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Ejecta Thickness Measurements at Small Lunar Craters
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Craters of Habit: Patterns of Deformation in the Western Galápagos
<p>Datasets used in Reddin et al., Craters of Habit: Patterns of Deformation in the Western Galápagos.</p> <p>LiCSBAS output files [in .h5 format] used in this study are provided, given by 128Dcum_filt.h5 for descending, and 106Acum_filt.h5 for ascending. These files contain displacement maps for both Isabela and Fernandina, and are used to produce time series, and conduct source modelling. </p> <p>.txt files contain time series information for their corresponding volcano, with track direction included [e.g. Darwin_Asc.txt].</p> <p>Text files not beginning with Alcedo or Darwin contain time series of the 2020 eruption of Fernandina, with the location of the time series point, and corresponding track direction included in the title [e.g. NEFlank_ts_A.txt].</p>
Supporting Data for Martian Dynamo Change at ~4.1 Ga: Evidence from the Magnetic Measurements of the Iota Crater
<p><a href="https://zenodo.org/api/records/14257490/draft/files/MAG_MAVEN_NIGHTTIME.txt/content" target="_blank" rel="noopener noreferrer">MAG_MAVEN_NIGHTTIME.txt</a> contains magnetic field from MAVEN nighttime tracks across the study area;</p> <p><a href="https://zenodo.org/uploads/14257490" target="_blank" rel="noopener noreferrer">TOPOGRAPHY_CRUST_AB.txt </a> contains the topography and crustal thickness data in Figure 2;</p> <p><a href="https://zenodo.org/api/records/14257490/draft/files/MAGNETIC_MODEL_CALCULATION.csv/content" target="_blank" rel="noopener noreferrer">MAGNETIC_MODEL_CALCULATION.csv</a> contains the <span>normalized circumferential averaged magnetic field upon the impact crater with different diameters and internal magnetizations, which are calculated randomly one hundred times in each case.</span></p>
Petrophysical data for 29 samples from the Chicxulub impact crater.
<p>Note: ɸ-porosity, ρ<sub>b</sub>-bulk density, ρ<sub>g</sub>-grain density, k-permeability, F-formation factor, m-cementation exponent, τ<sup>2</sup>-tortuosity, C<sub>s</sub>-surface conductivity, Vp-acoustic velocity of compressional waves. Uncertainty for porosity, density, permeability, velocity and conductivity is 5%. Uncertainty for formation factor, cementation exponent and tortuosity is 8%). Lith <sup>1 </sup>and Unit <sup>1</sup> after Morgan et al. (2017), Unit <sup>2</sup> after de Graaf et al. (2021, UIM-upper impact melt rock unit, LIMB-lower impact melt rock-bearing unit)) and Kaskes et al. (2021).</p> <p> </p> <p>Morgan, J. V., Gulick, S. P. S., Bralower, T. J., Chenot, E., Christeson, G. L., Claeys, P., et al. (2016). The formation of peak rings in large impact craters. Science, 354(6314), 878–882. <a href="https://doi.org/10.1126/science.aah6561">https://doi.org/10.1126/science.aah6561</a></p> <p>de Graaff, S. J., Kaskes, P., Déhais, T., Goderis, S., Vinciane, D., Ross, C. H., et al. (2021). New insights into the formation and emplacement of impact melt rocks within the Chicxulub impact structure, following the 2016 IODP-ICDP Expedition 364. Geological Society of America Bulletin. <a href="https://doi.org/doi:">https://doi.org/doi:</a> <a href="https://doi.org/10.1130/B35795.1">https://doi.org/10.1130/B35795.1</a></p> <p>Kaskes, P., de Graaff, S. J., Feignon, J. G., Déhais, T., Goderis, S., Ferrière, L., et al. (2021). Formation of the crater suevite sequence from the Chicxulub peak ring: A petrographic, geochemical, and sedimentological characterization. Geological Society of America Bulletin. <a href="https://doi.org/https://doi.org/10.1130/B36020.1">https://doi.org/https://doi.org/10.1130/B36020.1</a></p>
The Effects of Terrain Properties upon the Small Crater Population Distribution at Giordano Bruno: Implications for Lunar Chronology
<p>Derived data files from Williams et al. (2022) The Effects of Terrain Properties upon the Small Crater Population Distribution at Giordano Bruno: Implications for Lunar Chronology, submitted.</p>
Martian Frost in HiRISE Observations of Northern Mid-Latitude Craters
