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Integrative documentation workflow with augmented reality interaction
No full text<p>The organisational chart outlines a so called integrative documentation workflow with augmented reality feedback. While interlinking a range of survey tools and mapping data streams between software and hardware, an integration of a central processing cloud plus an augmented reality device for real-time feedback and information input is envisioned. The workflow is under development as part of a doctoral thesis; future adaptions will be updated in this repository.</p>
3D Reconstruction Model of the Former Synagogue in the Neudeggergasse 12, Vienna (1903 | Architect: Max Fleischer)
No full text<p>This record contains model data originally created in the framework of the masters' thesis of Georg Niessner & Peter Schilling at TU Wien (2004).</p><p>Facts: Association synagogue of the Tempelbauverein Josefstadt (Josefstadt Temple Erection Association) founded in 1903 by Baron Moritz von Königswarter | Erected 1903 | Architect: Max Fleischer | Capacity: seating for 239 women and 338 men | Appearance: brick neo-Gothic with delicate towers; triple-aisled interior</p><p>See also:</p><p>* City Guide --> https://www.lit-verlag.de/isbn/978-3-643-90170-5</p><p> </p><p>The data set includes</p><p>- Modelling software: ArchiCAD *.PLA - Archive</p><p>- Rendering Software: ArtLantis *.ATLA - Archive</p><p>- Panoramic representation: *.HTML & *.PNO</p><p> </p>
3D Reconstruction Model of the Former Synagogue in the Große Schiffgasse 8, Vienna (1864 | Architect: unknown | Redesign 1923; Ignaz Reiser)
No full text<p>This record contains model data originally created in the framework of ongoing research work.</p><p>Facts: Association synagogue in the courtyard of the property no. 8 Große Schiffgasse, known as the Schiffschul built 1858(?)–1864; Consecration on September 16 September 1864 | Architect: unknown, Ignaz Reiser (redesign 1923) | Capacity: seating for 250 women and 500 men | Appearance: single aisled hall with barrel-vault roof</p><p>See also:</p><p>* City Guide --> https://www.lit-verlag.de/isbn/978-3-643-90170-5</p><p>* Locations for comparison:</p><p>- Pazmanitengasse 6 - 1100 Vienna</p><p>- Storchengasse 21 - 1150 Vienna</p><p> </p><p>The data set includes</p><p>- Modelling software: ArchiCAD *.PLA - Archive</p><p>- Rendering Software: ArtLantis *.ATLA - Archive</p><p>- Panoramic representation: *.HTML & *.PNO</p><p> </p>
3D mesh model Karlskirche, Vienna Austria
No full text<p>mesh model interior and exterior created by laserscan and photogrammetry</p>
<p>please contact <strong>[email protected]</strong> for access</p><p>captured with Zoller Fröhlich Imager 5010C with HDR 80mpx camera; processed within local coordinate system; supplemented with photogrammetry using calibrated camera (undefined model) and 12mpx UAV camera; matched with Riegl (Riegl LMS & TU Wien) dataset using point sampling and ICP matching; </p><p>meshes in local coordinate system of capturing campaign; transformation matrix to WGS84_EPSG 4978 included in dataset</p>
Sentinel-1 Global Harmonic Parameters: A Seasonal Model for Flood Mapping and More
No full text<p>This dataset was generated by the <a href="https://mrs.geo.tuwien.ac.at/">Remote Sensing Group</a> of the <a href="https://www.geo.tuwien.ac.at/">TU Wien Department of Geodesy and Geoinformation</a>, within Framework Contract (No. 939866-IPR-2020) as part of the provision of an automated, global, satellite-based flood monitoring product for the Copernicus Emergency Management Service (CEMS) managed by the European Commission. The Global Flood Monitoring (GFM) product is integrated within the user interface of the Global Flood Awareness System (GloFAS) of the CEMS. Open use of the dataset is granted under the <a href="https://creativecommons.org/licenses/by/4.0/">CC BY 4.0 license</a>.</p><p>The Copernicus Sentinel-1 constellation is a highly-capable monitoring mission and provides one of the most comprehensive global archives on satellite imagery. The satellite sensors acquire Synthetic Aperture Radar (SAR) images, and as such, they observe regardless of weather conditions and daylight. The regular and systematic observations generate rich information on the global land surface and its dynamics, which is used for---but not limited to---terrestrial applications like e.g. land cover mapping, flood detection, or drought monitoring.