
NASA NTRS2017

Landsat-8 Operational Land Imager On-Orbit Radiometric Calibration

The Operational Land Imager (OLI), the VIS/NIR/SWIR sensor on the Landsat-8 has been successfully acquiring Earth Imagery for more than four years. The OLI incorporates two on-board radiometric calibration systems, one diffuser based and one lamp based, each with multiple sources. For each system one source is treated as primary and used frequently and the other source(s) are used less frequently to assist in tracking any degradation in the primary sources. In addition, via a spacecraft maneuver, the OLI instrument views the moon once a lunar cycle (approx. 29 days). The integrated lunar irradiances from these acquisitions are compared to the output of a lunar irradiance model. The results from all these techniques, combined with cross calibrations with other sensors and ground based vicarious measurements are used to monitor the OLI's stability and correct for any changes observed. To date, the various techniques have other detected significant changes in the shortest wavelength OLI band centered at 443 nm and these are currently being adjusted in the operational processing.

radiometric calibratio↗
NASA NTRS2002

Low Resolution Picture Transmission (LRPT) Demonstration System

Low-Resolution Picture Transmission (LRPT) is a proposed standard for direct broadcast transmission of satellite weather images. This standard is a joint effort by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) and the National Oceanic Atmospheric Administration (NOAA). As a digital transmission scheme, its purpose is to replace the current analog Automatic Picture Transmission (APT) system for use in the Meteorological Operational (METOP) satellites. Goddard Space Flight Center has been tasked to build an LRPT Demonstration System (LDS). It's main objective is to develop or demonstrate the feasibility of a low-cost receiver utilizing a Personal Computer (PC) as the primary processing component and determine the performance of the protocol in the simulated Radio Frequency (RF) environment. The approach would consist of two phases. In the phase 1, a Commercial-off-the-Shelf (COTS) Modulator-Demodulator (MODEM) board that would perform RF demodulation would be purchased allowing the Central Processing Unit (CPU) to perform the Consultative Committee for Space Data Systems (CCSDS) protocol processing. Also since the weather images are compressed the PC would perform the decompression. Phase 1 was successfully demonstrated on December 1997. Phase 2 consists of developing a high-fidelity receiver, transmitter and environment simulator. Its goal is to find out how the METOP Specification performs in a simulated noise environment in a cost-effective receiver. The approach would be to produce a receiver using as much software as possible to perform front-end processing to take advantage of the latest high-speed PCs. Thus the COTS MODEM used in Phase 1 is performing RF demodulation along with data acquisition providing data to the receiving software. Also, environment simulator is produced using the noise patterns generated by Institute for Telecommunications Sciences (ITS) from their noise environment study.

Fong, Wai↗
NASA NTRS2023

New York Ecological Conservation: Evaluating Agricultural Conservation Easement Impact Using Earth Observations to Examine Avoided Soil Carbon Loss to Development

Farmland provides ecosystems and communities with services ranging from habitat conservation to food security. As total U.S. farmland continues to decline, agricultural lands near urban areas are especially vulnerable. Our project partners—Finger Lakes Land Trust, Genesee Land Trust, and Saratoga Preserving Land and Nature (PLAN)—can use study results to better profile farmland vulnerability, issuing conservation easements to protect maximum acreage in Saratoga County and the Finger Lakes Region of New York. Multiple existing studies effectively use remote sensing imagery to analyze historical land cover and forecast future change. This study examined soil carbon stocks and land cover change to estimate avoided soil carbon loss. We also predicted farmland vulnerability. We completed these analyses using European Space Agency (ESA) and NASA Earth observations that include Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2, Sentinel-2 Multispectral Instrument (MSI), and Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) for nighttime lights data that aided in the land change model analysis. We determined that the conversion of agriculture to development from 1990 to 2022 occurred at rates of 0.91% (Finger Lakes) and 7% (Saratoga). Urban development is predicted to increase surrounding urban centers through 2030 and 2050. We also estimate that between 26.5 and 348,101 kilotons (Finger Lakes) and 3.7 and 58,006 kilotons (Saratoga) of soil carbon losses have been avoided through agricultural easements. Findings from this study will support our partners in determining agricultural conservation easement benefits and prioritizing the acquisition of future easement sites.