<p>This dataset contains a labeled set of High Resolution Imaging Science Experiment (HiRISE) image tiles that either do or do not contain visible indications of frost presence. The dataset was created using Labelbox to draw polygonal annotations over subframes extracted from HiRISE observations. Then, each subframe was broken into 299x299 pixel tiles at 0.5 m/pixel resolution, and a majority vote across annotations is used to determine whether each tile is given a "frost," "background," or "ambiguous" label. Ambiguous labels are assigned if there is not a majority agreement about the label of the tile given the polygons. All tiles from "background" subframes (taken during summer months when no frost is present) are assigned a "background" label. Corresponding to each tile is a JSON label file containing metadata from overlapping annotations. There is also a TensorFlow TFRecord object saved for each subframe that contains the set of all tiles extracted from that subrame.</p>
Dataset of the research article "A semi-automated analysis of displacement-to-length scaling of the grabens affecting lunar Floor-Fractured craters"
<p>This dataset includes all the raster data (DEM, orthoimage, slope) and vectors (shapefiles) used in our research, investigating the relationships between displacement and length of the faults affecting Lunar Floor-Fractured craters.</p>
Supplemental information data from: "Evidence for amorphous sulfates as the main carrier of soil hydration in Gale crater, Mars"
<p>This dataset includes the target name and chemical composition of each ChemCam sequence used in the above-mentioned article. The quantification for each ChemCam spectrum in the soils of the Bradbury, Rocknest and Yellowknife Bay area are in percentage mass fractions (wt.%) for most major oxides (i.e., SiO2, TiO2, Al2O3, FeOT , MgO, CaO, Na2O, K2O). Sulfur and hydrogen abundances are expressed respectively in peak area (normalized) and ICA H scores.</p>
Mur del volcà Puig del Roser. Espai Crater
Wall that was part of an ancient volcano in the Espai Crater science museum in Olot, Catalonia. https://espaicrater.com/ Captured and trimmed with Trnio-Plus. Source: Objaverse 1.0 / Sketchfab
Dataset for the manuscript "Amapari Marker Band Metal-Enrichments: Potential Mechanisms and Implications for Surface and Subsurface Water and Weathering in Gale crater"
<p>The dataset for the main manuscript contains three CSV files: list of long distance remote micro images (LDRMIs), the ChemCam chemical data, and the alpha particle X ray spectrometer (APXS) chemical data. The LDRMI csv lists two sets of data, one for the sol (Mars solar day), sequence identifier, and target name of LDRMIs that target the Amapari Marker Band (AMB). These are represented as green points on manuscript Figure 1. The second list are for LDRMI images that did not specifically target the AMB, but contain the AMB, and these are orange points on manuscript Figure 1. The ChemCam data file has metadata for each observation point in a ChemCam target: file name, spacecraft clock, observation number, stratigraphic member, rock type, target distance, and total of all spectral channels. Chemical information includes: the oxide chemistry (oxide wt%), uncertainty (RMSEP accuracy and shot-to-shot precision), minor element quantification, and minor element uncertainty (ppm), preliminary sulfate composition (without uncertainty and only provided up to sol 3778), peak areas for some elements (Cu, Zn, and Cr). The oxide sum includes all oxides and elements for which we have quantitative data. Spectral unmixing qualitative values are listed for each element. Derived data includes the corrected MgO, Na<sub>2</sub>O, and CaO in both mol and oxide wt% (values before and after correction are provided), and the calculated alteration index. Derived data is only calculated for AMB bedrock targets (does not include veins or mixed vein-rock targets with elevated CaO). The APXS data sheet provides sol, target name, oxide data, and uncertainties for the drill tailings observations, and the derived data for each target.</p>
Surface dust coverages on rock targets in Gale crater: Influence of seasonal wind variability, elevation and proximity to aeolian sand fields.
<p>The following dataset accompanies the paper submission to AGU - JGR: Planets for the paper titled: "</p> <p><span>Surface dust coverages on rock targets in Gale crater: Influence of seasonal wind variability, elevation and proximity to aeolian sand fields."</span></p>
Derived environmental temperatures at Jezero crater from Air Temperature Sensors' measurements on the Perseverance rover.