</p><p>The complete Sentinel-1 time-series dataset is challenging to analyze, primarily due to its sheer data volume of at the (global) scale of Petabytes. As a user-friendly alternative, this dataset provides a Harmonic (Fourier) series model that reduces the SAR backscatter seasonality to a relative small number of GeoTIFF files holding the harmonic coefficient values.</p><p>This dataset publication provides a temporal Sentinel-1 model for most of the world's land masses. Seven coefficients computed using (harmonic) least squares regression, along with the standard deviation of residuals and number of observations, comprise the harmonic parameter set. The parameters are being operationally used to determine the expected SAR backscatter signal for any day of the year as part of the TU Wien's method contributing to GFM's ensemble flood monitoring effort <a href="https://www.mdpi.com/2072-4292/14/15/3673">(Bauer-Marschallinger et. al, 2022)</a>. The Global Harmonic Parameters (HPARs) were derived from the whole Sentinel-1 VV temporal stack for the period 2019-2020 by least squares regression with a harmonic model formulation, running three sinusoidal iterations (k=3).</p><p>The model describes the typical seasonal Sentinel-1 backscatter variation on a 20 m pixel level. It was designed as a smoothed time-series approximation, removing short-term perturbations, such as speckle and transient events (like floods for instance). Hence, the model is suited to discern the seasonal changes brought about by varying water content, e.g., inundation or soil moisture, and progression of vegetation structure.</p><p>We encourage developers from the broader user community to exploit this extensive and functional data resource. In particular, we promote the use of these Sentinel-1 HPARs in models for various applications dealing with land cover, seasonal water mapping, or vegetation phenology.</p><p>For the datasets' theoretical formulation and primary use case as a non-flooded backscatter reference model, please refer to our peer-reviewed <a href="https://doi.org/10.3390/rs14153673">article</a>. Additionally, the software used, computation process, and outlook are discussed in this conference <a href="https://doi.org/10.5194/isprs-archives-XLVIII-4-W1-2022-495-2022">paper</a>.</p><h2>Data record</h2><p>The parameter sets are provided per Sentinel-1's relative <a href="https://sentinels.copernicus.eu/web/sentinel/missions/sentinel-1/satellite-description/orbit">orbit</a> to account for geometric effects. The parameter files are sampled at 20 m pixel spacing, georeferenced to the Equi7Grid, and divided into six continental zones (Africa, Asia, Europe, North America, Oceania, and South America. For portability and easier downloads, further sub-divisions into continental parts are done, resulting in 12 compressed bundles (please refer to coverage map).</p><p>The parameter sets are provided per Sentinel-1's relative to account for geometric effects. The parameter files are sampled at 20 m pixel spacing, georeferenced to the <a href="https://github.com/TUW-GEO/Equi7Grid">Equi7Grid</a>, and divided into six continental zones (Africa, Asia, Europe, North America, Oceania, and South America);. For portability and easier downloads, further sub-divisions into continental parts are done, resulting in 12 compressed bundles (please refer to coverage map).</p><p>The data itself is organised as square tiles of 300 km extent ("T3"-tiles). Note that the parameters are generated for each orbit, resulting in several orbit-sets per tile. Given this structure, a total of 98910 files for the 10990 tiled orbit-sets, comprising overall a compressed disk size of 3.7 TB.</p><p>The datasets follow the Yeoda filenaming convention (documentation <a href="https://github.com/TUW-GEO/geopathfinder/blob/master/src//geopathfinder/naming_conventions/yeoda_naming.py">here</a>) where the core meta information is embedded. Notably, the file name is prefaced by the product name 'SIG0-HPAR-' and the particular parameter codes:</p><ul><li><strong>M0</strong> - effective mean of the time series stacks, also called the harmonic residual in other literature.