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751 results for “geology”
U.S. Geological Survey Aerial Photography
The U.S. Geological Survey (USGS) Aerial Photography data set includes over 2.5 million film transparencies. Beginning in 1937, photographs were acquired for mapping purposes at different altitudes using various focal lengths and film types. The resultant black-and-white photographs contain less than 5 percent cloud cover and were acquired under rigid quality control and project specifications (e.g., stereo coverage, continuous area coverage of map or administrative units). Prior to the initiation of the National High Altitude Photography (NHAP) program in 1980, the USGS photography collection was one of the major sources of aerial photographs used for mapping the United States. Since 1980, the USGS has acquired photographs over project areas that require photographs at a larger scale than the photographs in the NHAP and National Aerial Photography Program collections.
First year geology students experience of geologic time video- and audio metadata
<p>This dataset contains data collected and used for the master thesis <a href="http://lup.lub.lu.se/student-papers/record/9025735"> “One simply fills it with more information”: a phenomenographic study on students’ experience of geological time</a> by Jennie Lundqvist Department of Geology, Lund University, Sweden. The dataset consists of questionnaire answers, audio- and video recordings from three interviews, collected illustrations and materials that were used during the interviews. The interviews were recorded by two to three cameras (GoPro Hero 6) and several microphones (WS-852). The interviews were conducted at a university in southern Sweden with six first year geology students during the period fall 2019 and winter 2020. Due to the Swedish curriculum the students in this study have limited previous knowledge of earth science as a subject. The students had used the Earth: Portrait of a Planet by Stephen Marshak 6th edition in their first geology course.</p> <p>151 GB of collected data divided up on video files, audio files, scanned images, photos, transcriptions, word files and pdf.</p> <p>The actual data cannot be published since it contains personal information and the consent form does not allow for the construction of an anonymised dataset.</p>
3-component synthetic seismograms associated with highly heterogeneous geologies
<p>This dataset has been generated by propagating seismic waves in heteroegenous geologies. Geologies are 3D domains of size 9.6 x 9.6 x 9.6 km. The source is placed at (4.8km, 4.8km, -8.4km). It is parametrized as a moment tensor with M<sub>0</sub> = 2.47 · 10<sup>16</sup> N.m, strike = 48°, dip = 45°, and rake = 88°.</p> <p>The propagation of seismic waves is simulated with <a href="https://github.com/sem3d">SEM3D</a>, a High-Performance Code based on the Spectral Element Method. The simulation lasts for 20s.</p> <p>Ground motion is recorded at the surface by a grid of 16 x 16 sensors (600m spacing between two consecutive sensors). This dataset contains velocity timeseries for the sensor located at coordinates (1390m, 1390m). There are 3 timeseries associated with the three components (EW = East-West, NS = North-South, Z = upward). Timeseries are given at a 100Hz frequency.</p> <p>Due to the definition of the mesh elements in the numerical simulation, results are accurate only up to a 5Hz frequency. Timeseries still contain frequencies above 5Hz but they have no physical meaning.</p> <p>Each file is given as a numpy array. Each row corresponds to one numerical simulation (i.e. one geology). Columns correspond to the time steps (0, 0.01, 0.02, ..., 19.98, 19.99).</p>
Addressing infrastructure challenges posed by the Harwich Formation through understanding its geological origins - dataset
<p>The dataset contains borehole records and laboratory test results from PhD research titled 'Addressing infrastructure challenges posed by the Harwich Formation through understanding its geological origins' by J. Edgar.</p>
Clustering has a meaning: optimization of angular similarity to detect geometric anomalies in geological terrains - Input and processed data.
<p>This companion dataset relates to the manuscript "<strong>Clustering has a meaning: optimization of angular similarity </strong></p> <p><strong>to detect geometric anomalies in geological terrains</strong>", by</p> <p>Michał P. Michalak, Lesław Teper, Florian Wellmann, Jerzy Żaba, Krzysztof Gaidzik, Marcin Kostur, Yuriy P. Maystrenko, Paulina Leonowicz</p> <p>The archive contains the input and processed data. The input data contains XYZ coordinates of points documenting the investigated interfaces. The output files contains calculated orientations and coordinates of vectors. The output files can be processed in RStudio.</p>
Synthetic geophysical survey using geological modelling from the Yerrida Basin (Western Australia)
<p>This is a companion dataset to the manuscript:</p><p>"Towards geologically reasonable lithological classification from integrated geophysical inverse modelling", by J. Giraud, M. Lindsay, M. Jessell, and V. Ogarko.</p><p>This dataset contains the true model, the geological uncertainty volume constraining inversion, the starting model for inversion, and the inverted model. It also contains the inverted geophysical data. The inverted data were generated using geological modelling from the area and prior petrophysical information (more information in the above-mentioned document). For standalone usage of this dataset, the inversion parameters can be found in the following publication: </p><p>Giraud, J., M. Lindsay, V. Ogarko, M. Jessell, R. Martin, and E. Pakyuz-Charrier, 2019a, Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization: Solid Earth, 10, 193–210.</p>