<p><strong>Material from Version 2</strong> extends derived Air Temperature Sensor data to the first 700 sols of the Mars 2020 mission used in the analysis of <em>Munguira et al. (2024). "One Martian Year of Near-Surface Temperatures at Jezero from MEDA measurements on Mars2020/Perseverance". Journal of Geophysical Research: Planets. [in revision]. </em>We also include the tables needed to generate and reproduce the figures in the paper. Most importantly, the tables include the results from different analyses of temperatures through Fourier series and Reynolds averaging. </p>
A catalogue of impact craters with diameters larger than 200 m in the Chang'e-6 landing area
<p>Chang'e-6 (CE-6) is the first sample-return mission from the lunar farside and will be launched in May of 2024. The landing area is in the south of Apollo basin inside the South Pole Aitken basin. Statistics and analyses of impact craters in the landing area are essential to support safe landing and geologic studies. This dataset is craters with diamters larger than 200m in the 134 km × 246 km landing area. The craters are extracted by an automated method and checked manually. </p>
Image data of bright deposits in permanently shadowed craters on Ceres
<p>These are image data described in "Spectral properties of bright deposits in permanently shadowed craters on Ceres" by Schröder et al., published as Astronomy & Astrophysics 688 (2024) A178, doi:10.1051/0004-6361/202450247. The data correspond to the permanently shadowed craters on Ceres shown in Figs. 2 to 6 in the paper.</p> <p>There is a data set for each of the following permanently shadowed regions: NP04, NP05, NP07, and SP01. Each data set consists of 4 parts: (1) unprojected images in IMG format (header + binary), (2) unprojected images in FITS format, (3) projected images in IMG format, and (4) projected images in FITS format. The images contain reflectance values (I/F) in floating-point format. They are corrected for in-field stray light and have been registered to a global shape model to correct minor pointing errors. The data files are equipped with a rudimentary header.</p> <p>File name syntax: In "FC21B0045550_15282040820F2D.IMG", "FC2" is the camera model, "45550" is the image number, and "F2" is the filter.</p>
iSALE Datasets of "Evidence for magnetized ejecta deposits on the Moon based on observations of demagnetized craters"
<p>The input data (*.inp) is used for iSALE impact simulation for the four craters (Chaplygin, Keeler, Gauss, and Fermi) and the output data (*.dat) are its result.</p>
Supplementary Dataset for "Grain Size Measurements of the Eolian Stimson Formation, Gale Crater, Mars and Implications for Sand Provenance and Paleoatmospheric Conditions"
<p>Grain size measurements and results in support of "Grain Size Measurements of the Eolian Stimson Formation, Gale Crater, Mars and Implications for Sand Provenance and Paleoatmospheric Conditions".</p> <p>The subfolder "MAHLI images" consists of images taken by the Mars Science Laboratory <em>Curiosity</em> Mars Hand Lens Imager; these images are accesible via the MSL Analyst's Notebook at an.rsl.wustl.edu.</p> <p>The subfolder "ImageJ ROIs" contains .zip files that can be opened with the ImageJ software, available at imagej.nih.gov/ij.</p> <p>The subfolder "GRADISTAT results" contains PDFs with grain size statistics that were created from the data in "Grain size measurements" using the GRADISTAT software, available at https://doi.org/10.1002/esp.261. </p>
CRESENT: a CRatEr-baSed pose estimation datasEt for cisluNarlocated spacecrafT
<h3>CRESENT is first introduced in the paper “Robust Perspective-n-Crater for Crater-based Camera Pose Estimation” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops.</h3> <p><strong>Overview:</strong></p> <p>This dataset contains images produced by The University of Adelaide using PANGU Planet Surface Simulation Software developed by the Space Technology Centre at the University of Dundee, Scotland.</p> <p>High-resolution lunar DEMs from the PDS data node were rendered in PANGU, and images were taken above the lunar surface at an altitude of 100km with varying angles off nadir to mimic the expected conditions of a lunar orbiter surface surveillance mission.</p> <p>The dataset contains images taken above four different surface regions on the Moon, each within a region of 45 degrees latitude and 45 degrees longitude.</p> <p><strong>Data organisation:</strong></p> <p>There are four root folders, each containing images produced under one of the four lunar regions:</p> <p><em>LDEM_x_yE_l_mN/</em></p> <p>where x and y are the latitude bounds (degrees) of the lunar region and l and m are the longitude bounds (degrees) of the lunar region, rendered in PANGU. Note that due to the high resolution of the DEMs, any region of the Moon that was outside these latitude and longitude bounds was not rendered (and the surface will appear cut off/black at the boundaries of these regions).