</li><li><strong>Cn</strong> - cosine component coefficients, where n = 1, 2, or 3.</li><li><strong>Sn</strong> - sine component coefficients, where n = 1, 2, or 3.</li><li><strong>STD</strong> - standard deviation of residuals, a proxy for model goodness of fit.</li><li><strong>NOBS</strong> - number of observations used for the least squares regression, also<br>an indicator of solution quality.</li></ul><p>Orbit sets are distinguishable by orbit direction, i.e. (A - ascending and D - descending) and relative orbit number, for example: 'A175', 'D080'.</p><p>File naming scheme is as follows:</p><p><i><strong>SIG0-HPAR</strong></i>-NNN_YYYYMMDD1_YYYYMMDD2_<i><strong>VV</strong></i>_OOOO_TTTTTTTTTT_GGGG_<i><strong>V02R01</strong></i>_<i><strong>S1IWGRDH</strong></i>.tif </p><p>*bold faced items are fixed for this product version.</p><ul><li><i>NNN</i> - product name which indicates parameter code.</li><li><i>YYYYMMDD1</i> - start date of time series processed.</li><li><i>YYYYMMDD2 </i>- end date of time series processed.</li><li><i>VV </i>- polarization of product.</li><li><i>OOOO</i> - relative orbit.</li><li><i>TTTTTTTTTT </i>- Equi7grid tile name.</li><li><i>GGGG</i> - Subgrid. Contains continent code and sampling size.</li><li><i>V02R01</i> - Product version.</li><li><i>S1IWGRDH </i>- Sensor type.</li></ul><p>For example:<br>'SIG0-HPAR-STD_20190101_20210101_VV_D111_E102N066T3_SA020M_V02R01_S1IWGRDH.tif'</p><p>The parameters' file format is an LZW-compressed GeoTIFF holding 16-bit integer values, with tagged metadata on encoding and georeference. Compatibility with common geographic information systems such as QGIS or ArcGIS, and geodata libraries as GDAL is given.</p><p>This repository provides all parameter sets per orbit for each tile and is organized in a folder structure per (sub-)continent. With this, twelve zipped dataset collections per (sub-)continent are available for download.</p><h2><strong>Code Availability</strong></h2><p>We suggest users to use the open-source Python package yeoda, a datacube storage access layer that offers functions to read, write, search, filter, split and load data from this repository as an HPAR datacube. The yeoda package is openly accessible on GitHub at <a href="https://github.com/TUW-GEO/yeoda">https://github.com/TUW-GEO/yeoda</a>.</p><p>Furthermore, for the usage of the Equi7Grid we provide data and tools via the python package available on GitHub at <a href="https://github.com/TUW-GEO/Equi7Grid">https://github.com/TUW-GEO/Equi7Grid</a>. More details on the grid reference can be found in this <a href="https://doi.org/10.1016/j.cageo.2014.07.005">publication</a> .</p><p>A day-of-year estimate reader tool based on the packages above is likewise available on GitHub at <a href="https://github.com/TUW-GEO/hpar-reader">https://github.com/TUW-GEO/hpar-reader</a>. </p><h2><strong>Acknowledgements</strong></h2><p>The authors would like to thank our colleagues: Thomas Melzer of TU Wien for his invaluable insights on the parameter formulation, and Senmao Cao of Earth Observation Data Centre GmbH (EODC) for his contributions to the code base used to process dataset.</p><p>This work was partly funded by TU Wien, with co-funding from the project "Provision of an Automated, Global, Satellite-based Flood Monitoring Product for the Copernicus Emergency Management Service" (GFM), Contract No. 939866-IPR-2020 for the European Commission's Joint Research Centre (EC-JRC), and the project "Flood Event Monitoring and Documentation enabled by the Austrian Sentinel Data Cube" (ACube4Floods), Contract No. 878946 for the Austrian Research Promotion Agency (FFG, ASAP16).</p><p>The computational results presented have been achieved using the Vienna Scientific Cluster (VSC). We further would like to thank our colleagues at TU Wien and EODC for supporting us on technical tasks to cope with such a large and complex dataset.</p>
Impact of erroneous a priori information on the UT1-UTC determination from VLBI Intensive sessions (simulation study)
