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At least 37 records · Page 2

FERMI/GLAST Integrated Trending and Plotting System Release 5.0

An Integrated Trending and Plotting System (ITPS) is a trending, analysis, and plotting system used by space missions to determine performance and status of spacecraft and its instruments. ITPS supports several NASA mission operational control centers providing engineers, ground controllers, and scientists with access to the entire spacecraft telemetry data archive for the life of the mission, and includes a secure Web component for remote access. FERMI/GLAST ITPS Release 5.0 features include the option to display dates (yyyy/ddd) instead of orbit numbers along orbital Long-Term Trend (LTT) plot axis, the ability to save statistics from daily production plots as image files, and removal of redundant edit/create Input Definition File (IDF) screens. Other features are a fix to address invalid packet lengths, a change in naming convention of image files in order to use in script, the ability to save all ITPS plot images (from Windows or the Web) as GIF or PNG format, the ability to specify ymin and ymax on plots where previously only the desired range could be specified, Web interface capability to plot IDFs that contain out-oforder page and plot numbers, and a fix to change all default file names to show yyyydddhhmmss time stamps instead of hhmmssdddyyyy. A Web interface capability sorts files based on modification date (with newest one at top), and the statistics block can be displayed via a Web interface. Via the Web, users can graphically view the volume of telemetry data from each day contained in the ITPS archive in the Web digest. The ITPS could be also used in nonspace fields that need to plot data or trend data, including financial and banking systems, aviation and transportation systems, healthcare and educational systems, sales and marketing, and housing and construction.

Ritter, Sheila↗

Mapping wall-to-wall fractional cover of Arctic tundra plant functional types in Alaska using 20-m spatial resolution satellite imagery and harmonized plot observations

Estimates of fractional cover (fCover) across given land surfaces are used to assess, and often model, vegetation composition and diversity, which are crucial for understanding the health and functioning of terrestrial ecosystems. Remote sensing provides a useful means for scaling local, plot-measured fCover estimates to regional scales. Leveraging a recently synthesized and harmonized plot database, this study generated wall-to-wall maps of fCover for six Alaskan-Arctic plant functional types (PFT), including non-vascular plants, forbs, graminoids, and deciduous and evergreen shrubs, using 20-m satellite data (Sentinel-1, Sentinel-2, ArcticDEM) using a machine learning regression approach, specifically the random forest (RF) algorithm, which is well-suited for handling nonlinear relationships and high-dimensional satellite datasets. This study additionally addressed the spatio-temporal inconsistencies e.g., sampling scale, plot size, and collection year in plot measured fCover by adopting a multivariate outlier detection approach—Cook’s distance—to identify high-quality plots for model training and validation. Our approach achieves high accuracy (R 2 = 0.59–0.93, root mean squared errors = 0.02–0.10 for all PFTs) between plot-observed and satellite-derived fCover when using high-quality plot samples. The mapped fCover characterizes the spatial patterns of different PFTs across the tundra biome at a 20-m resolution, providing key information needed for improved representation of Arctic tundra vegetation in terrestrial biosphere models to better understand climate-vegetation feedback across the Arctic tundra.

Arctic tundra↗

SPRUCE Vertical Profiles of CO2 and H2O Concentrations in Air in Experimental Plots Beginning in 2015

This dataset provides a record of hourly average CO2 and H2O concentrations in air at 4 vertical locations (0.5, 1, 2, and 4 m above ground level (agl)) on the central tower location for each of 13 SPRUCE experimental plots. Ten plots have enclosures (plots 4, 6, 8, 10, 11, 13, 16, 17, 19, and 20) and three plots (5, 7 and 21) are ambients without enclosures. Data are included for measurement periods beginning in 2015 and extend throughout the whole ecosystem warming (WEW) manipulations for the SPRUCE Project (Hanson et al. 2016, 2017). In August 2015, WEW was initiated at 5 warming levels (+0, +2. +4.5, +6.75 and +9 °C) with 2 plots per warming level. DPH measurements were underway before the initiation of WEW heating treatments and both are expected to operate through 2025. Elevated CO2 treatments were initiated within 5 experimental plots (Plots 4, 10, 11, 16 and 19) in June of 2016. All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗

A simplified modal plotting technique for the representation of complex structural models

A plotting method has been developed that has proven to be useful in rapidly defining the mode shapes of a complex spacecraft. The reduction of the complex model to a simple stick plot is accomplished by augmenting the existing NASTRAN plot package with constrained plot elements. Both the existing NASTRAN modal plot package and the stick plots of a representative mode are presented for comparison. The NASTRAN plot package provides the capability of generating modal deformations (mode shapes) resulting from real eigenvalue analysis. These modal deformations of the structural model may be displayed in the deformed shape either alone or superimposed on the undeformed shape. Another available method of displaying the modal deformations is by means of displacement vectors at the grid points

Hanlein, S. L.↗

A fast hidden line algorithm for plotting finite element models

Effective plotting of finite element models requires the use of fast hidden line plot techniques that provide interactive response. A high speed hidden line technique was developed to facilitate the plotting of NASTRAN finite element models. Based on testing using 14 different models, the new hidden line algorithm (JONES-D) appears to be very fast: its speed equals that for normal (all lines visible) plotting and when compared to other existing methods it appears to be substantially faster. It also appears to be very reliable: no plot errors were observed using the new method to plot NASTRAN models. The new algorithm was made part of the NPLOT NASTRAN plot package and was used by structural analysts for normal production tasks.

