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5,247 results for “cataloguing”
Earthquake Catalogue for: Illuminating the pre-, co-, and post-seismic phases of the 2016 M7.8 Kaikoura earthquake with 10 years of seismicity
<p><strong>0.2: Correction</strong></p> <p>This version corrects the original dataset which had some incorrect focal mechanisms. These mechanisms had incorrect rakes as a result of an error in the uncertainty calculation algorithm. The remainder of the catalogue is unchanged.</p> <p><strong>Code:</strong></p> <p>If you are looking for the code used for this project this is here: <a href="https://zenodo.org/record/5047794#.Y22Mvn5By-Y">https://zenodo.org/record/5047794#.Y22Mvn5By-Y</a> - the link in the paper appears to be wrong as of 11/11/2022.</p> <p><strong>Description</strong></p> <p>Earthquake catalogue generated around the rupture area of the 2016 M7.8 Kaikoura earthquake. For a full description see the associated paper submitted to JGR 2021.</p> <p>The catalogue is here in two forms:</p> <ol> <li>A QuakeML file with all picks, magnitudes, and locations included. This is quite a large file. When reading using ObsPy this will take a long time to read (>10 minutes), and expand in memory to > 8GB.</li> <li>A CSV file with the preferred origin and magnitude information for all events. Relocated events can be identified because they have a station count of 0: GrowClust does not return the number of stations used, whereas NonLinLoc (used for absolute locations) does.</li> </ol>
ARtracks - a Global Atmospheric River Catalogue Based on ERA5 and IPART
<p>The <strong>ARtracks Atmospheric River Catalogue</strong> is based on the ERA5 climate reanalysis dataset, specifically the output parameters "vertical integral of east-/northward water vapour flux". Most of the processing relies on<br>IPART (Image-Processing based Atmospheric River (AR) Tracking, https://github.com/ihesp/IPART), a Python package for automated AR detection, axis finding and AR tracking. The catalogue is provided as a pickled pandas.DataFrame as well as a CSV file.</p> <p>For detailed information, please see <a href="https://github.com/dominiktraxl/artracks">https://github.com/dominiktraxl/artracks</a>.</p> <p>The ARtracks catalogue covers the years from 1979 to the end of the year 2019.</p>
MarsQuakeNet: A More Complete Marsquake Catalogue Obtained by Deep Learning Techniques (Supporting Material, JGR Planets)
<p>Supporting Material (JGR Planets, 2022JE007503) - contains:</p> <ul> <li>Extended marsquake catalogue</li> <li>List of all detections</li> <li>Sol-wise predictions</li> <li>Snapshot of MarsQuakeNet code</li> </ul> <p>MarsQuakeNet code (dynamic version) also available from: https://github.com/niko-d/MarsQuakeNet.git</p>
Ulysses Fossae Crater Catalogue
<p>Catalogue of all craters in Ulysses Fossae, Mars, with a diameter >800m in shapefile format. Craters are mapped on Context Camera (CTX) images, within the Tanaka et al. (2014) unit boundary outlines.</p>
Ulysses Fossae Fault Catalogue
<p>Catalogue of all faults in Ulysses Fossae, Mars, in shapefile format. Faults are mapped on Context Camera (CTX) images, within the Tanaka et al. (2014) unit boundary outlines.</p>
Mediterranean Sentinel-2 Litter Windrows Catalogue (Jun. 2015 - Sept. 2021) v1.0
<p>This dataset contains the <strong>14,374 Litter Windrows detections </strong>found using multispectral Copernicus Sentinel-2/MSI L1c data in the Mediterranean Sea for the period June 2015–September 2021. The dataset includes exclusively the filaments deemed as valid by the research team and used in the main research of the associated research paper. The following information is provided:</p> <ul> <li>Geocentric lat/lon coordinates (WGS84) of the 'centroid' position for the filament</li> <li>(X, Y) coordinates of the filament's centroid related to the multispectral Sentinel-2 image array, when considering all spectral bands resampled at 10m spatial resolution.</li> <li>Number of 10x10m pixels composing the filaments where floating matter has been identified.</li> <li>(X, Y) coordinates for all the detected pixels within the filament and related to the associated Sentinel-2 L1c image at 10m resolution.</li> <li>Original full spectrum (13 bands) for each of the pixels within the filament.</li> <li>Limits of the bounding box (in image (x, y) coordinates at 10m resolution) contain the entire filament.</li> <li>Full name of the Sentinel-2 L1c product containing the filament.</li> <li>Central decimal time (UTC) of the associated Sentinel-2 acquisition.</li> </ul> <p>The file has <strong>netcdf-4 format (NETCDF-CLASSIC)</strong>, with a size of <strong>2 GB</strong>. Note that to maintain structure, the variables related to each pixel in the filament have a size equal to the largest filament in the database. As most filaments are shorter, these variables are padded with dummie values (-999) in all the relevant fields.