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106 results for “map projections”
Mapped Trees in CRUI Land Use Project at Harvard Forest 1996-2006
Numerous variables related to land use disturbance and recovery processes influence forest composition, structure, and growth. We measured forest communities in six sites that were formerly plowed, pastured, or continuously forested woodlots in Prospect Hill to test predictions about species composition, stand structure, and productivity in response to agricultural land use legacies. A permanent 30 x 50 m plot gridded in 5 x 5 m sub-plots was established in each of the 6 sites. All trees at least 2.5 cm DBH (diameter at breast height, 1.3 m) were mapped visually in the field, marked with an aluminum tag, and their DBH recorded in summer 1996. Individual boles of multi-stemmed trees were measured separately and a composite single DBH was calculated. Standing dead trees were also mapped and their DBH recorded as well. The 1996 data were used to determine above ground woody biomass using allometric equations for individual trees. The permanent plots were re-surveyed ten years later in fall 2006. The status of each tree mapped in 1996 was recorded (alive, dead standing, dead fallen, forked) and DBH’s were re-measured. Additional trees that grew across the 2.5 cm DBH threshold during the ten-year period were mapped and their DBH’s measured. Composite diameters and above ground woody biomass were determined for forked trees as in 1996. The 2006 re-measurements were used to analyze changes in species composition, stand structure (density, diameter distribution), and mortality patterns among species and size classes, and to calculate net changes in above ground woody biomass across the ten-year period.
New maps of global geologic provinces and tectonic plates: global tectonics data and QGIS project file
<p>The global tectonics data compilation is a set of raster and vector data that are useful for investigating tectonics past and present. The datasets are useful on their own or can be used in GIS software, which includes the QGIS project file for convenience. The datasets include our new models for tectonic plate boundaries and deformation zones, geologic provinces and orogens. Additional datasets include earthquake and volcano locations, geochronology, topography, magnetics, gravity, and seismic velocity.</p> <p>The global tectonics collection is suitable for research and educational purposes.</p>
Supplemental catalogs for "The Sloan Digital Sky Survey Reverberation Mapping Project: Sample Characterization"
<p>We have compiled additional properties for the SDSS-RM sample in several ancillary catalogs. Below are the notes on these supplemental catalogs. There are .readme files for each additional catalog. We also include the quality assurance plots for the global spectral fits.</p> <p><strong>QA-0000-56837.ps.gz </strong>The full set of 849 quality assessment plots for the global spectral fitting. Each plot includes a top panel showing the continuum (brown) and Fe II (blue) model components; the red line is the sum of the two. The cyan diamonds are pixels masked as absorption or bad pixels. The gray brackets near the top of the panel indicate the windows used for the continuum+Fe II fit. The bottom panels present the emission line fits for five line complexes.</p> <p><strong>allqso_sdssrm.fits</strong> A FITS table of all 1214 known quasars in the 7 square degree SDSS-RM field. Only 849 of them received a fiber in the SDSS-RM spectroscopy. This table lists the basic target information of these quasars.</p> <p><strong>QSObased_Expanded_SDSSRM_107.fits</strong> The narrow MgII/FeII absorber catalog for SDSS-RM quasars, following the methodology outlined in Zhu & Ménard (2013). Each entry corresponds to one quasar. The search for narrow absorbers includes systems that have absorber redshift close to the quasar systemic redshift (|dz|<0.04). MgII absorbers blueshifted from the quasar by dz>0.04 and also redward of CIV by dz>0.02 are of high purity. MgII absorbers with |dz|<0.04 or those at wavelength blueward of CIV, or those with FeII detection but no MgII detections (likely due to bad pixels), while included in this catalog, should be treated with caution, and may contain a small fraction of false positives (mainly CIV absorbers).</p> <p>For convenience, we also provide a version of the absorber catalog organized by absorbers (<strong>Expanded_SDSSRM_107.fits</strong>), i.e., each entry corresponds to one absorber system.</p> <p><strong>rmqso32_aegis_multi_lambda.fits</strong> Multi-wavelength data compiled from Nandra et al. (2015) or 32 SDSS-RM quasars in the AEGIS field.</p> <p><strong>spitzer_seip_rm_match_1.5arcsec.fits</strong> Spitzer IRAC and MIPS data from the Spitzer Enhanced Imaging Products (SEIP) source list for 176 SDSS-RM quasars, with a matching radius of 1.5 arcseconds. This file also compiles infrared fluxes (if available) from 2MASS (Skrutskie et al. 2006).</p> <p><strong>spec_2014_BALrobust.csv</strong> List of 95 BALQSOs (including mini-BALQSOs) identified from the first-year coadded spectroscopy. This file includes BAL flags on CIV, AlIII, MgII, and FeII/FeIII. It also includes notes on individual objects.</p> <p><strong>PS1_MD07_LC_sdssrm.fits</strong> PS1 Medium Deep light curves for the SDSS-RM quasars used to compute PS1_NMAG_OK and PS1_RMS_MAG in the main catalog. Note this is the unofficial release of the PS1 MD07 data, which was approved by the PS1 collaboration. These photometric light curves may differ slightly from the final official release of the PS1 Medium Deep field data. </p>