</p> <p>Within each of the lunar region folders, there are seven subfolders:</p> <p><em>LDEM_x_yE_l_mN_float_60fov_1024_1024_ideg_off_nadir/</em></p> <p>where i is the viewing angle (degree) off nadir the image was taken at, where i is either 0, 10, 20, 30, 40, 50, or 60 degrees. Each subfolder contains a folder of images, a poses.csv file of ground truth poses, a calibration file and a file detailing the specifics of the rendered LDEM. Note that each image taken within each sub-directory of each lunar region folder will have the same number of files, each located at the same position in the Selenographic reference frame, but at different angles off nadir. For example,<em> LDEM_-90_-45E_0_45N/LDEM_-90_-45E_0_45N_float_60fov_1024_1024_0deg_off_nadir/</em> and <em>LDEM_-90_-45E_0_45N/LDEM_-90_-45E_0_45N_float_60fov_1024_1024_60deg_off_nadir/</em> will both have the same number of images in their <em>images/</em> subdirectory, and each image file number in these directories was taken at the same camera position, but at viewing angles of 0 degrees and 50 degrees off nadir, respectively.</p> <p>Each line in the poses file contains the X, Y, Z position (m) and the yaw, pitch, roll angles (degrees) of the camera in the selenographic reference frame. There are the same number of lines in the poses file as images in each subfolder, e.g., the first line of the poses file corresponds to the XYZ yaw pitch roll pose of the camera that generated <em>images/0.png</em>, the second line of the poses file corresponds to the pose of the camera of <em>images/1.png</em>, etc.</p> <p><strong>How to cite:</strong></p> <p>Users of this dataset are requested to cite the following paper.</p> <p>Reference String</p> <p><em>McLeod, S. et al. Robust Perspective-n-Crater for Crater-based Camera Pose Estimation in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops (June 2024)</em></p> <p>Bibtex</p> <p><code>@InProceedings{Mcleod_2024_CVPR,</code></p> <p><code>author = {Mcleod, Sofia and Chng, Chee Kheng and Ono, Tatsuharu and Shimizu, Yuta and Hemmi, Ryodo and Holden, Lachlan and Rodda, Matthew and Dayoub, Feras and Miyamoto, Hirdy and Takahashi, Yukihiro and Kasai, Yasuko and Chin, Tat-Jun}, </code></p> <p><code>title = {Robust Perspective-n-Crater for Crater-based Camera Pose Estimation}, </code></p> <p><code>booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, </code></p> <p><code>month = {June}, </code></p> <p><code>year = {2024}, </code></p> <p><code>pages = {6760-6769} </code></p> <p><code>}</code></p> <p><strong>DISCLAIMER</strong>:</p> <p><em>The dataset provided is a lower resolution version of the original and is intended for academic research purposes only, consistent with the terms of the Open Access License that applies to the usage of this dataset. Please contact <a href="mailto:tat-jun.chin@adelaide.edu.au">tat-jun.chin@adelaide.edu.au</a> if you require the higher resolution versions of the dataset.</em></p>
Crater diameter of granular polystyrene layer with various diameter of grains and Weber number of water droplet
<p>Datas about experiments of impacts made in 2021-2023. A water droplet impacting a polystyrene granular layer of 4 differents grains diameters. These datas give the crater diameter obtain in function of the Weber number of the droplet. A file from tomography of the granular layer before impact is added.</p>
Digitization, Georeferencing, and Modelling of Regan and Hinze's Barringer Crater Study
<p>This is a digitized data set of Regan and Hinze's (1975) Gravity and Magnetic Survey of Meteor Crater, AZ, also known as Barringer Crater, AZ. This data is interpolated from figures within the paper pertaining to the Residual Bouguer Anomaly, Total Bouguer Anomaly, Regional Bouguer Anomaly, and Terrain Correction, as the paper's original data set could not be recovered. We georeferenced the station coordinates to latitude/longitude and Zone 12 UTM coordinates using a LiDAR DEM in order to provide an updated terrain correction for the data set.</p>
raw crater counts for layered ejecta craters
<p>JMARS .jlf shape files that contain the measurement area polygon and crater measurements (diameters, center lat/lon, and a degradation classification). And .csv files of crater measurements. Names of files indicate the region for the counts. See associated publication for descriptions of those regions.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.