Jones, G. K.↗

A laser plotting system for VLSI chip layouts

One of the most time consuming facets of custom Very Large Scale Integration (VLSI) design is obtaining hardcopy plots of the mask geometries of cells and chips. The traditional method of generating these plots is to use a multicolor pen plotter. Pen plotters are inherently slow and the plotting speed increases linearly with the number of edges that must be plotted. A moderate custom chip design at the Jet Propulsion Laboratory (JPL) now consists of more than 200,000 such edges and can take as much as eight hours to plot using a pen plotter. Software is described that was written at JPL to produce similar plots using a laser printer. It is shown that, for rather small layouts, the laser printer can provide nearly instantaneous turnaround. For moderate to large chip designs, the laser printer provides a factor of five or more improvement is speed over pen plotting.

Deutsch, L. J.↗

User Guide for the Plotting Software for the Los Alamos National Laboratory Nuclear Weapons Analysis Tools Version 2.0

The Los Alamos National Laboratory Plotting Software for the Nuclear Weapons Analysis Tools is a Java™ application based upon the open source library JFreeChart. The software provides a capability for plotting data on graphs with a rich variety of display options while allowing the viewer interaction via graph manipulation and scaling to best view the data. The graph types include XY plots, Date XY plots, Bar plots and Histogram plots.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SPRUCE Terrestrial Laser Scanning of Experimental Plots, Beginning in 2015

This data set comprises terrestrial laser scanning (TLS) point clouds from the SPRUCE experimental plots located in the S1-Bog of the Marcell Experimental Forest (MEF) near Grand Rapids, Minnesota. In 2015 and 2020 the 12 experimental SPRUCE plots were scanned near peak foliage ("summer”). In 2016-2019 and 2021-2023 the 12 plots were scanned prior to green up ("spring”) and once near peak foliage (Table 1). Additional data will be added through summer 2025. A RIEGL VZ-1000 unit was used to collect all scans. Four TLS scans in each plot were registered to produce a single point cloud per plot using RiSCAN PRO v2.3 software. Up to six additional scans were registered to account for data occlusion when necessary. Point clouds are saved in LAS (*.las) 1.2 format. Point clouds were geo-registered to surveyed plot locations. There are 192 *.las files provided with this dataset.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Microtopography of Experimental Plots Derived from Terrestrial Laser Scans Beginning in 2016

This dataset consists of maps and summaries of very high resolution (1 cm2) spatial data derived from terrestrial laser scans (TLS) characterizing the microtopography (hummocks and hollows) in 12 SPRUCE experimental plots from 2016-2018. The SPRUCE experiment is located in the S1-Bog of the Marcell Experimental Forest (MEF) near Grand Rapids, Minnesota. Additional data will be added through Summer 2021.The TLS sampling plan follows the SPRUCE experimental design, with scanning of the ten enclosed treatment plots with five temperature treatments (0, 2.25, 4.5, 6.75, and 9°C) with and without elevated CO2 (~900 ppm) and the two monitored ambient plots without enclosures. Enclosures are octagonal in shape and are 12.8 m in diameter (114.8 m2 in area), 8 m tall, with a belowground corral that penetrates through the peat to glacial material below, which averages 2.5 m deep across the site. In the spring of each year, four TLS scans were taken per plot/enclosure and registered together to produce a single point cloud for each plot (Figure 2A). Digital surface models (DSMs) were generated from the point clouds and clipped to the inside boundary of the boardwalk in each plot resulting in an approximately 9 x 9 m study area. . All other characterization data types were derived from plot DSMs (elevation), including: slope (Figure 3), concavity (Figure 4), index used for microform classification (Hollow Index) (Figure 6), and microforms (Figure 2C; hummocks and hollows) classified using three methodologies.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Plot-Level Water Table Data Assessments for Absolute Elevations and Height with Respect to Mean Hollows Beginning in 2015