</p> <p><strong>ncdump </strong>will yield the following information:</p> <pre>netcdf file:/C:/Users/mab_l/Downloads/Science/WASP/WASP_LW_SENT2_MED_L1C_B_201506_202109_10m_6y_NRT_v1.0.nc { dimensions: n_filaments = 14374; box_dims = 4; n_max_pixels_fil = 2563; n_bands = 13; nchar = 65; variables: char s2_product(n_filaments=14374, nchar=65); :long_name = "Copernicus Sentinel-2/MSI L1c product"; :description = "Full name of the Sentinel-2 product where the filament was found."; double dec_time(n_filaments=14374); :description = "Decimal time of the Sentinel-2 acquisition where the filament was found."; :long_name = "Decimal Time"; :units = "year"; :calendar = "gregorian"; :_FillValue = -999.0; // double short x_centroid(n_filaments=14374); :units = "X image coordinate"; :description = "X-axis position of the filament in the S-2/MSI data array at 10m resolution."; :_FillValue = -999S; // short :long_name = "X-axis centroid position"; short y_centroid(n_filaments=14374); :description = "Y-axis position of the filament in the S-2/MSI data array at 10m resolution."; :_FillValue = -999S; // short :long_name = "Y-axis centroid position"; :units = "Y image coordinate"; double lat_centroid(n_filaments=14374); :units = "degrees North"; :axis = "Y"; :description = "Geocentric longitudinal coordinates of the filament (WGS84)."; :long_name = "Latitude"; :_FillValue = -999.0; // double double lon_centroid(n_filaments=14374); :long_name = "Longitude"; :units = "degrees East"; :axis = "X"; :_FillValue = -999.0; // double int n_pixels_fil(n_filaments=14374); :units = "none"; :description = "Number of detected pixels composing the filament."; :long_name = "Number of pixels in filament"; :_FillValue = -999; // int short limits(n_filaments=14374, box_dims=4); :description = "Image coordinates of the bounding box containing the filament [x_lower, y_lower, x_upper, y_upper]"; :coordinates = "n_filaments box_dims"; :units = "(X, Y) image coordinates"; :_FillValue = -999S; // short short pixel_x(n_filaments=14374, n_max_pixels_fil=2563); :units = "X image coordinate"; :coordinates = "n_filaments n_max_pixels_fil"; :description = "X-axis position of the pixels composing the filament in the S-2/MSI data array at 10m resolution."; :long_name = "Pixel x-axis coordinate"; :_FillValue = -999S; // short short pixel_y(n_filaments=14374, n_max_pixels_fil=2563); :description = "Y-axis position of the pixels composing the filament in the S-2/MSI data array at 10m resolution."; :units = "Y image coordinate"; :coordinates = "n_filaments n_max_pixels_fil"; :long_name = "Pixel y-axis coordinate"; :_FillValue = -999S; // short float pixel_spec(n_filaments=14374, n_max_pixels_fil=2563, n_bands=13); :units = "reflectance"; :coordinates = "n_filaments n_max_pixels_fil n_bands"; :description = "Spectral L1c (TOA) reflectance values for pixel and band on the filament."; :long_name = "Pixel Spectra"; :_FillValue = -999.0f; // float // global attributes: :title = "Mediterranean Sentinel-2 Litter Windrows Catalogue (Jun. 2015 - Sept. 2021) v1.0"; :institution = "Barcelona Expert Center (BEC), ICM-CSIC, Barcelona, Spain"; :url = "http://bec.icm.csic.es"; :email = "m.arias@icm.csic.es m.arias@zenithalblue.com"; :copyright = "BEC research products are freely distributed. If these data are used for publication, please \ncite the original research work."; :reference = "https://doi.org/10.5281/zenodo.11045944"; :project = "Mapping Windrows as Proxies for Marine Litter Monitoring from Space (WASP)"; :funding = "ESA contract no. 4000130627, within the Discovery Element of the ESA\'s Basic Activities."; :sensor = "Multi Spectral Instrument (MSI)"; :platform = "Copernicus Sentinel-2A/B"; :license = "This product is distributed under Creative Commons Attribution license (CC BY 4.0).\nYou are free to share and adapt this product under the following terms:You must give appropriate credit (see copyright), \nprovide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in \nany way that suggests the licensor endorses you or your use."; :license_url = "https://creativecommons.org/licenses/by/4.0/"; :Conventions = "CF-1.6"; :time_coverage_start = "20150601T00:00:00"; :time_coverage_end = "20210917T23:59:59"; :geospatial_lat_min = 29.905254805021364; // double :geospatial_lat_max = 45.740728823657236; // double :geospatial_lat_units = "degrees north"; :geospatial_lon_min = -6.703167546213006; // double :geospatial_lon_max = 36.20086905862957; // double :geospatial_lon_units = "degrees east"; :spectral_bands = "B01, B02, B03, B04, B05, B06, B07, B08, B8A, B09, B10, B11, B12"; }<br><br></pre> <p>Please, if you use this dataset, make reference to it in your work: <strong>https://doi.org/10.5281/zenodo.11045944</strong><br>Additionally, please, refer to the original research paper (<strong>Cózar & Arias et al. (2024) 'Proof of concept for a new sensor to monitor marine litter from space', in Nature Communications</strong>)</p> <p>To contact authors about this dataset, please write to<strong> M. Arias (m.arias@zenithalblue.com, m.arias@icm.csic.es) and A. Cózar (andres.cozar@uca.es)</strong>.</p>