Agriculture↗
NASA NTRS1988

Some comments on particle image displacement velocimetry

Laser speckle velocimetry (LSV) or particle image displacement velocimetry, is introduced. This technique provides the simultaneous visualization of the two-dimensional streamline pattern in unsteady flows as well as the quantification of the velocity field over an entire plane. The advantage of this technique is that the velocity field can be measured over an entire plane of the flow field simultaneously, with accuracy and spatial resolution. From this the instantaneous vorticity field can be easily obtained. This constitutes a great asset for the study of a variety of flows that evolve stochastically in both space and time. The basic concept of LSV; methods of data acquisition and reduction, examples of its use, and parameters that affect its utilization are described.

Lourenco, L. M.↗
NASA NTRS2005

Experiments on Supervised Learning Algorithms for Text Categorization

Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

Namburu, Setu Madhavi↗
NASA NTRS2000

A New Look at Aerosol Optical Models in the MODIS/AERONET ERA

The MODerate resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra satellite will permit the first time operational satellite retrievals of atmospheric aerosols over land. The retrieval uses dynamic models of aerosol optical properties developed from ground-based sun/sky radiometer data at selected specific locations. Three recent developments argue for a reevaluation of these optical models. (1) The expansion of the AERONET sun/sky radiometer network into new geographical regions that possibly features aerosols with different properties. (2) The development of the Dubovik sky radiance inversion that now offers a more comprehensive retrieval of aerosol optical properties. (3) The launch of the Terra satellite and acquisition of MODIS data that will reveal exactly how well the models perform.

Remer, Lorraine↗
NASA NTRS2005

Calibration Refinements in Support of MISR

The Multi-angle Imaging SpectroRadiometer (MISR) is one of five instruments on-board the EOSI Terra spacecraft, and has collected science data since March 2000. A multi-angle capability is provided by ninecameras, which view up to 70' forward and aft of the spacecraft track and enable unique geophysical retrievals. Throughout its mission, a calibration team has made periodic refinements to the process used to calibrate MISR. These have resulted in improved absolute, and band and camera-relative calibrations, as well as in derived geophysical data products. Data reprocessing is on-going, such that these refinements also improve previous data acquisitions. The calibration process is believed to be mature at this time, with no other changes anticipated. Bimonthly deployments of the on-board-calibrator continue to monitor instrument response degradations, and provide correction coefficients needed to maintain the accuracy of the radiance products.

refinements↗
NASA NTRS2009

Monitoring Disasters by Use of Instrumented Robotic Aircraft

Efforts are under way to develop data-acquisition, data-processing, and data-communication systems for monitoring disasters over large geographic areas by use of uninhabited aerial systems (UAS) robotic aircraft that are typically piloted by remote control. As integral parts of advanced, comprehensive disaster- management programs, these systems would provide (1) real-time data that would be used to coordinate responses to current disasters and (2) recorded data that would be used to model disasters for the purpose of mitigating the effects of future disasters and planning responses to them. The basic idea is to equip UAS with sensors (e.g., conventional video cameras and/or multispectral imaging instruments) and to fly them over disaster areas, where they could transmit data by radio to command centers. Transmission could occur along direct line-of-sight paths and/or along over-the-horizon paths by relay via spacecraft in orbit around the Earth. The initial focus is on demonstrating systems for monitoring wildfires; other disasters to which these developments are expected to be applicable include floods, hurricanes, tornadoes, earthquakes, volcanic eruptions, leaks of toxic chemicals, and military attacks. The figure depicts a typical system for monitoring a wildfire. In this case, instruments aboard a UAS would generate calibrated thermal-infrared digital image data of terrain affected by a wildfire. The data would be sent by radio via satellite to a data-archive server and image-processing computers. In the image-processing computers, the data would be rapidly geo-rectified for processing by one or more of a large variety of geographic-information- system (GIS) and/or image-analysis software packages. After processing by this software, the data would be both stored in the archive and distributed through standard Internet connections to a disaster-mitigation center, an investigator, and/or command center at the scene of the fire. Ground assets (in this case, firefighters and/or firefighting equipment) would also be monitored in real time by use of Global Positioning System (GPS) units and radio communication links between the assets and the UAS. In this scenario, the UAS would serve as a data-relay station in the sky, sending packets of information concerning the locations of assets to the image-processing computer, wherein this information would be incorporated into the geo-rectified images and maps. Hence, the images and maps would enable command-center personnel to monitor locations of assets in real time and in relation to locations affected by the disaster. Optionally, in case of a disaster that disrupted communications, the UAS could be used as an airborne communication relay station to partly restore communications to the affected area. A prototype of a system of this type was demonstrated in a project denoted the First Response Experiment (Project FiRE). In this project, a controlled outdoor fire was observed by use of a thermal multispectral scanning imager on a UAS that delivered image data to a ground station via a satellite uplink/ downlink telemetry system. At the ground station, the image data were geo-rectified in nearly real time for distribution via the Internet to firefighting managers. Project FiRE was deemed a success in demonstrating several advances essential to the eventual success of the continuing development effort.

