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39 results for “ERT”
Electromagnetic data (FDEM and ERT) collected in the Venice coastland (Zennare basin)
<p>FDEM and ERT data collected southern of the Venice lagoon (Italy) in the Zennare basin in 2019-2020.</p> <p>FDEM_ZENNARE37.csv: Raw output of Quadrature and Inphase values for the 6 frequencies adopted with the GEM2 FDEM probe.<br> ERT_ROUGHoutput_Zennare.dat: Apparent resistivity data as retrieved with the 48 channels Syscal Pro georesistivimeter ERT.</p>
Electrical Resistivity Tomography (ERT) datasets from the Otemma glacier forefield and outwash plain
<p><strong>Electrical Resistivity Tomography (ERT) datasets collected in the Otemma forefield (Switzerland) from 2019 to 2021.</strong><br> Data were collected by the research teams of Bettina Schaefli<sup>1,2</sup>, Stuart N. Lane<sup>1</sup> and James Irving<sup>3</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p><sup>3</sup> Institute of Earth Sciences (ISTE), University of Lausanne, 1015 Lausanne, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> </ul> <p><strong>This dataset is first referenced and discussed in the research paper by Müller et al., 2022.</strong></p> <p>------------------------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><strong>Data Description</strong></p> <p>Electrical Resistivity Tomography (ERT) profiles were collected around the outwash plain of the Otemma glacier forefield (WGS84 : 45.93434 / 7.41209). All data were collected with a <a href="http://www.iris-instruments.com/syscal-pro.html">Syscal Pro</a> Switch 48 from Iris Instruments, using an array of maximum 48 electrodes with a spacing between 1 and 10 meters. For each line, measurements were performed using a Dipole-Dipole (dd) and a Wenner-Schlumberger (ws) electrode configuration.</p> <p>All ERT lines locations can be visualized in <em><strong>ERT_map_lines_2019-2021.jpg</strong>.</em></p> <p>A result overview can be vizualized in <em><strong>ERT_allResults_3Doverview.png</strong>.</em></p> <p><strong>Data Structure</strong></p> <p>Two <a href="https://jupyter.org/">Juypter Notebook</a> files are provided and can be used to reproduce all inversion analyses.</p> <ul> <li><em><strong>1_createInput_prosys_to_pygimli.ipynb</strong></em> : Transforms the raw data from Syscal Pro (exported with <a href="http://www.iris-instruments.com/download.html">ProsysII</a> software as .csv) to a processed .dat file formated for inversion using the <a href="https://www.pygimli.org/">pyGIMLi</a> library.</li> <li><em><strong>2_ERT_inversion.ipynb</strong></em> : Reads the processed .dat file and performs a 2D robust inversion for a set of regularization parameters for the selected line.</li> </ul> <p>In <strong>ERT_data.zip</strong>, 3 folders with similar structure contain all data for year 2019, 2020 and 2021. Each folder contains :</p> <ol> <li><strong>GPS </strong>: folder with electrodes coordinates for each ERT line</li> <li><strong>inputGiMLi</strong> <ul> <li><strong>prosys_csv</strong>: contains the raw field measurements (downloaded from the Syscal device using ProsysII)</li> <li><strong>input_ERT </strong>: stores the processed .dat file. (created from notebook 1)</li> <li><strong>results_lambda</strong> : contains a .png image with the inversion results using different values of the regularization parameter lambda used to assess the sensitivity of the inversion results (over/underfitting). Analysis is performed for each line and each electrode configuration (dd or ws). (created from notebook 2)</li> <li><strong>results_final</strong> : contains a .png image with the final inversion results for each line and electrode configuration (dd or ws) using the optimal lambda parameter only (all arrays are shown from East to West). (created from notebook 2)</li> <li><strong>vtk</strong> : contains a .vtk file for each final results for 3D vizualization in the <a href="https://www.paraview.org/">Paraview</a> software.</li> </ul> </li> <li><strong><em>ERT_line_description_yyyy.csv</em> </strong>: a file describing the ERT arrays characteristics (read in notebook 1 and 2)</li> </ol> <p>The <strong>results </strong>folder contains :</p> <ul> <li><strong>ERT_3Dview_paraview</strong> folder : contains Paraview state files (.pvsm) for 3D vizualization of all results, as well as image files.