UKRI Digital Research Infrastructure Mapping Survey Dataset (for Net Zero Scoping Project)
<p>This dataset was generated as an output for the DRI Mapping exercise carried out during the UKRI Net Zero Digital Research Infrastructure (DRI) Scoping Project undertaken from 2021-2023. The "README.md" provides more information about the dataset and how to use it.</p> <p>The report associated with this dataset is available at:</p> <p>https://doi.org/10.5281/zenodo.7805987</p>
Mapping Building BioData.pt Indicators against the performance and impact assessment frameworks for research infrastructures of OECD, ESFRI and RI-PATHS project
<p>"Buiding BioData.pt" indicators observed in international frameworks for performance and impact assessment of research infrastructures, namely, OECD, ESFRI and RI-PATHS.</p>
Topic Map for KPI analysis of e-Infrastructure projects
<p>This is a Topic Map from the e-IRG Knowledge Base used by the e-IRGSP5 project to analyse Key Performance Indicators (KPIs) for e-Infrastructure projects funded by Horizon 2020.</p>
Results of the crowd-mapping action within the project TeRRIFICA [Dataset No. 1 dated 2022-09-19]
<p>The dataset includes the results of the crowd-mapping action within the project "Territorial RRI fostering innovative climate action" - TeRRIFICA (Horizon 2020 under GA 824489) dated 2022-09-19. The data are points added to the map by the users (volunteers) and represent locations where climate change-related issues occur regarding air temperature, air quality, water, soil, and wind (SPOTS). The second part of the dataset is related to the crowd-mapping users and their anonymized characteristics (USERS). More details are available at https://terrifica.eu/.</p>
GEOLAB - Transnational Access project QC-CEM - Mapping quick clay with geophysical methods
<p>Quick clay is characterised by complete collapse and liquid-like mobility when overloaded. Quick clay is found primarily in Norway and Sweden, but also exists in Finland, Russia, Canada and Alaska. Quick clay landslides, with their retrogression characteristics and extreme mobility, pose significant risk to human lives, infrastructure, property and surrounding ecosystems. Hence, the proper characterization of quick clay sites is essential for ensuring the safety and resilience of infrastructure in Norway and elsewhere in Europe.<br> The current practice for mapping quick clay in Norway relies heavily on borehole data with either rotary sounding or total sounding and core samples tested in the laboratory. The only method for identifying quick clay with certainty is physical testing in the laboratory, but it is time-consuming, expensive and gives limited information, i.e., only at the depths and locations where the samples are taken. In Norway, rotary sounding and total soundings are frequently used in mapping of quick clay. There is increasing interest in using geophysical methods such as Electrical Resistivity Tomography (ERT) to supplement the results from soundings, particularly in early stage of ground investigation for mapping of quick clay. ERT is a near surface geophysical method that uses direct current to measure the earth's electrical resistivity. The current is injected into the subsurface through steel electrodes installed 10-20 cm into the ground, and the apparent resistivity distribution along a profile or area is measured. Using data processing and inverse modelling a 2D or 3D resistivity model of the subsurface can be derived.<br> Geophysical methods such as ERT show capability to identify not quick clay such as sand, silt, dry crust, moraine and bed rock reasonably accurate, but the identification of quick clay is still generally limited. The detection of leached clay (thus potentially quick clay) is however possible.<br> Transnational Access project QC-CEM is funded through the 1st call for proposal for the GEOLAB project. This project aims at testing various geophysical methods for their capability for soil characterisation, particularly for detecting quick clay.</p> <p>The objectives of the QC-CEM project are:<br> (i) to test different configurations of Electrical Resistivity Tomography survey for detection of quick clay<br> (ii) to test innovative and efficient electromagnetic based methods for mapping of quick clay. Results from this investigation is not available to share at this stage.<br> (iii) to investigation the effectiveness of cross-interpretation using different geophysical methods for soil characterisation. The results from this activity will be published in open publication after they are processed.</p>