No full text<p>The dataset was generated by researchers from the <a href="https://www.geo.tuwien.ac.at/">TU Wien Department of Geodesy and Geoinformation</a> and the <a href="https://baug.ethz.ch/">ETH Zürich Department of Civil, Environmental and Geomatic Engineering</a>, as a fundamental part of a study related to the analysis of the impact of erroneous a priori information on the UT1-UTC determination from VLBI Intensive sessions. The corresponding publication (title: "On the importance of accurate pole and station coordinates for VLBI Intensive baselines") has been submitted to the Journal of Geodesy. </p><p>In addition, a <a href="https://doi.org/10.34726/4201">conference paper</a>, and presentations at the <a href="http://hdl.handle.net/20.500.12708/139204">IVS General Meeting 2022</a>, <a href="http://hdl.handle.net/20.500.12708/136186">EGU General Assembly 2022</a> and <a href="https://doi.org/10.34726/3183">REFAG 2022</a> are available.</p><h3>Context and methodology</h3><p>The dataset contains monthly simulated UT1-UTC values of an artificial global grid of VLBI antennas (VGOS) where realistic errors in the a priori values of the station coordinates, polar motion and nutation offsets are introduced. With the help of these simulated values the global impact of erroneous a priori information is analysed.</p><p><a href="https://doi.org/10.1088/1538-3873/ab1820">VieSched++</a> and <a href="https://doi.org/10.1088/1538-3873/aaa22b">VieVS </a>(both developed at the TU Wien) were used to generate the schedules and simulations.</p><h3>Technical details</h3><p>The dataset is structured as follows. There are 7 subfolders in the zipped folder that contain the simulation results of the evaluations with modified a priori values:</p><ul><li>folder "errSTAu" - error of 5 mm introduced in the up-direction of the second station</li><li>folder "errSTAe" - error of 5 mm introduced in the east-direction of the second station</li><li>folder "errSTAn" - error of 5 mm introduced in the north-direction of the second station</li><li>folder "errPMx" - error of 162 microarcseconds introduced in the x-component of the polar motion</li><li>folder "errPMy" - error of 162 microarcseconds introduced in the y-component of the polar motion</li><li>folder "errNUTx" - error of 162 microarcseconds introduced in the x-component of the nutation offsets</li><li>folder "errNUTy" - error of 162 microarcseconds introduced in the y-component of the nutation offsets</li></ul><p>Within these folders, there are .txt files with the following naming convention: "N%E%__N%E%_d#.txt".</p><ul><li>"N%E%__N%E%" represents the location (North and East in degrees = latitude and longitude) of the reference and remote station</li><li>"d#" again shows the error that has been introduced in the simulation process</li><li>The files contain the monthly simulation results of UT1-UTC and its accuracy in milliseconds.</li></ul>
Terrestrial reference frame (TRF) from VIE2022 VLBI solution
No full text<p>Terrestrial reference frame estimated from Very Long Baseline Interferometry (VLBI) technique measurements (1979.6 - 2023.0).</p><p>VLBI global solution of S/X + VGOS 24h sessions.</p><ul><li>GENERATION TIME: 2023-07-28T02:40:05</li><li>DATA START: 1979-08-03T00:00:00</li><li>DATA END: 2022-12-30T00:00:00</li><li>ANALYSIS CENTER: VIE (TU Wien, Austria)</li><li>CONTACT: VIE Analysis Center ([email protected])</li><li>SOFTWARE: VieVS v3.2</li><li>TECHNIQUE: VLBI</li><li>FREQUENCY BANDS: S/X + VGOS</li><li>FORMAT: ITRF</li><li>DESCRIPTION: VLBI station positions from VLBI global solution S/X + VGOS, updated with additional VGOS sessions. Station positions are given for epoch 2015.0 with linear velocities. Position of stations affected by post-seismic deformations (PSD) has to be computed by applying the ITRF2020 PSD corrections (Altamimi et al., 2023).</li></ul><p> </p>
RAAV - Results of the PT-STA accessibility analysis for five public transport scenarios based on automated vehicles in Mühlwald, South Tyrol