This data set provides a record of the half-hourly automated water table depth data collected for 12 SPRUCE plots (4, 6, 7, 8, 10, 11, 13, 14, 16, 17, 19, 20, and 21) beginning during deep peat heating (DPH) in 2015 and continuing throughout the whole ecosystem warming (WEW) manipulations for the SPRUCE Project (Hanson et al. 2017). The data currently cover 2015-05-12 through 2024-12-31 and will be updated periodically throughout the duration of the SPRUCE project. Also provided are daily plot normalized data for water table depths with respect to mean hollow locations within each plot. The hollow referenced data provide the basis for the intercomparison of peat saturation or aeration across treatment plots. A limited data set for manual water table observations made periodically from 2015-2022 are also provided as a reference to the plot center automated observations. In August 2015, WEW was initiated at 5 warming levels (+0, +2. +4.5, +6.75 and +9 °C) with 2 plots per warming level. DPH measurements were underway before the initiation of WEW heating treatments and both are expected to operate through 2025. Elevated CO2 treatments were added in June 2016 (Enclosures 4, 10, 11, 16 and 19). All measurements were made at the 8.1-ha S1 bog forest site in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). This dataset contains three data files in comma separated (*.csv) format.

54 ENVIRONMENTAL SCIENCES↗

NEMAR plotting computer program

A FORTRAN coded computer program which generates CalComp plots of trajectory parameters is examined. The trajectory parameters are calculated and placed on a data file by the Near Earth Mission Analysis Routine computer program. The plot program accesses the data file and generates the plots as defined by inputs to the plot program. Program theory, user instructions, output definitions, subroutine descriptions and detailed FORTRAN coding information are included. Although this plot program utilizes a random access data file, a data file of the same type and formatted in 102 numbers per record could be generated by any computer program and used by this plot program.

Myler, T. R.↗

Faster simulation plots

Most simulation plots are heavily oversampled. Ignoring unnecessary data points dramatically reduces plot time with imperceptible effect on quality. The technique is suited to most plot devices. The departments laser printer's speed was tripled for large simulation plots by data thinning. This reduced printer delays without the expense of a faster laser printer. Surpisingly, it saved computer time as well. All plot data are now thinned, including PostScript and terminal plots. The problem, solution, and conclusions are described. The thinning algorithm is described and performance studies are presented. To obtain FORTRAN 77 or C source listings, mail a SASE to the author.

Fowell, Richard A.↗

Improved NASTRAN plotting

The new 1991 COSMIC/NASTRAN version, compatible with the older versions, tries to remove some old constraints and make it easier to extract information from the plot file. It also includes some useful improvements and new enhancements. New features available in the 1991 version are described. They include a new PLT1 tape with simplified ASCII plot commands and short records, combined hidden and shrunk plot, an x-y-z coordinate system on all structural plots, element offset plot, improved character size control, improved FIND and NOFIND logic, a new NASPLOT post-prosessor to perform screen plotting or generate PostScript files, and a BASIC/NASTPLOT program for PC.

Chan, Gordon C.↗

Analysis of a Split-Plot Experimental Design Applied to a Low-Speed Wind Tunnel Investigation

A procedure to analyze a split-plot experimental design featuring two input factors, two levels of randomization, and two error structures in a low-speed wind tunnel investigation of a small-scale model of a fighter airplane configuration is described in this report. Standard commercially-available statistical software was used to analyze the test results obtained in a randomization-restricted environment often encountered in wind tunnel testing. The input factors were differential horizontal stabilizer incidence and the angle of attack. The response variables were the aerodynamic coefficients of lift, drag, and pitching moment. Using split-plot terminology, the whole plot, or difficult-to-change, factor was the differential horizontal stabilizer incidence, and the subplot, or easy-to-change, factor was the angle of attack. The whole plot and subplot factors were both tested at three levels. Degrees of freedom for the whole plot error were provided by replication in the form of three blocks, or replicates, which were intended to simulate three consecutive days of wind tunnel facility operation. The analysis was conducted in three stages, which yielded the estimated mean squares, multiple regression function coefficients, and corresponding tests of significance for all individual terms at the whole plot and subplot levels for the three aerodynamic response variables. The estimated regression functions included main effects and two-factor interaction for the lift coefficient, main effects, two-factor interaction, and quadratic effects for the drag coefficient, and only main effects for the pitching moment coefficient.

Erickson, Gary E.↗

NGEE Arctic Plant Traits: Vegetation Plot Locations, Ecotypes, and Photos, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, 2016

This dataset provides field site documentation for related datasets including GPS waypoints for intensive plots, reference points, vegetation plots, and soil temperature/moisture monitoring stations that were established in July 2016 at the Kougarok hill slope located at Kougarok Road, Mile Marker 64. At all intensive plots and reference points, photographs of the surrounding area were also taken using an Olympus Stylus TG-3 digital camera. Photographs were July 2nd through July 7th looking in each of the four cardinal directions. GPS waypoints were taken using a Garmin eTrek 10 handheld GPS and World Geodetic System 1984 (WGS-84). The error associated with the Garmin GPS coordinates was 9 foot or approximately 3 m. When marking waypoints, users waited until the instrument reached this error level before recording. Coordinate units are decimal degrees. This dataset is comprised of one comma-separated (*.csv) file containing GPS waypoints locating intensive plots, reference points, soil temperature/moisture monitoring stations, and vegetation plots. The dataset also contains one folder of photographs (*.jpg) taken at intensive stations, one folder of photographs (*.jpg) taken at reference points, and one User file (*.pdf). The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Tree damage and mortality measurements across seven ForestGEO plots in the tropics between Oct 2016 and Mar 2023