Wegener, Steven S.↗
NASA NTRS2000

BOREAS Landsat MSS Imagery: Digital Counts

The Boreal Ecosystem-Atmospheric Study (BOREAS) Staff Science Satellite Data Acquisition Program focused on providing the research teams with the remotely sensed satellite data products they needed to compare and spatially extend point results. The Earth Resources Technology Satellite (ERTS) Program launched the first of a series of satellites (ERTS-1) in 1972. Part of the NASA Earth Resources Survey Program, the ERTS Program and the ERTS satellites were later renamed Landsat to better represent the civil satellite program's prime emphasis on remote sensing of land resources. Landsat satellites 1 through 5 carry the Multispectral Scanner (MSS) sensor. Canada for Remote Sensing (CCRS) and BOREAS personnel gathered a set of MSS images of the BOREAS region from Landsat satellites 1, 2, 4, and 5 covering the dates of 21 Aug 1972 to 05 Sep 1988. The data are provided in binary image format files of various formats. The Landsat MSS imagery is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗
NASA NTRS2004

The Isolated Synthetic Jet in Crossflow: A Benchmark for Flow Control Simulation

An overview of the data acquisition, reduction, and uncertainty of experimental measurements of the flowfield created by the interaction of an isolated synthetic jet and a turbulent boundary layer is presented. The experimental measurements were undertaken to serve as the second of three computational fluid dynamics validation databases for Active Flow Control. The validation databases were presented at the NASA Langley Research Center Workshop on CFD Validation of Synthetic Jets and Turbulent Separation Control in March, 2004. Detailed measurements were made to document the boundary conditions for the flow and also for the phase-averaged flowfield itself. Three component Laser-Doppler Velocimetry, 2-D Particle Image Velocimetry, and Stereo Particle Image Velocimetry were utilized to document the phase averaged velocity field and the turbulent stresses.

Schaeffler, Norman W.↗
NASA NTRS1992

Using AVIRIS images to measure temporal trends in abundance of photosynthetic and nonphotosynthetic canopy components

The Jasper Ridge Biological Preserve, Stanford, California is a good example of hardwood rangeland ecosystems in California. Structurally, it is composed of a mosaic of serpentine grasslands, oak savannah, coastal chaparral, and mixed evergreen woodland, representing a broad cross-section of physiognomic classes. The Mediterranean climate produces an extended seasonal drought lasting throughout most of the growing season and has significant impact on the expression of divergent phenological patterns related to contrasting ecological strategies of these taxa. The region is well understood biologically due to the rich history of ecological research at the site. Thus, community characteristics, physiological characteristics, phenology, and temporal dynamics are reasonably well understood for many of the dominant species. Because of its proximity to NASA Ames Research Center, it has been subject to a large number of aircraft data acquisitions over many years. A more complete examination of this database would provide an opportunity to test current remote sensing hypotheses for measurement and detection of ecological attributes, particularly those involving canopy chemistry and physiology. Better definition of ecological rules might permit development of remotely sensed surrogate variables for biological properties that cannot be directly measured or measured with sufficient accuracy.