No full text<h2>Dataset description</h2><p>As part of the project <strong>"RAAV - Rural Accessibility and Automated Vehicles"</strong> between the TU Vienna (Austria) and the EURAC institute (Bolzano, Italy), this file serves to summarise the results of the application of the PT-STA method for separate public transport scenarios in a comprehensible manner and to make them publicly available.</p><h3>Context and methodology</h3><p>An adaption of a classical STA accessibility analysis was applied on a sample of over 100 individuals in Mühlwald, South Tyrol. Five different public transport scenarios based on a possible implication of automated vehicle technology were compared regarding their potential impact on accessibility for the local population.</p><p>To be as transparent as possible the data is provided in the Microsoft Excel format with all cell references. By doing this, we ensure that the data can also be used and adapted for other research.</p><h3>Technical details</h3><p>The dataset contains one Microsoft Excel file containing multiple data sheets. In order to ensure data protection and anonymisation all names, addresses and coordinates of interviewed people, origins and destinations have been deleted from the dataset.</p><p>Other than Microsoft Excel, there is no additional software needed to investigate the data. The first datasheet gives an overview of abbreviations and data stored in each data sheet.</p>
Celestial reference frame (CRF) from VIE2022 VLBI solution
No full text<p>Celestial reference frame estimated from Very Long Baseline Interferometry (VLBI) technique measurements (1979.6 - 2023.0).</p><p>VLBI global solution of S/X + VGOS 24h sessions.</p><ul><li>GENERATION TIME: 2023-07-28T02:41:15</li><li>DATA START: 1979-08-03T00:00:00</li><li>DATA END: 2022-12-30T00:00:00</li><li>ANALYSIS CENTER: VIE (TU Wien, Austria)</li><li>CONTACT: VIE Analysis Center ([email protected])</li><li>SOFTWARE: VieVS v3.2</li><li>TECHNIQUE: VLBI </li><li>FREQUENCY BANDS: S/X + VGOS</li><li>FORMAT: ICRF</li><li>DESCRIPTION: CRF from the VLBI global solution S/X + VGOS, updated with additional VGOS sessions. Source positions are in the J2000 frame, but at the 2015.0 galactic aberration epoch. Reported source position errors are inflated with scaling factors: 1.5 RA, 1.5 De, and a RA/Dec noise floor 30/ 30 micro-arc-sec is applied.</li></ul>
Supplementary data for "Absence of electron-phonon-mediated superconductivity in hydrogen-intercalated nickelates"
No full text<h3>Context and Methodology</h3><p>This repository contains raw data for the paper "Absence of electron-phonon-mediated superconductivity in hydrogen-intercalated nickelates" in the field of computational condensed matter. It was uploaded with the purpose of making the data of the paper publicly available to ensure reproducibility of the calculations performed. The preprint is <a href="https://arxiv.org/pdf/2304.03599.pdf">available on arXiv.</a> The manuscript has been submitted to a peer review journal. The dataset contains raw data used for the figures, input and output files for the calculations, as well as the modified code employed.</p><h3>Technical details</h3><p>The repository contains data in plain text format, as well as a few .png figures. It contains the following data:</p><ul><li>One folder corresponding to each figure in the publication, with the raw data used to generate the figure (Figure1, Figure2, Figure3). Where more than one panel is present, subfolders indicate the data for each panel.</li><li>Raw input and output files for the calculations performed. All input and output files are in plain text format and can be read by any text editor. To understand their significance we refer the reader to the manual for the Quantum ESPRESSO and EPW codes. The folders containing input and output data are divided as follows:<ul><li>The "LaNiO2" folder contains calculations for LaNiO2 done in two different supercells. The name of the folders/subfolders indicates the type of calculations. </li><li>The "NdNiO2" folder contains calculations for NdNiO2 done in the 2x2x1 supercell, as well as convergence checks. Please note that under /PHONONS/ANHARMONIC/ only the raw data for the anharmonic phonon calculations are reported. The code was not uploaded, since it was given privately by the group of prof. Heil from TU Graz. Enquiries for the code should be directed to them. </li></ul></li><li>QE-7.1_<i>DiCataldo_</i>edit contains a modifided version of Quantum ESPRESSO that will accept as input the number of electrons and compute the electron-phonon coupling in the rigid-band approximation. This modified Quantum ESPRESSO code is shared under the GNU general public license in respect of the<a href="https://www.quantum-espresso.org/Doc/pw_user_guide/node5.html"> original license of the code.</a></li></ul><h3>License</h3><p>All data is published under the CC-BY 4.0 license. The code is under the GNU General public license.</p>