</li> <li><em><strong>ERT_results_all.pdf</strong></em> : A summary of all final results for all years (similar content as <em>ERT/inputGiMLi</em><strong>/</strong><em>results_final</em> folders)</li> <li><em><strong>ERT_results_bedrock.pdf</strong></em> : Contains the vizualization of specific ERT profiles in the outwash plain and their field location . The separation between a surface layer of water-saturated sediments (resistivity <2500 Ωm) and the underlying bedrock is delimited. The likely presence of buried ice blocks (isolated blocks with resistivity >5000-10000 Ωm) is also highlighted.</li> <li><em><strong>ERT_timelapse_salt_tracer.gif</strong></em> : results of a time-lapse ERT measurement performed on 9 August 2019 to track the movement of a salt plume injected at 06 am, 9.38 meters upslope (see paper by<em> Müller et al., 2022</em> for detailed analysis). The tracer starts to appear at 12:45 at a distance of 30m on the array. Minimum resistivity is reached at between 16:45 and 17:45.</li> </ul>
ERT Datasets for the paper of Nickschick et al. (2019) in Solid Earth
<p>Underlying data for the paper</p> <p>Nickschick, T., Flechsig, C., Mrlina, J., Oppermann, F., Löbig, F. & Günther, T. (2019): Large-scale electrical resistivity tomography in the Cheb Basin (Eger Rift) at an ICDP monitoring drill site to image fluid-related structures. Solid Earth. https://doi.org/10.5194/se-2019-38.</p> <p>The paper contains two types of data:</p> <p>DC resistivity (geoelectrics) ERT data in four profiles<br> -------------------------------------------------------<br> P1, P2 and P3 represent classical multi-electrode ERT data with a unit electrode spacing of a=5m using the Wenner array. They are a representative selection of in total 8 profiles measured in the frame of the (German) MSc work of F. Loebig (there called P2, P5 and P7) where also the lithological section (Fig. 2) was developed:<br> 1. P1 between Lesinka and Hnevin, 620m long<br> 2. P2 around the Hartousov mofette, 700m long<br> 3. P3 between Hartousov and Kacerov, 700m long</p> <p>The inversion results are shown in Fig. 6a,b,c.</p> <p>The large-scale dataset represents data from a dipole-dipole experiment that is in detail described in the paper (Figs. 3-5) with the inversion result given in Fig. 7a along with borehole data.<br> For location see Fig. 1.</p> <p>For all four profiles we provide<br> - measured data with electrode positions on top and the electrode array (abmn) along with the resistance below, topography at the bottom<br> - the configuration file for the inversion software BERT (see https://gitlab.com/resistivity-net/bert), we used version 2.2.9 from January 2019<br> - kml/gpx files denoting the positions of the electrode chains (P1-P3) or an Excel file containing the positions in UTM33N</p> <p>Note that for P2 and the large-scale profile the topography needs to be taken into account whereas it is not necessary <br> Users should be able to reproduce the results by calling<br> bert cfgfile all show</p> <p>Gravity data<br> ------------<br> The data represent a two-column file:<br> 1. position along the ERT profile (projected) in metres<br> 2. Bouguer anomaly in mGal</p> <p>See also special README file in the gravity folder.</p>
Soil moisture determinations by Electrical Resistivity (ERT) Experiment at the Kellogg Biological Station, Hickory Corners, MI (2009)
Dataset AbstractLarge-scale conversion of croplands to perennial biofuel crops could substantially impact regional water, nutrient, and C cycles due to the longer growing seasons and differences in rooting systems compared with most annual crops. However, these differences in crop water use are not well known due to the limited tools available to nondestructively study the spatiotemporal patterns of root water uptake in situ at field scales. Geophysical imaging tools such as electrical resistivity (ER) reveal changes in water content in the soil profile. Data used in: https://doi.org/10.1002/vzj2.20124original data source http://lter.kbs.msu.edu/datasets/222
Post-remediation evaluation of contaminated site using geophysical methods: ERT
