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At least 1,063 records · Page 59

Cardinal: Seismic and Geoacoustic Array Processing

Data collected via seismic and infrasound array deployments are leveraged in the geosciences to detect and characterize a myriad of natural and anthropogenic sources. These deployments consist of numerous sensors placed in a predetermined configuration to amplify signal strength and improve the efficacy of array processing techniques used to measure signal directionality and waveform coherence. High‐fidelity feature extraction is often predicated on interstation distance as well as the frequency content and wavelength of an incident signal. Numerous array processing softwares analyze data in sequential frequency bands to obtain a more detailed characterization of a signal. However, current algorithms are limited in their ability to determine optimal array configuration for each band. We introduce an open‐source Python code, called Cardinal, to process seismic and infrasound array data in discretized time–frequency space with the option of applying an adaptive array design to determine optimal subarray configuration for each frequency band. To reduce computational time, the array processing step can be run in parallel using multithreading. Furthermore, the software has the capability to aggregate array processing results from different time–frequency pixels to produce separate sets of detections, or families, with added utility via the application of an adaptive semblance threshold, which aids in isolating signals‐of‐interest from coherent background noise. Upon appropriate configuration, Cardinal exhibits the potential to combine distinct seismic and infrasound phases into separate families.

Adaptive Array↗

Processing by data and program blocks

A processing system is presented that implements simultaneously the efficiency of the special-purpose processor and the total applicability of the general-purpose computer - characteristics commonly thought of as being mutually exclusive. This is achieved through specializing the machine by programming the hardware structure, rather than by adding software systems to it. Data are organized in circulating pages which form a multiplicity of local dynamic memories for each process. Programs are made up of modules, each describing a transient special-purpose machine. A characteristic of this approach is that the processes are data-driven, rather than program-driven. The programming language presents significant flexibility and efficiency in modeling certain classes of problems, and it may be of interest as an implementation model in a broader context. Applications to real-time processing of radar signals are reported. The relevance of characteristics of this system to problems in multiprogramming and multiprocessing systems is discussed.

Schaffner, M. R.↗

Appendix B: Principles of computer processing of LANDSAT data

Computer processing facilitates extraction of information from every pixel by executing a variety of functional operations, called processed algorithms, in general or specialized routines. The best results are obtained when data from more than one multispectral band are used together. Multivariate tatistical analysis, computer tape characteristics, processing modes, and a choice of systems (batch or interactive) are discussed. The major operations in computer processing elaborated include: preprocessing, enhancement, effects of rationing, and classification. Techniques for multisource data correlation are considered with emphasis on geobased systems.

Source record↗

Kepler Archive Manual

A description of Kepler, its design, performance and operational constraints may be found in the Kepler Instrument Handbook (KIH, Van Cleve Caldwell 2016). A description of Kepler calibration and data processing is described in the Kepler Data Processing Handbook (KDPH, Jenkins et al. 2016; Fanelli et al. 2011). Science users should also consult the special ApJ Letters devoted to early Kepler results and mission design (April 2010, ApJL, Vol. 713 L79-L207). Additional technical details regarding the data processing and data qualities can be found in the Kepler Data Characteristics Handbook (KDCH, Christiansen et al. 2013) and the Data Release Notes (DRN). This archive manual specifically documents the file formats, as they exist for the last data release of Kepler, Data Release 25(KSCI-19065-002). The earlier versions of the archive manual and data release notes act as documentation for the earlier versions of the data files.

Kepler↗

Eye/Brain/Task Testbed And Software

Eye/brain/task (EBT) testbed records electroencephalograms, movements of eyes, and structures of tasks to provide comprehensive data on neurophysiological experiments. Intended to serve continuing effort to develop means for interactions between human brain waves and computers. Software library associated with testbed provides capabilities to recall collected data, to process data on movements of eyes, to correlate eye-movement data with electroencephalographic data, and to present data graphically. Cognitive processes investigated in ways not previously possible.

Janiszewski, Thomas↗

Research In Optical Processing Of Data

Report describes current research in optical processing of data at NASA's Ames Research Center. Describes advanced optical feature extractor performing Fourier-Mellin transform to generate feature vector invariant under changes of scale and position and responds to rotation with simple translation. Potential advantages include high speed and low cost.

Ennis, David↗

Information expectations from Landsat-D

The first satellite of the Landsat-D Project is to be launched in the third quarter of 1982 with a second satellite to be prepared for launch 12 to 15 months later. Both spacecraft are to include the familiar Multispectral Scanner (MSS) and the advanced multispectral scanner called the Thematic Mapper (TM). The ground data processing system for the MSS data is to be ready to produce 200 scenes a day in 1982. The data processing systems for the TM are to be fully operational at the 50 to 100 scenes a day level in early 1985. The fabrication of the system components has proceeded well in recent months, and integration of the total system is under way. The procedures for processing the data and meeting specifications are nearly completed for the MSS and are outlined in detail for the TM. An outline of an investigation program stressing systems performance has been developed for the period 1982 to 1985.

