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270 results for “craters”
Chang'e-6 nearby craters within a 1 km diameter and the simulated craters
<p><a href="https://zenodo.org/api/records/13997862/draft/files/CE6_NAC_1km_Circle.txt/content" target="_blank" rel="noopener noreferrer">CE6_NAC_1km_Circle.txt</a> : text file for the craters within a 1-kilometer diameter circle across the CE-6 landing site</p> <p><a href="https://zenodo.org/api/records/13997862/draft/files/producd%20craters.zip/content" target="_blank" rel="noopener noreferrer">producd craters.zip</a> : the generated primary and secondary craters in the four period models (2.4-3.0 Ga). In the each numpy file, the data are saved in a 6*n materix, including the craters diameter, x&y position in pixel, craters indentifier (1 for primary and <1 for the secondary), generated time steps and their impactors, sequentially.</p>
Data from: Brine driven destruction of clay minerals in Gale crater, Mars
<p><span><span><span><span><span><span><span><span><span><span><span>This repository contains files and non-commercial software associated with the journal article "Brine Driven Destruction of Clay Minerals in Gale Crater, Mars.<strong>" </strong></span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>The article presents mineralogical, geochemical, and sedimentological observations made by the Mars Science Laboratory rover <em>Curiosity </em>in an area called Glen Torridon, Gale crater, Mars. Rocks exposed in Glen Torridon were deposited in a lake that occupied the floor of Gale crater about 3.5 billion years ago and are stratigraphic and depositional equivalents of rocks exposed ~ 400m away on Vera Rubin ridge. The mineralogy of rocks in these two areas are different despite forming in the same lake at the same time. Glen Torridon rocks contain about 30 wt % clay minerals and 2 wt % or less of the mineral hematite (an iron oxide). In contrast, Vera Rubin ridge rocks contain 5 to 13 wt % clay minerals, with larger quantities (between 9 and 16 wt %) of iron oxide and oxyhydroxide minerals. The observed differences in mineralogy are attributed to preferential post-depositional alteration of Vera Rubin ridge rocks by silica-poor brines. These brines are thought to have formed during the deposition of sedimentary strata of the 'sulfate-bearing unit' that overlie Glen Torridon and Vera Rubin ridge rocks. Orbital spacecraft have detected magnesium sulfates in the sulfate-bearing unit. The presence of these highly soluable salts imply that changing climate and/or hydrological conditions in Gale crater resulted in the formation of dense brines during deposition of the sulfate-bearing unit. It is hypothesized that brines infiltrated older clay-bearing sediments, converting iron-rich clay minerals to iron oxides and oxyhydroxides. Glen Torridon rocks also contain a mineral phase not previously identified on the mission. This mineral gives rise to a distinctive x-ray diffraction peak represents a interplanar spacing of 9.22 angstroms. This phase is identified as a mixed-layer serpentine-talc and is thought to have been transported into the crater floor by rivers.</span></span></span></span></span></span></span></span></span></span></span></p> <p>This repository contains:</p> <p>- Files needed to perform mineral search and Rietveld refinement of measured x-ray diffraction data using <span><span><span><span><span><span><span><span><span><span><span>BGMN and MDI Jade software.</span></span></span></span></span></span></span></span></span></span></span> </p> <p>- A non-commerical Excel-based program called FULLPAT, used for mineral and x-ray amorphous quantification of x-ray diffraction patterns collected by the CheMin instrument aboard <em>Curiosity. </em></p> <p><em>- </em>Python code that was used to identify the 9.22 angstrom phase through automated search the American Mineralogist Crystal Structure Database.</p> <p>- Collection times of Alpha Particle X-ray Spectrometer analyses of bulk rock geochemical presented in the article that can be used to retrieve raw data from NASA's Planetary Data system (<span><span><span><span><span><span><span><span><span><span><span>https://pds-geosciences.wustl.edu/msl/msl-m-apxs-4_5-rdr-v1/mslapx_1xxx/extras/)</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span><span>- A compilation of Li abundances across Vera Rubin ridge and Glen Torridon measured by the ChemCam that were presented in the article and used as a proxy for rock clay mineral content.</span></span></span></span></span></span></span></span></span></span></span></p>
Dataset - Lagain et al., 2021. Latitudinal dependency of the impact rate: any room for a recalibration of crater chronologies ?