The application of XRF scanning to different geological archives
<p>For this datasets we further our efforts using high resolution XRF scanning method on loess, stalagmite, and tridacna samples to illucidate which elements can be robustly obtained by XRF scanning, focusing on reproducibility, and the major factors (settings, scanning path, resolution) influencing the results for each three archives. </p>
Synthetic datasets used for numerical testing of geology-geophyiscs integration
<p>This datasets is a companion dataset to the manuscript "<strong>Integration of automatic implicit geological modelling in geophysical inversion with posterior topological analysis</strong>", by Jérémie Giraud, Guillaume Caumon, Lachlan Grose, Vitaliy Ogarko, and Paul Cupillard, for publication in Solid Earth. <br> </p> <p>It contains models and data shown in the paper that are not available elsewhere.<br> <br> The folder organisation is as follows, where <strong>bold</strong> refers to folders and subfolders, and text in <em>italic</em> corresponds to a succinct description of the contents.</p> <p> </p> <p>|-- <strong>synthetic 1 </strong>> <em>synthetic dataset and results for the first synthetic example</em><br> | |-- <strong>geol_data_layered_model.pckl </strong>> <em>geological data and model</em><br> | |-- <strong>grav_data_synthetic1.pckl </strong>> <em>gravity data produced by the true model</em><br> | |-- <strong>inverted_model_no_correction.txt </strong>> <em> inversion results</em><br> | |-- <strong>inverted_model_with_correction.txt </strong>> <em> inversion results</em><br> | |--<strong> note.txt </strong>> <em> metadata</em><br> | |--<strong> starting_model.txt </strong>> <em> starting model for inversion</em><br> | |--<strong> true_model.txt </strong>> <em> true model</em><br> <br> |-- <strong>synthetic 2 </strong>> <em>synthetic dataset and results for the second synthetic example</em><br> | |-- <strong>case<num>.pckl </strong>> <em>inversion results for case with number 1..5 as in the manuscript</em><br> | |-- <strong>grav_data_synthetic2.pckl </strong>> <em>gravity data produced by the true model</em><br> | |-- <strong>inverted_model_no_correction.txt </strong>> <em> inversion results</em><br> | |-- <strong>inverted_model_with_correction.txt </strong>> <em> inversion results</em><br> | |--<strong> note.txt </strong>> <em> metadata</em><br> | |--<strong> starting_model_case5.txt </strong>> <em> starting_model_case5</em><br> | |--<strong> model_start_unconformity.pckl </strong>> <em> starting model for inversion, cases 1..5.</em><br> | |--<strong> true_mod_geol_data.pckl </strong>> <em> true model and geological data</em><br> | |--<strong> start_model_and_geol_data.pckl </strong>> <em> starting geological model and corresponding geological data</em></p> <p> </p>
Geological data of the White Sea glendonites
<p>The dataset provides information about Bivalves found within concretions with glendonites; mineralogical, geochemical and isotopic composition of the studied samples. </p>
A new methodology using borehole data to measure angular distances between geological interfaces - Input and processed data
<p>This companion dataset relates to the manuscript "<strong>A new methodology using borehole data to measure angular distances between geological interfaces</strong>", by</p> <p>Michał P. Michalak<sup>a,b,</sup><a href="#sdfootnote1sym"><sup>1</sup></a>, Paweł Marzec<sup>b,</sup><a href="#sdfootnote2sym"><sup>2</sup></a>, Filip Turoboś<sup>c,</sup><a href="#sdfootnote3sym"><sup>3</sup></a>, Paulina Leonowicz<sup>d,</sup><a href="#sdfootnote4sym"><sup>4</sup></a>, Lesław Teper<sup>a,</sup><a href="#sdfootnote5sym"><sup>5</sup></a>, Paweł Gładki<sup>e,</sup><a href="#sdfootnote6sym"><sup>6</sup></a>, Michael J. Pyrcz<sup>f</sup><sup>,</sup><a href="#sdfootnote7sym"><sup>7</sup></a>,</p> <p>Mariusz Szubert<sup>g,</sup><a href="#sdfootnote8sym"><sup>8</sup></a></p> <p><a href="#sdfootnote1anc">1</a> Michał Michalak devised the project, wrote the manuscript, performed the computations and discussed the results.</p> <p><a href="#sdfootnote2anc">2</a> Paweł Marzec conducted the geological interpretation and discussed the results.</p> <p><a href="#sdfootnote3anc">3</a> Filip Turoboś conducted the statistical analysis.</p> <p><a href="#sdfootnote4anc">4</a> Paulina Leonowicz prepared the chapter about stratigraphy.</p> <p><a href="#sdfootnote5anc">5</a> Lesław Teper prepared the chapter about regional geology.</p> <p><a href="#sdfootnote6anc">6</a> Paweł Gładki participated in the study conceptualisation (discussion about distance functions)</p> <p><a href="#sdfootnote7anc">7</a> Michael Pyrcz discussed the applications of the method and revised the statistical section.</p> <p><a href="#sdfootnote8anc">8</a> Mariusz Szubert was responsible for the data acquisition.</p> <p>The archive contains the input and processed data. The input data contains XYZ coordinates of points documenting the investigated interfaces. The output files contains calculated orientations and coordinates of vectors. The output files can be processed in RStudio.</p>
Dataset for SPBM tunnel geological condition prediction
<p>This is the operational data collected during the construction of the He Yan Road river crossing project and the corresponding geological information.</p>
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.