Baltimore Ecosystem Study: Stewardship Mapping And Assessment Project (STEW-MAP) survey results 2011 and 2019
Addressing the challenges of sustainable and equitable city management in the 21st century requires innovative solutions and integration from a range of dedicated actors. In order to form and fortify partnerships of multi-sectoral collaboration, expand effective governance, and build collective resiliency it is important to understand the network of existing stewardship organizations. The term ‘stewardship’ encompasses a spectrum of local agents dedicated to the evolving process of community care and restoration. Groups involved in stewardship across Baltimore are catalysts of change through a variety of conservation, management, monitoring, transformation, education, and advocacy activities for the local environment – many with common goals of joint resource management, distributive justice, and community power sharing. The “environment” here is intentionally broadly defined as land, air, water, energy and more. The Stewardship Mapping and Assessment Project (STEW-MAP) is a method of data collection and visualization that tracks the characteristics of organizations and their financial and informational flows across sectors and geographic boundaries. The survey includes questions about three facets of environmental stewardship groups: 1) organizational characteristics, 2) collaboration networks, and 3) stewardship “turfs” where each organization works. The data have been analyzed alongside landcover and demographic data and used in multi-city studies incorporating similar datasets across major urban areas of the U.S. Additional information about the growing network of cities conducting stewmap can be found here: https://www.nrs.fs.usda.gov/STEW-MAP/ Romolini, Michele; Grove, J. Morgan; Locke, Dexter H. 2013. Assessing and comparing relationships between urban environmental stewardship networks and land cover in Baltimore and Seattle. Landscape and Urban Planning. 120: 190-207. https://www.fs.usda.gov/research/treesearch/44985 Johnson, M., D. H. Locke, E. Svendsen, L
SCRUM framework adaptations - dataset of systematic mapping study, EclipseIDE project
<p>Dataset from the SCRUM framework adaptations systematic mapping study</p>
Supplemental Figures for: "The SDSS-V Black Hole Mapper Reverberation Mapping Project: Multi-Line Dynamical Modeling of a Highly Variable Active Galactic Nucleus with Decade-long Light Curves"
<p>Additional figures for the paper The SDSS-V Black Hole Mapper Reverberation Mapping Project: Multi-Line Dynamical Modeling of a Highly Variable Active Galactic Nucleus with Decade-long Light Curves. </p> <h2> </h2> <h2>Interactive Figure Data</h2> <p>Data files used to create the intreactive version of Figure 5 in the publication. There is a version of each file for each line species in the plot (i.e., Hα, Hβ, and MgII).</p> <p><strong>clouds_{line_name}.csv</strong>: A CSV file containing the cloud positions, line-of-sight velocities, and weights. The columns of the file are x [light-day], y [light-day], z [light-day], velocity [km/s], and weight.</p> <p><strong>transfer_function_velocity_{line_name}.csv</strong>: A CSV file containing x-axis of the transfer function panels, the rest-frame velocity.</p> <p><strong>transfer_function_tau_{line_name}.csv</strong>: A CSV file containing the y-axis of the transfer function panels, the rest-frame time delay τ in days.</p> <p><strong>transfer_function_{line_name}.csv</strong>: A CSV file containing the transfer function <span lang="el">Ψ.</span></p> <p> </p> <h2>Model-Related Figures</h2> <p><strong>fitplot_low.pdf</strong>: Same as Figure 4 in the publication, but for the low state.</p> <p><strong>fitplot_high.pdf</strong>: Same as Figure 4 in the publication, but for the high state.</p> <p><strong>geoplot_low.pdf</strong>: Same as Figure 5 in the publication, but for the low state.</p> <p><strong>geoplot_high.pdf</strong>: Same as Figure 5 in the publication, but for the high state.</p> <p><strong>lagplot_low.pdf</strong>: Same as Figure 6 in the publication, but for the low state.</p> <p><strong>lagplot_high.pdf</strong>: Same as Figure 6 in the publication, but for the high state. </p> <p> </p> <h2>Spectral Reduction Method Comparison</h2> <p><strong>spec_decomp_pyqsofit.pdf</strong>: A figure showing the spectral decomposition performed in PyQSOFit for the processed line profiles for Hβ, Hα, and MgII for an example epoch. The total spectrum is shown in black, and each of the decomposed elements are shown, color-coded using the legend above the three panels.