<p>data related to the following article: Lagain A. et al. (2021). Latitudinal dependency of the impact rate: any room for a recalibration of crater chronologies ? submitted to <em>EPSL </em>(July 2021).</p>
Absolute model ages of three craters in the vicinity of the Chang'E-5 landing site and their geologic implications
<p>We used the Crater Size Frequency distribution (CSFD) method to yield the formation ages of Pythagora, Sharp B, and Harpalus crater, and the crater density values (N(1)). Here we provide the crater counting data.</p>
Drone survey, time-lapse camera, and satellite SAR data covering the 2021 summit craters and late fractures at Tajogaite volcano, Cumbre Vieja, La Palma
<p>A new eruption started on 19 September 2021 at the Tajogaite volcano, which is at the western flank of the Cumbre Vieja, just 1•5km to the north of the vents of the 1949 eruption, and terminated after 85 days on 13 December 2021. The location of the 2021 eruption at the Cumbre Vieja was not foreseen, although a diffuse unrest was identified years before already. At the location of the eruption, the slope of the edifice was gentle, but a number of older vents, mostly open to the west, were evident. Here we present field and satellite data showing (a) the development of the craters at the summit of the evolving Tajogaite volcano, and (b) the formation of a pronounced structural trend interpreted to be related to tensile faulting during the late stage of the eruption.</p> <p>Data contains:</p> <ol> <li>Drone data acquired by DJI drones (Phantom RTK and Mavic2) during two periods showing the summit craters and the tensile fracture set in detail.</li> <li>Time-lapse camera records from the east and the north-northeast showing eruption and morphology changes.</li> <li>Satellite radar amplitude data acquired in three different geometries (2 ascending and 1 descending track) of the Cosmo Skymed Satellite constellation</li> </ol> <p>Use data without restriction but cite our work; for details on acquisition geometries and maps refer to the papers published by:</p> <ul> <li>Walter, T.R.; Zorn, E.Z.; Gonzalez, P.J.; Sansosti, E.; Munoz, V.; Shevchenko, A.V.; Plank, S.; Reale, D.; Richter, N. (in press) Late complex tensile fracturing interacts with topography at Cumbre Vieja, La Palma, VOLCANICA 5(2): 300–316. https://doi.org/10.30909/vol.05.02.300</li> <li>Muñoz, V.; Walter, T.R.; Zorn, E.U.; Shevchenko, A.V.; González, P.J.; Reale, D.; Sansosti, E. Satellite Radar and Camera Time Series Reveal Transition from Aligned to Distributed Crater Arrangement during the 2021 Eruption of Cumbre Vieja, La Palma (Spain). Remote Sens. 2022, 14, 6168. https://doi.org/10.3390/rs14236168</li> </ul> <p> </p>
3D Models of Devil's Throat and Twin Pits Pit Craters
<p>3D models of Devil's Throat and Twin Pits pit craters in Hawai'i Volcanoes National Park, from 2017 and 2022. Estimated absolute positional accuracy is ~40 m, and estimated vertical orientation certainty is ±~7°.</p>
Pre-ejecta Craters and Measured Ejecta Thicknesses from Complex Craters on Ceres
<p>Original Publication Date: October 17, 2022</p> <p>Modified Date: February 27, 2023<br> Authors: P. E. Montalvo and H. Christopher<br> Notes: This ReadMe file serves as an overview for the Data Sets S1 and S2. Data Set S1 shows the High Altitude Mapping Orbit (HAMO) and Low Altitude Mapping Orbit (LAMO) images used in this study. Data Set S2 contains the crater counts and estimated ejecta thicknesses estimated in this study. We strongly recommend reading the details the contents of this file to properly understand the structure of each Data Set.</p> <p>Data Set S1 content:<br> Requirements: None. The contents of Data Set S1 are Dawn image information.<br> - File 1: HAMO.csv; Description: CSV file containing HAMO image information<br> - File 2: LAMO.csv; Description: CSV file containing LAMO image information<br> - File 3: Additional_LAMO.csv; CSV file containing additional LAMO images for Occator and Haulani.