Salomonson, V. V.↗

The Landsat thematic mapper World Data Base

A World Data Base of potential thematic mapper (TM) scenes was developed to aid in acquisition planning. The World Data Base contains geopolitical, geographic and economic regions along with a format that enables users to find the satellite day, sun angle and cloud cover probability for any month of the year. Scenes that have been acquired by TM and have an average cloud cover of 30 percent of less from July 1982 when TM was launched until the Landsat system was taken over by NOAA in September 1984 are also in the World Data Base. Processed data are referenced in maps and data bases at EROS Data Center; however, a large number of acquistions have never been processed and therefore are not accessible. The World Data Base enables the rapid location of scenes and areas with the least effort making it invaluable in TM scheduling. Users of TM data can use the World Data Base to determine if scenes of interest have been acquired, the acquisition date, and if scenes have been processed to computer-compatible tape (CCT). These uses of the World Data Base make it a valuable tool in the acquisition and location of TM scenes.

Ludwig, R. W.↗

Resource Prospector Instrumentation for Lunar Volatiles Prospecting, Sample Acquisition and Processing

Data gathered from lunar missions within the last two decades have significantly enhanced our understanding of the volatile resources available on the lunar surface, specifically focusing on the polar regions. Several orbiting missions such as Clementine and Lunar Prospector have suggested the presence of volatile ices and enhanced hydrogen concentrations in the permanently shadowed regions of the moon. The Lunar Crater Observation and Sensing Satellite (LCROSS) mission was the first to provide direct measurement of water ice in a permanently shadowed region. These missions with other orbiting assets have laid the groundwork for the next step in the exploration of the lunar surface; providing ground truth data of the volatiles by mapping the distribution and processing lunar regolith for resource extraction. This next step is the robotic mission Resource Prospector (RP). Resource Prospector is a lunar mission to investigate 'strategic knowledge gaps' (SKGs) for in-situ resource utilization (ISRU). The mission is proposed to land in the lunar south pole near a permanently shadowed crater. The landing site will be determined by the science team with input from broader international community as being near traversable landscape that has a high potential of containing elevated concentrations of volatiles such as water while maximizing mission duration. A rover will host the Regolith & Environment Science and Oxygen & Lunar Volatile Extraction (RESOLVE) payload for resource mapping and processing. The science instruments on the payload include a 1-meter drill, neutron spectrometer, a near infrared spectrometer, an operations camera, and a reactor with a gas chromatograph-mass spectrometer for volatile analysis. After the RP lander safely delivers the rover to the lunar surface, the science team will guide the rover team on the first traverse plan. The neutron spectrometer (NS) and near infrared (NIR) spectrometer instruments will be used as prospecting tools to guide the traverse path. The NS will map the water-equivalent hydrogen concentration as low as 0.5% by weight to an 80 centimeter depth as the rover traverses the lunar landscape. The NIR spectrometer will measure surficial H2O/OH as well as general mineralogy. When the prospecting instruments identify a potential volatile-rich area during the course of a traverse, the prospect is then mapped out and the most promising location identified. An augering drill capable of sampling to a depth of 100 centimeters will excavate regolith for analysis. A quick assay of the drill cuttings will be made using an operations camera and NIR spectrometer. With the water depth confirmed by this first auguring activity, a regolith sample may be extracted for processing. The drill will deliver the regolith sample to a crucible that will be sealed and heated. Evolved volatiles will be measured by a gas chromatograph-mass spectrometer and the water will be captured and photographed. RP is a solar powered mission, which given the polar location translates to a relatively short mission duration on the order of 4-15 days. This short mission duration drives the concept of operations, instrumentation, and data analysis towards critical real time analysis and decision support. Previous payload field tests have increased the fidelity of the hardware, software, and mission operations. Current activities include a mission level field test to optimize interfaces between the payload and rover as well as better understand the interaction of the science and rover teams during the mission timeline. This paper will include the current status of the science instruments on the payload as well as the integrated field test occurring in fall of 2015. The concept of operations will be discussed, including the real time science and engineering decision-making process based on the critical data from the instrumentation. The path to flight will be discussed with the approach to this ambitious low cost mission.

ISRU↗

Coherent optical processing of synthetic aperture radar data

Consideration is given to the data processing algorithm used in synthetic aperture radar (SAR) systems. Examples are presented of radar imagery obtained with the ERIM X-band SAR system and processed with a precision optical processor. An optical recording of the data is the input to the coherent optical processing channel. The encoding technique, spatial format, and quality of the stored data are discussed. Several optical processor configurations are outlined, noting particularly the tilted-plane system. A scanning photodetector serves to convert the optical processor output image data into an electronic signal stream. Solid-state two-dimensional photodetector arrays may provide this function at increased speeds and with greater accuracy.