</p> <p><strong>input_method_comp.pdf</strong>: A figure showing the processed multi-epoch line profiles for each spectral reduction method (PyQSOFit and PrepSpec). Each column corresponds to a given line (labeled above), and each row corresponds to a given spectral reduction method (labeled on the right). Note that the scales for each panel are different.</p> <p> </p> <h2>Published Value Comparison</h2> <p><strong>pubval_table.pdf</strong>: A table comparing the values obtained for certain physically relevant parameters obtained from our BRAINS modeling to those obtained in Shen et al. (2024). </p> <p> </p> <h2>Joint Posterior Analysis</h2> <p><strong>joint_line_posterior_table.pdf</strong>: A table containing the median values (and their uncertainties) extracted from the joint posteriors for a few key model parameters. These joint posteriors are produced for a given state, across all line species. </p> <p> </p> <h2>Virial Factor Analysis</h2> <p><strong>fcomp.pdf</strong>: A comparison of the virial factor values obtained by using the line dispersion (σ) and FWHM of each of the lines in each of the states.</p> <p><strong>fcorr_table.pdf</strong>: A table showing the correlations between the virial factor and model parameters (i.e., the slopes obtained using <a href="https://github.com/jmeyers314/linmix">LinMix</a> assuming a linear relationship, and the correlation coefficients). Values are given for virial factors obtained using both the line dispersion (σ) and FWHM.</p>
Project files provided as supporting information to the manuscript "Making sense of complex systems through resolution, relevance, and mapping entropy"
<p>README file to the project files provided as supporting information to the manuscript “Making sense of complex systems through resolution, relevance, and mapping entropy”</p> <p>Feb. 25, 2022</p> <p>Authors: Roi Holtzman, Marco Giulini and Raffaello Potestio</p> <p>==================================</p> <p>The dataset contains the following files:</p> <p>- A README file with the description of the pymap program for describing how different selections of *N* out of *n* degrees of freedom (mappings) affect the amount of information retained about a full data set.<br> - The pymap.py program<br> - The pymap.yml support file<br> - The data.tar tarball with the setup data<br> - The results.tar tarball with the output data<br> ===</p>
Fig. 4. The potential distribution map for B. bombina under projected 2050 in Long-Term Bioclimatic Modelling The Distribution Of The Fire-Bellied Toad, Bombina Bombina (Anura, Bombinatoridae), Under The Influence Of Global Climate Change
Fig. 4. The potential distribution map for B. bombina under projected 2050 climatic conditions. The colour gradient represents high (red) to low (green) habitat suitability for the species.
Supplementary Data: Mapping of local lattice parameter ratios by projective Kikuchi pattern matching
<p>This is the experimental dataset which was analyzed in:</p> <p>"Mapping of local lattice parameter ratios by projective Kikuchi pattern matching"<br> Aimo Winkelmann, Gert Nolze, Grzegorz Cios, and Tomasz Tokarski<br> Phys. Rev. Materials <strong>2</strong> (2018) 123803<br> https://doi.org/10.1103/PhysRevMaterials.2.123803</p> <p>We describe a lattice-based crystallographic approximation for the analysis of distorted crystal structures via electron backscatter diffraction (EBSD) in the scanning electron microscope. EBSD patterns are closely linked to local lattice parameter ratios via Kikuchi bands that indicate geometrical lattice plane projections. Based on the transformation properties of points and lines in the real projective plane, we can obtain continuous estimations of the local lattice distortion based on projectively transformed Kikuchi diffraction simulations for a reference structure. By quantitative image matching to a projective transformation model of the lattice distortion in the full solid angle of possible scattering directions, we enforce a crystallographically consistent approximation in the fitting procedure of distorted simulations to the experimentally observed diffraction patterns. As an application example, we map the locally varying tetragonality in martensite grains of steel.</p>
Data for: Image-based evaluation of beers at an online Pint of Science festival using Projective Mapping, Check-All-That-Apply and Acceptability
<p>Data obtained from n=67 untrained attendants at an outreach Pint of Science festival, online because of the COVID-19 pandemic but usually held at bars. The participants used images of brand logos to evaluate eight beers among the most commonly consumed in Spain. Three sensory analysis techniques were used: Projective Mapping, Acceptability and Check-All-That-Apply (CATA).</p>
Data release for paper "The Araucaria Project: Deep near-infrared photometric maps of Local and Sculptor Group galaxies. I. Carina, Fornax, Sculptor"