<br> - File 4: ReadMe.txt; Description: TXT file with content description</p> <p>Data Set S2 content:<br> Requirements: A Python script is included in Data Set S2. The script needs all CSV files included in Data Set S2 in the same directory.<br> - File 1: meta.csv; Description: CSV file containing host crater file names<br> - File 2: Occator.csv; Description: pre-ejecta crater data from Occator<br> - File 3: Haulani.csv; Description: pre-ejecta crater data from Haulani<br> - File 4: Cacaguat.csv; Description: pre-ejecta crater data from Cacaguat<br> - File 5: Dantu.csv; Description: pre-ejecta crater data from Dantu<br> - File 6: Ikapati.csv; Description: pre-ejecta crater data from Ikapati<br> - File 7: tmax.csv; Description: crater rim ejecta thickness data<br> - File 8: plotProf.py; Description: Python script that reproduces Figure 8</p> <p>Data Set S3 content:<br> Requirements: None. The contents of Data Set S3 are CSV files with point locations. Note that the file names are in order of analysis.<br> - File 1: Occator_hr.csv; Description: CSV file with rim point location<br> - File 2: Occator_ht.csv; Description: CSV file with outcrop point location<br> - File 3: Haulani_hr.csv; Description: CSV file with rim point location<br> - File 4: Haulani_ht.csv; Description: CSV file with outcrop point location<br> - File 5: Cacaguat_hr.csv; Description: CSV file with rim point location<br> - File 6: Cacaguat_ht.csv; Description: CSV file with outcrop point location<br> - File 7: Dantu_hr.csv; Description: CSV file with rim point location<br> - File 8: Dantu_ht.csv; Description: CSV file with outcrop point location<br> - File 9: Ikapati_hr.csv; Description: CSV file with rim point location<br> - File 10: Ikapati_ht.csv; Description: CSV file with outcrop point location</p>
Recalibration of the lunar chronology due to spatial cratering-rate variability - Supporting Information
<p>CR_moon.csv: Relative cratering rate shown in Fig.3 and 5.a. The<strong> </strong>data are provided over the full range of latitudes and longitudes, with a 1-degree bin.</p> <p>SI_convert_age.m: Matlab code computing model ages of Plutarch and Kirkwood craters using the chronology function presented in this study.</p>
Dark Halo Craters Data
<p>This dataset is a global collection of the longitude and latitude and diameters of dark halo craters. The software used to map the DHCs was Lunar QuickMap.The data for the iron content of the ejecta was found both from the Kaguya (Selene) and Clementine missions. We mapped all longitudes and latitudes of the lunar surface.</p> <p>We determined a crater to be a DHC if it had an ejecta pattern with visibly higher iron content than the surrounding rock. All of the counted DHCs exhibited this quality. We omitted craters that had elevated iron inside the crater rim (as opposed to in the ejecta) because the iron signature inside might result from visible mare that filled in the crater subsequent to impact. Areas associated with visible lunar maria were ignored for this particular data set.</p> <p>We identified and mapped craters globally that had a minimum diameter of 1 km. We mapped the section 40–70 W, 20–70 S with no minimum diameter limit. Determining whether the ejecta had an iron content pattern that is significantly different and distinctive from the surrounding rock is subjective, so we mapped craters conservatively. The surface was mapped by two different people so there could be some additional human error and slight subjectivity of DHCs. We only considered craters with a clearly identifiable ejecta pattern, and we required that the ejecta had to surround at least 25% of the crater. We allowed cases with asymmetrical ejecta.</p> <p>We mapped the craters in 10-degree longitude bands, first checking the iron content and ejecta pattern of craters and then confirmed the DHC with albedo satellite images. We took the longitude and latitude of the center of the crater and measured the diameter with QuickMap tools, from one rim to the other rim.<br> </p>