Ustin, Susan L.↗
DOE OSTI2025

SANE: strategic autonomous non-smooth exploration for multiple optima discovery in multi-modal and non-differentiable black-box functions

Both computational and experimental material discovery bring forth the challenge of exploring multidimensional and multimodal parameter spaces, such as phase diagrams of Hamiltonians with multiple interactions, composition spaces of combinatorial libraries, material structure image spaces, and molecular embedding spaces. Often these systems are black-boxes and time-consuming to evaluate, which resulted in strong interest towards active learning methods such as Bayesian optimization (BO). However, these systems are often noisy which make the black box function severely multi-modal and non-differentiable, where a vanilla BO can get overly focused near a single or faux optimum, deviating from the broader goal of scientific discovery. To address these limitations, here we developed Strategic Autonomous Non-Smooth Exploration (SANE) to facilitate an intelligent Bayesian optimized navigation with a proposed cost-driven probabilistic acquisition function to find multiple global and local optimal regions, avoiding the tendency to becoming trapped in a single optimum. To distinguish between a true and false optimal region due to noisy experimental measurements, a human (domain) knowledge driven dynamic surrogate gate is integrated with SANE. We implemented the gate-SANE into pre-acquired piezoresponse spectroscopy data of a ferroelectric combinatorial library with high noise levels in specific regions, and piezoresponse force microscopy (PFM) hyperspectral data. SANE demonstrated better performance than classical BO to facilitate the exploration of multiple optimal regions and thereby prioritized learning with higher coverage of scientific values in autonomous experiments. Our work showcases the potential application of this method to real-world experiments, where such combined strategic and human intervening approaches can be critical to unlocking new discoveries in autonomous research.

Biswas, Arpan [University of Tennessee, Knoxville,↗
NASA NTRS1995

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗
NASA NTRS2006

The Isolated Synthetic Jet in Crossflow: A Benchmark for Flow Control Simulation

An overview of the data acquisition, reduction, and uncertainty of experimental measurements made of the flowfield created by the interaction of an isolated synthetic jet and a turbulent boundary layer is presented. The experimental measurements were undertaken to serve as the second of three computational fluid dynamics validation databases for Active Flow Control. The validation databases were presented at the NASA Langley Research Center Workshop on CFD Validation of Synthetic Jets and Turbulent Separation Control in March, 2004. Detailed measurements were made to document the boundary conditions for the flow and also for the phase-averaged flowfield itself. Three component Laser-Doppler Velocimetry, 2-D Particle Image Velocimetry, and Stereo Particle Image Velocimetry were utilized to document the phase-averaged velocity field and the turbulent stresses.

Schaeffler, Norman W.↗
NASA NTRS2021

Landsat Derived Bathymetry of Lakes on the Arctic Coastal Plan of Northern Alaska

The Pleistocene sand sea on the Arctic Coastal Plain (ACP) of northern Alaska is underlain by anancient sand dune field, a geological feature that affects regional lake characteristics. Many of these lakes, whichcover approximately 20 % of the Pleistocene sand sea, are relatively deep (up to 25 m). In addition to the nat-ural importance of ACP sand sea lakes for water storage, energy balance, and ecological habitat, the need forwinter water for industrial development and exploration activities makes lakes in this region a valuable resource.However, ACP sand sea lakes have received little prior study. Here, we collect in situ bathymetric data to test12 model variants for predicting sand sea lake depth based on analysis of Landsat-8 Operational Land Imager(OLI) images. Lake depth gradients were measured at 17 lakes in midsummer 2017 using a Humminbird 798ciHD SI Combo automatic sonar system. The field-measured data points were compared to red–green–blue (RGB)bands of a Landsat-8 OLI image acquired on 8 August 2016 to select and calibrate the most accurate spectral-depth model for each study lake and map bathymetry. Exponential functions using a simple band ratio (withbands selected based on lake turbidity and bed substrate) yielded the most successful model variants. For eachlake, the most accurate model explained 81.8 % of the variation in depth, on average. Modeled lake bathymetrieswere integrated with remotely sensed lake surface area to quantify lake water storage volumes, which rangedfrom 1.056×10−3to 57.416×10−3km3. Due to variations in depth maxima, substrate, and turbidity betweenlakes, a regional model is currently infeasible, rendering necessary the acquisition of additional in situ datawith which to develop a regional model solution. Estimating lake water volumes using remote sensing will fa-cilitate better management of expanding development activities and serve as a baseline by which to evaluatefuture responses to ongoing and rapid climate change in the Arctic. All sonar depth data and modeled lakebathymetry rasters can be freely accessed at https://doi.org/10.18739/A2SN01440 (Simpson and Arp, 2018) andhttps://doi.org/10.18739/A2HT2GC6G (Simpson, 2019), respectively.

Claire E Simpson↗