Annual records (raw data) on tree survival and structural completeness of 36,524 trees (2,467 species) collected across 29 censuses in seven tropical forests distributed across the Neotropics (Amacayacu, Colombia; Barro Colorado Island (BCI), Panamá; Yasuní, Ecuador) and Asia (Fushan, Taiwan; Huai Kha Khaeng (HKK), Thailand; Khao Chong (KC), Thailand; Pasoh, Malaysia). This dataset was used to compare aboveground biomass loss via damage to living trees relative to total AGB loss (mortality + damage). Variable definitions: site: name of the ForestGEO plot stemID.ams: Unique ID for the stem in the annual mortality surveys (ams) treeID.ams: Unique ID for the tree in the ams date.full.census: date of the previous full census of the plot, format: YYYY-MM-DD dbh.full.census: diameter at the breast height (dbh in mm) measured during the previous full census of the plot home: height of measurement of dbh (in m) meanWD: species-level wood density (g cm-3) date.ams: date of the ams, format: YYYY-MM-DD status: survival status of the tree (A: alive; D: dead; NF: not found; "?": unknown) H_considering_damage: living length of the main axis in meters; provides an estimate of the amount of remaining living tissues along the main axis of the stem (e.g., the height of breakage or the height discounting wood decay) b: the remaining proportion of branch volume within the living length (b∈[0,1]). weights.ind: frequency of the [size class x species] bins within the forest plot relative to their frequency in the sample. Necessary to extrapolate estimates to the whole plot.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Hyperspectral Remote Sensing of Vegetation Communities in SPRUCE Experimental Plots, 2016

This dataset consists of reflectance observations from hyperspectral remote sensing of the vegetation communities from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experimental site within the Marcell Experimental Forest in northern Minnesota, USA. Observations were collected in SPRUCE experimental study plots located in the S1-Bog. Community vegetation plots in ten chambered treatment plots (6, 19, 11, 20, 4, 13, 8, 16, 10, 17) and 3 unchambered ambient plots (7, 14, 21) were scanned. Spectral data were collected on 22 September 2016 (2016-09-22) under clear sky conditions beginning at 1:00 p.m. local time (Central Standard Time). Although it was past peak growing season, senescence had only just begun at the site, and experimentally warmed plots were still near peak growing conditions. Data collection was performed using a PP Systems UniSpec-DC spectroradiometer that detected incoming and reflected solar radiation in 3–4 nm bandwidths between 310 and 1100 nm. The fiber optic cable on the Unispec was fitted with a field of view (FOV) restrictor that limited the FOV to approximately 15°. The instrument foreoptic was leveled at 1 m above the ground capturing an area of approximately 35 cm in diameter, or 0.1 m2. White reference scans were performed between each treatment. Bands at the beginning and end of the spectrum were eliminated due to noise, resulting in a reported data range of 400-1000 nm. These data can help characterize boreal peatland plant composition and species diversity and their responses to elevated temperatures and carbon dioxide concentrations. These observations were used in analyses in McPartland et al (2019). This dataset contains 4 data files in comma-separate values (*.csv) format. Additional metadata are provided: four data dictionaries and a file-level metadata file in comma-separate values (.csv) format and a user guide in PDF (*.pdf) format.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Experimental Plot Top View Aerial Images beginning June 2019

This data set provides a record of the aerial images of the SPRUCE experimental plots obtained periodically using an unmanned aerial vehicle (UAV) with attached camera from 2019-05-05- to 2022-08-25. New images of the plots will be added periodically. The initial RGB images may be used for studies of greenness and snow coverage and compared with ground-based measurements and chamber-based tree and shrub Phenocam images (e.g. Schädel et al., 2022). Also included are NDVI (Normalized Difference Vegetation Index) images showing calculated difference between visible near-infrared (NIR) light reflectance from vegetation, as well as infrared (IR) and multispectral images. Files are presented in JPEG (*.jpg) or PDF (*.pdf) format inside of 28 compressed (*.zip) files. Images were collected for the 10 plots with enclosures, the 7 unchambered plots, and the environmental monitoring instrument cluster area. Images are slightly off-plot center at 12 to 15 meters above ground level or approximately 2 meters above the top of an experimental chamber.

54 ENVIRONMENTAL SCIENCES↗