<p>The ERT measurements (7 profiles: M1-M7) were performed using the LUND electrical imaging system with a SAS 4000 Terrameter produced by ABEM Malå (Guideline Geo) with 0.5 m electrode separation and the Wenner-Schlumberger configuration. </p> <p>This research was funded by National Science Centre, Poland MINIATURA-5 2021/05/X/ST10/00673 “Post-remediation evaluation of contaminated site using geophysical methods”</p>
Electrical tomography resistivity (ERT) monitoring time series
<p>Multi-temporal electrical tomography resistivity (ERT) measurements for monitoring the performance of the bio-degradable bentonite mat in OAL-Austria. The first measurement was conducted on 30 July 2020 before the implementation of the mat, afterwards seasonal measurement (except for winter due to snow cover) were obtained: 19 Oct 2020, 27 Arpil 2021, 10 August 2021, 4 October 2021, 13 April 2022. A time-lapse inversion algorithm was used to prepare the final results. See OPERANDUM deliverable 4.6 for more details.</p> <p>Device: Lippmann 4point light 10 W</p>
A-ERT and ground temperature data- 2010- Deception Island/Antarctica
<p>Climate induced warming of permafrost soils is a global phenomenon, with regional and site-specific variations, which are not fully understood. In this context, a 2D automated electrical resistivity tomography (A-ERT) system was installed for the first time in Antarctica at Deception Island, associated to the existing Crater Lake site of the Circumpolar Active Layer Monitoring Network (CALM-S). This set-up aims to I) monitor subsurface freezing and thawing processes on a daily and seasonal basis and to map the spatial and temporal variability of thaw depth, and to II) study the impact of short-lived extreme meteorological events on active layer dynamics. In addition, the feasibility of installing and running autonomous ERT monitoring stations in remote and extreme environments such as Antarctica was evaluated for the first time. Measurements were repeated at 4-hour intervals during a full year, enabling the detection of seasonal trends, as well as short-lived resistivity changes reflecting individual meteorological events. The latter is important to distinguish between (1) long-term climatic trends and (2) the impact of anomalous seasons on the ground thermal regime.<br> The A-ERT.txt file contains all ERT surveys which were performed using Wenner electrode configuration. 20 copper plates, which are connected by buried cables to the active boxes, with an electrode spacing of 0.5 m were used in this experiment. This setup yields 56 individual data points for each monitoring data set at six data levels. All data were saved in the Res2Dinv format.<br> The temperature. xlsx file contains air and ground temperatures data during the experiment period. The Air temperature was measured at 160 cm above the surface and ground temperatures in the shallow borehole S3,3 were measured with ibutton-sensors at depths 2.5, 5, 10, 20, 40, 80 and 160 cm.</p>
ERT data collected at the Corona volcano (Lanzarote, Canary Islands) during the European Space Agency (ESA) testing campaign PANGAEA-X 2017
<p>This dataset contains the ERT (Electrical Resistivity Tomography) data collected between 22 and 23 November 2017 at the Corona volcano (Lanzarote, Canary Islands, Fig. 1) for the detection of lava tubes and the stratigraphic investigation of planetary volcanic analogues. This geophysical survey was carried out within the European Space Agency (ESA) testing campaign PANGAEA-X 2017 (Bessone et al., 2018), aimed at integrating astronaut training-data collection, documentation, analogue field geology procedures with remote sensing and in situ geophysical methods. </p> <p>Two ERT profiles were acquired in NE-SW and NNE-SSW orientations (Fig. 1). These were located roughly orthogonal to the Corona lava tube system and as far as possible on top of the main lava tube axes. The longer profile, profile D, is 470 m in length and was obtained using 48 electrodes spaced 10 m apart. The profile orientation is from SW to NE (electrode 1 to 48). The profile was acquired to detect lava tubes in test site D (sub-area south) where the exact location of a lava tube was known thanks to a LiDAR TLS (Terrestrial Laser Scan) subsurface survey (Santagata et al., 2018). A shorter profile, profile E, is 235 m long and was obtained using 48 electrodes 5 m apart. The profile orientation is from SSW to NNE (electrode 1 to 48). This profile was acquired in test site E (sub-area north) to provide a more detailed investigation of the potential existence of inaccessible sections of the tube whose location could be indicated by the evidence of closely-spaced aligned collapse structures.