Cindrich, I.↗

First Scientific Working Group Meeting of Airborne Doppler Lidar Wind Velocity Measurement Program

The purpose of the first scientific working group meeting was fourfold: (1) to identify flight test options for engineering verification of the MSFC Doppler Lidar; (2) to identify flight test options for gathering data for scientific/technology applications; (3) to identify additional support equipment needed on the CV 990 aircraft for the flight tests; and (4) to identify postflight data processing and data sets requirements. The working group identified approximately ten flight options for gathering data on atmospheric dynamics processes, including turbulence, valley breezes, and thunderstorm cloud anvil and cold air outflow dynamics. These test options will be used as a basis for planning the fiscal year 1981 tests of the Doppler Lidar system.

Kaufman, J. W.↗

Satellite radar altimetry over ice. Volume 1: Processing and corrections of Seasat data over Greenland

The data-processing methods and ice data products derived from Seasat radar altimeter measurements over the Greenland ice sheet and surrounding sea ice are documented. The corrections derived and applied to the Seasat radar altimeter data over ice are described in detail, including the editing and retracking algorithm to correct for height errors caused by lags in the automatic range tracking circuit. The methods for radial adjustment of the orbits and estimation of the slope-induced errors are given.

Zwally, H. Jay↗

UNH TDP - Voltsys Raw Data and Processing Scripts - Fall 2021

This submission contains raw Voltsys rectifier data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

UNH TDP - Load Cell Raw Data and Processing Scripts - Fall 2021

This submission contains raw Load Cell data and processing scripts associated with MHKDR submission 394 (UNH TDP - Concurrent Measurements of Inflow, Power Performance, and Loads for a Grid-Synchronized Vertical Axis Cross-Flow Turbine Operating in a Tidal Estuary, DOI: 10.15473/1973860) from the University of New Hampshire and Atlantic Marine Energy Center (AMEC) turbine deployment platform. The user is directed to the MHKDR submission 394 for relevant context and detail of this deployment; see link below. The 394_READ_ME file here provides the description from that submission for quick reference. The READ_ME file for this specific instrument from the 394 submission is also available here. This submission contains a zipped folder structure containing raw data in its original format and MATLAB (2019a) processing scripts used to process and manipulate the data into its final form. The final data products are submitted in the 394 submission.

16 TIDAL AND WAVE POWER↗

Canopy spectra, Feb2017, PA-SLZ: Panama

Canopy spectra of sunlit canopy of Guarea kunthiana, Brosimum utile, Terminalia amazonia (TERMAM), Vochysia ferruginea (VOCHFE), Miconia borealis (MICOBO) and Guatteria dumetorum (GUATDU) species from the Smithsonian Tropical Research Institute (STRI) canopy crane site in the San Lorenzo National Park, Republic of Panama (PA-SLZ: Bosque Protector San Lorenzo). Canopy spectra were measured at 1:20 – 2 pm on 22 February 2017, using a SVC spectroradiometer. This data package includes the raw SVC data (*.sig), processed data of individual spectra, and processed spectra averaged over the canopy of each of the six trees measured (*.csv). The package also includes photographs of the canopy spectral targets, metadata and the instrument manual. This data was collected as part of the 2017 Brookhaven National Laboratory – Smithsonian Tropical Research Institute leaf traits by age campaign.

54 ENVIRONMENTAL SCIENCES↗

Computer-generated maps of lunar composition from gamma-ray data

Processing of some of the gamma-ray data obtained by Apollo 15 and 16 has been accomplished by analyzing count rates in three energy bands. The count rate variations in the three energy bands are due in various degrees to thorium, uranium, potassium, iron and titanium. The mapping which results from the gamma-ray count rates has an effective resolution of about two degrees. Regions of high titanium content in certain maria, the low values of iron in a zone of the central equatorial highland and the relatively low value of iron near Archimedes are noted.

Arnold, J. R.↗

Atmosphere Explorer control system software (version 2.0)

The Atmosphere Explorer Control System (AECS) was developed to provide automatic computer control of the Atmosphere Explorer spacecraft and experiments. The software performs several vital functions, such as issuing commands to the spacecraft and experiments, receiving and processing telemetry data, and allowing for extensive data processing by experiment analysis programs. The AECS was written for a 48K XEROX Data System Sigma 5 computer, and coexists in core with the XDS Real-time Batch Monitor (RBM) executive system. RBM is a flexible operating system designed for a real-time foreground/background environment, and hence is ideally suited for this application. Existing capabilities of RBM have been used as much as possible by AECS to minimize programming redundancy. The most important functions of the AECS are to send commands to the spacecraft and experiments, and to receive, process, and display telemetry data.

Mocarsky, W.↗