<p>Deep near-infrared J- and K-band photometry of three Local Group dwarf spheroidal galaxies: Fornax, Carina, and Sculptor, is made available for the community. Until now, these data have only been used by the Araucaria Project to determine distances using the tip of the red giant and RR Lyrae stars. Now, we present the entire data collection in a form of a database, consisting of accurate J- and K-band magnitudes, sky coordinates, ellipticity measurements, and timestamps of observations, complemented by stars' loci in their reference images. Depth of our photometry reaches about 22 mag at 5 sigma level, and is comparable to NIR surveys, like the UKIRT Infrared Deep Sky Survey (UKIDSS) or the VISTA Hemisphere Survey (VHS), and small overlap with VHS and no overlap with UKIDSS makes our database a unique source of quality photometry.</p> <p>Data release consists of:</p> <ul> <li>databases in a form of text files for Carina, Fornax and Sculptor galaxies<br> (db_Car.txt, db_For.txt , db_Scu.txt)</li> <li>completeness tables and plots for every field in Carina, Fornax and Sculptor galaxies<br> (compl_Car.pdf, compl_Car.txt, compl_Scu.pdf, compl_Scu.txt, compl_For.pdf, compl_For.txt)</li> <li>explanatory file for each galaxy<br> (info_Car.txt, info_Scu.txt, info_For.txt)</li> <li>FITS images of scientific quality of all analyzed fields in Carina, Fornax and Sculptor galaxies, archived in tar.gz files</li> </ul>
XRF maps and line scans project files belonging to XRF instrument report. Identification of ink components through XRF analysis of Azzolino documents.
<p>RTX Project files. Details given in supporting information </p> <p><a href="https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0283539.s002">S2 File. </a>XRF instrument report.</p> <p>Identification of ink components through XRF analysis of Azzolino documents.</p> <p><a href="https://doi.org/10.1371/journal.pone.0283539.s002">https://doi.org/10.1371/journal.pone.0283539.s002</a></p> <p>(DOCX)</p> <p>Belonging to publication </p> <p>Lagerqvist Alidoost A, Hacke M, Winther T, Sandström T (2023) A closer look at the Azzolino collection. PLOS ONE 18(4): e0283539. <a href="https://doi.org/10.1371/journal.pone.0283539">https://doi.org/10.1371/journal.pone.0283539</a></p>
Landcover change analysis of the McKenzie Basin for the Maps and Locals (MALS) project.
This dataset was developed for use in an analysis of landcover change in the McKenzie Basin for the Maps and Locals (MALS) project. MALs is funded by LTER Social Science Supplement grants of the National Science Foundation.
GIS Map of project 'Skopje 2014'
<p>This is the GIS file, data, metadata and a first series of maps that were produced through research on project 'Skopje 2014' (REPLICIAS MSCA grant). The information was collected through personal survey, newspaper sources, Prizma's research (BIRN), the Association of Architects of North Macedonia, and online forums. </p> <p>Researchers are welcome to further enrich this and return new versions. Attribution is necessary. This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/.</p>
Maps of reference evapotranspiration for the irrigation project in Brazil
<p>The maximum daily evapotranspiration data set for a project (ETproject) for Brazil. It has a spatial resolution of <strong>30 seconds (~ 1 km²)</strong>. The data set grid is in <strong>GeoTIFF format</strong> and corresponds perfectly to WorldClim. It uses the <strong>geographic coordinate</strong> reference system, with <strong>WGS84 projection (EPSG: 4326)</strong>.</p> <p>The objective study is to estimate and provide evapotranspiration values of monthly reference and the maximum of twelve months, for dimensioning irrigation systems throughout the Brazilian territory. With the meteorological data of two hundred and fifty-nine conventional INMET stations, the daily reference evapotranspiration (ETo) for 15 years was calculated. For each weather station, the data was grouped by month and the ETo for the irrigation project (ETproject) was determined to meet the eighty percent probability of occurrence, following the recommendations of FAO24. In parallel, monthly images of 15 years of ETo were acquired for Brazil, and the climatic variables of WorldClim. Using the ET values of the stations design, it was modeled for the rest of Brazil, using machine learning algorithms and the covariates. After modeling, the following performances were achieved: mean square error of 0.306 mm / d, mean bias error of -0.004 mm / d, mean absolute error of 0.227 mm / d, determination coefficient of 0.938 and efficiency of Nash-Sutcliffe 0.937. ETo values for irrigation projects were similar to several others reported in the literature when compared at a given point. With this research it was possible to determine the monthly and annual ETo for irrigation projects throughout the Brazilian territory.</p> <p>The article has been submitted for publication.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.