</p> <p>Each profile was collected using measure sequences compounded by 276 Wenner-Schlumberger array quadrupoles which ensure high vertical resolution and signal amplitude and 328 dipole-dipole array quadrupoles which provide enhanced lateral resolution. A fully automatic multi-electrode resistivity meter SYSCAL Jr Switch-48 by IRIS Instruments (400 V max output voltage, 1200 mA max output current, 100 W max output power, <a href="http://www.iris-instruments.com/syscal-juniorsw.html">http://www.iris-instruments.com/syscal-juniorsw.html</a>), was used for data collection.</p> <p>At most of the measurement points, it was necessary to drill the basalt using a hand drilling machine in order to place the tips of the electrodes into the ground at a depth of approximately 40 cm. The electrodes also needed to kept moist to reduce contact resistance between the electrode and the ground. A large amount of water (up to 2 liters per point) was needed for profile D, situated in an area above the lava tubes with very porous dry soil cover.</p> <p>The dataset is presented as a spreadsheet format which has the "space" as separator and the ".txt" extension. The structure of such a file is the following one:</p> <p>#, El array, Spa1/4, Rho, Dev, M, Sp, Vp, In, Time, Spa5/12, M1/20</p> <p>- #: Data point number</p> <p>- El array: Electrode array</p> <p>- Spa. 1/4: four spacing parameters (corresponding to the electrode array – in m)</p> <p>- Rho: resistivity value (in Ohm.m)</p> <p>- Dev: standard deviation (quality factor, in %)</p> <p>- M: global chargeability value (induced polarization parameter (in mV/V – "=0" if only-resistivity data))</p> <p>- Sp: spontaneous polarization (measured just before the injection, in mV)</p> <p>- Vp: measured primary voltage (in mV)</p> <p>- In: injected current intensity (in mA)</p> <p>- Time: injection time (pulse duration, in s)</p> <p>- Spa. 5/8: other spacing parameters (in m)</p> <p>- Spa. 9/12: electrode elevation (in m)</p> <p>- M1/M20: partial chargeability values (induced polarization window (in mV/V – "=0" if only-resistivity data))</p> <p> </p> <p>Acknowledgements</p> <p>The authors are grateful to ESA and all PANGAEA-X 2017 staff, particularly Loredana Bessone, Matthias Maurer, Herve Stevenin and Igor Drozdovskiy for their participation in data collection during some of the experiments and to the MilesBeyond Team, particularly Francesco Maria Sauro for his logistical support. Regional and local remote sensing data were obtained by the Spanish Instituto Geográfico Nacional (https://www.ign.es) and Gobierno de Canarias (https://www.grafcan.es, <a href="https://opendata.sitcan.es/">https://opendata.sitcan.es</a>).</p> <p> </p> <p>References</p> <p>Bessone, L., et al., 2018, Testing technologies and operational concepts for field geology exploration of the Moon and beyond: the ESA PANGAEA-X campaign, Geophysical Research Abstract, #EGU2018-4013.</p> <p>Santagata, T., Sauro, F., Massironi, M., Pozzobon, R., Del Vecchio, U., Lazzaroni, M., Damiano, N., Tonello, M., Tomasi, I., Martínez-Frìas, J. and Mateo Medero, E., 2018. Subsurface laser scanning and photogrammetry in the Corona Lava Tube System, Lanzarote, Spain, EGU General Assembly 2018, pp. EGU2018-5290.</p>
ERT geophysical surveys for detecting gravitational morpho-structures in the Becca France area (Aosta Valley, Italy)
<p>This dataset contains the raw and processed data of an Electrical Resistivity Tomography (ERT) geophysical survey conducted on November 2023 in the Becca France area (Aosta Valley, Italy), in order to help the geological reconstruction of gravitational morpho-structures.</p> <p>It represents the supplementary materials of a publication submitted on Geohazards journal: Forno et al., 2024. Deep electrical resistivity tomography for detecting gravitational morpho-structures in the Becca France area (Aosta Valley, Italy).</p> <p> </p> <p>For details, please refer to the above mentioned publication and to the readme file.</p> <p> </p> <p>7z software (free and open source) can be used to unzip the dataset.</p> <p> </p>
Data and results for manuscript "Imaging groundwater infiltration dynamics in karst vadose zone with long-term ERT monitoring"