Catalogue of metal urns discovered in Europe (14th - 2nd centuries BC)
<p>This dataset provides a list of archaeological sites that have provided metal cinerary urns. These occurrences were used for the doctoral thesis defended in December 2020, entitled "L'usage des textiles dans les pratiques funéraires : le cas des incinérations en urns métallique en Europe au Ier millénaire av. J.-C." (The use of textiles in funerary practices: the case of cremation in metal urns in<br>Europe in the 1st millennium BC) (Paris, Sorbonne University). It represents a current state of art and needs to be supplemented and expanded by future work and research.</p> <p>This dataset also constitutes the basis of the following two articles:<br>- Desplanques E. (2022). Protohistoric metal-urn cremation burials (1400–100 BC): a pan-European phenomenon. Antiquity 96(389):1162-1178. https://doi.org/10.15184/aqy.2022.109<br>- Desplanques E. (2022). Les textiles dans les tombes gauloises à dépôt de crémation en vase métallique : usages pratiques, mises en scène et perspectives anthropologiques (seconde moitié du VIe s.-V e s. av. J.-C.). Gallia, 79(2):1-25. https://doi.org/10.4000/gallia.6684</p>
Euclid Early Release Observations of Abell 2390 & 2764: NISP-selected photometry and photometric redshift catalogue
<p><strong>Euclid Early Release Observations 'Magnifying Lens' (PI: Atek)</strong><br><strong>Elementary Photometric Catalogues and Photometric Redshifts</strong></p> <p>Version 1.0.0</p> <p>Authors: J. Weaver (UMass), S. Taamoli (UCR), and H. Atek (IAP)<br>Contact: john.weaver.astro@gmail.com</p> <p>If you use this work, please cite:</p> <p>Survey Paper: Atek et al. 2024<br>Processing Paper: Cuillandre et al. 2024<br>Demonstration Paper: Weaver et al. 2024</p> <p>While photometric redshfits are provided, we caution that they are derived from only four optical-NIR bands and are designed for high-z dropout galaxies. Users may encounter issues at lower redshifts.</p> <p>These files are provided 'as is'. We the authors retain the right to modify the files at any time.</p> <p>Please see the dedicated README file for details.</p>
294B in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
294B. Bolitoglossa orestes. La Bravera, way from Mérida to La Azulita, Mérida, near type locality of the synonym B. spongai. Photo: César Barrio-Amorós.
282 in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
282. Pristimantis yuruaniensis. Female. Summit of Yuruani-tepui, Bolívar. Photo: César Barrio-Amorós.
279D in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
279D. Pristimantis vanadisae. Juvenile, spotted pattern. Estancia La Bravera, way from Mérida to La Azulita, 2,200 m asl, Mérida. Photo: César Barrio-Amorós.
279C in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
279C. Pristimantis vanadisae. Female, pattern dorsoconcolor. Estancia La Bravera, way from Mérida to La Azulita, 2,200 m asl, Mérida. Photo: César Barrio-Amorós.
279A in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
279A. Pristimantis vanadisae. Female, pattern plain. Estancia La Bravera, way from Mérida to La Azulita, 2,200 m asl, Mérida. Photo: César Barrio-Amorós.
275. Pristimantis sarisarinama. Paratopotype EBRG 4674 in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
275. Pristimantis sarisarinama. Paratopotype EBRG 4674. Sima Mayor Sarisariñama-tepui, Bolívar. Photo: César Barrio-Amorós.
272A. Pristimantis rivasi. Female holotype MHNLS 18445 in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
272A. Pristimantis rivasi. Female holotype MHNLS 18445. Cerro Las Antenas, Sierra de Perijá, Zulia. Photo: Tito Barros.
280B in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
280B. Pristimantis vilarsi. Female. Tobogán de la Selva, near Puerto Ayacucho, Amazonas. Photo: Zelimir Cernelic.
273B in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
273B. Pristimantis riveroi. Amplexus. Rancho Grande, Henri Pittier National Park, Aragua. Photo: Andrés González.
297 in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
297. Microcaecilia rabei. Imataca Forestal Reserve, Bolívar-Delta Amacuro boundary. Photo: Fernando Rojas-Runjaic.
268A in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
268A. Pristimantis paramerus. Quebrada del Padre, way to páramo Los Granates, Mérida. Photo: César Barrio-Amorós.
270B in Catalogue of the amphibians of Venezuela: Illustrated and annotated species list, distribution, and conservation
270B. Pristimantis pleurostriatus. Juvenile. Estancia La Bravera, way from Mérida to La Azulita, 2,200 m asl, Mérida. Photo: César Barrio-Amorós.
ScienceDex guides
Understand access before you commit
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)
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.