<p>This data set contains raw and inverted data from an Electrical Resistivity Tomography (ERT) monitoring experiment conducted over a period of three years at the Rochefort Cave Laboratory (RCL) site in South Belgium. It highlights variable hydrodynamics in the karst vadose zone of Lorette Cave. More conventional hydrological measurements (drip discharge monitoring, soil moisture and water conductivity data sets) are also included in the package, which aims at provide a thorough understanding of the groundwater infiltration. Seasonal changes affect all the imaged areas leading to increases in resistivity in spring/summer attributed to enhanced evapotranspiration, whereas winter is characterised by a general decrease in resistivity associated with a groundwater recharge of the vadose zone. This study provides detailed images of the sources of drip discharge spots traditionally monitored in caves and aims to support modelling approaches of karst hydrological processes.</p>
ERT and topographic profiles from the Sarpang terraces (Bhutan)
<p>This dataset provides data used for Gautier et al. (2024) paper. See reference for details.</p> <p>Electrical Resistivity Tomography profiles at 1 m, 2 m and 5 m electrode spacing with Wenner-Schlumberger (ws) and Dipole-Dipole (dd) geometries.</p> <p>Topographic profiles P0 to P8 from staellite photogrammetry and post-processed to remove vegetation.</p>
Identifying mountain permafrost degradation by repeating historical ERT-measurements - supplement
<p>Ongoing global warming affects the degradation of mountainous permafrost. Permafrost thawing impacts landform evolution, reduces fresh water resources, enhances the potential of natural hazards, and thus has significant socio-economic impact. Electrical resistivity tomography (ERT) has been widely used to map the ice-containing permafrost by its resistivity contrast compared to the surrounding non-frozen medium. We analyse the temporal changes in the resistivity distribution by comparing historical with recently measured ERT profiles. Three periglacial landforms (two rock glaciers and one talus slope) are surveyed in the Swiss and Austrian Alps by repeating historical field campaigns after periods of 10, 12, and 16 years, respectively. The resistivity values have been significantly reduced concerning ice-poor permafrost at all study sites. Interestingly, resistivity values related to ice-rich permafrost in the studied active rock glacier partly increased during the studied time period. To explain this apparent contradictory (in view of observed increase) observation, geomorphological circumstances, such as the relief and creeping behaviour of the active rock glacier, are discussed. Additional remote sensing data indicates an increased velocity in and around the active part with increased resistivity. The present study highlights alpine permafrost degradation resulting from ever-accelerating global warming.</p>
Hydrogeophysical data Schillerslage test site, joint MRT ERT GPR
<p>Dataset of hydrogeophysical Survey at Schillerslage test site including magnetic resonance tomography (MRT), ground-penetrating Radar (GPR) and electrical resistivity tomography (ERT).</p> <p> </p>
Hydrogeophysical Data Spiekeroog, ERT DP
<p>Hydrogeophysical dataset of Spiekeroog (2019, 2021) including electrical resistivity tomography (ERT) and Direct Push (DP) results. </p>
An Open-Label Extension Study of GA-GCB ERT in Patients With Type 1 Gaucher Disease
ClinicalTrials.gov study NCT00635427. IPD Sharing: Not stated. Countries: 11. Publications: 3.
Study of Gene-Activated® Human Glucocerebrosidase (GA-GCB) ERT Compared With Imiglucerase in Type I Gaucher Disease
ClinicalTrials.gov study NCT00553631. IPD Sharing: Not stated. Countries: 9. Publications: 1.
Open-Label Extension Study Evaluating Long Term Safety in Patients With Type 1 Gaucher Disease Receiving DRX008A (ERT)
ClinicalTrials.gov study NCT00391625. IPD Sharing: Not stated. Countries: 3. Publications: 1.
ERT dataset
<p>ERT dataset</p>
Intravitreal ERT to Prevent Retinal Disease Progression in Children With CLN2
ClinicalTrials.gov study NCT05152914. IPD Sharing: NO. Countries: 1. Publications: 4.
ERT data
<p>This dataset contains ERT data.</p>
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