Supporting Material for "Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC And Kaguya TC Images"
<p>Supporting Material for "Lunar Surface Model Age Derivation: Comparisons Between Automatic and Human Crater Counting Using LRO-NAC And Kaguya TC Images"</p> <p>Contents of this material</p> <ul> <li>Supplemental Text S1 and Text S2.</li> <li>Figures S1, S2, S2, S4, S5.</li> <li>Tables S1, S2</li> </ul> <p>For any questions email JHF (john.h.fairweaher@gmail.com).</p>
Dataset For "Nyiragongo crater collapses measured by multi-sensor SAR amplitude time series"
<p>This archive contains the input ant results files used with PickCraterSAR for publication "Nyiragongo crater collapses measured by multi-sensor SAR amplitude time series" submitted to JGR-SE.</p> <p>It also contains crops of each amplitude images used in this study in ENVI format with corresponding headers.</p> <p>At least, it contains the ash index values derives from SEVIRI data analysis.</p>
Museum genomics reveals the hybrid origin of an extinct crater lake endemic
Open the record for dataset details and reuse information.
Data from: Brine driven destruction of clay minerals in Gale crater, Mars
Open the record for dataset details and reuse information.
A New Global Catalog LU1319381 of Lunar Craters (≥1 km)
<p>The new global catalog LU1319381 includes approximately 1.32 million lunar craters, which extends the existing global catalogs to craters with diameters of 1 km or larger and is enriched with 3D morphological information on the craters.</p>
Model Age Derivation of Large Martian Impact Craters, using automatic crater counting methods / Dataset
<ul> <li>"counting_area" folder: shapefiles of the mapped ejecta layers considered in this study</li> <li>"scc" folder: .scc files readable on CraterStats listing the size and location of craters detected by our CDA and recognized as primaries by the ASCI. The counting area considered for each crater slightly vary from the area indicated in the shapefile due to the removal of Thiessen polygons associated to secondary craters by the ASCI.</li> </ul> <p>The ASCI code and toolbox implementable to ESRI ArcGIS (10.6) is discoverable here: https://github.com/curtin-crater-detection/secondary-crater-removal<br> </p>
An Improved Global Catalog LU1319373 of Lunar Craters (≥1 km) with 3D Morphometric Information of Craters
<p>A global crater catalog LU1319373 that includes approximately 1.32 million lunar craters with diameters ≥ 1 km. The crater catalog also include 3D morphometric data on the craters.</p> <p>This first version of the crater catalog LU1319373 includes the following information for each crater:</p> <ul> <li>Longitude and latitude coordinates of the center;</li> <li>Crater diameter;</li> <li>Crater depth (other morphometric data will be provided in future versions).</li> </ul> <p>Please cite the following reference for using the crater catalog LU1319373.</p> <p>Wang, Y., Wu, B., Xue, H., Li, X., & Ma, J. (2021). An improved global catalog of lunar impact craters (≥1 km) with 3D morphometric information and updates on global crater analysis. Journal of Geophysical Research: Planets, 126, e2020JE006728.</p>
Crater 2: An Extremely Cold Dark Matter Halo
<p>supplementary data products, including all sky-subtracted spectra from individual targets, as well as random draws from posterior PDFs for model parameters (see enclosed README file)</p> <p> </p>
Sources of hydrothermal alteration in Toro crater
<p>The plotting and modeling details used in "Sources of hydrothermal alteration in Toro crater"</p>
Data from: Repeated divergence in opsin genes expression mirrors photic habitat changes in rapidly evolving crater lake cichlid fishes
<div> <div> <div class="msocomtxt"> <p class="MsoNormal"><span>Selection pressures differ along environmental gradients and organisms' phenotypes. Traits tightly linked to fitness (e.g., the visual system) are expected to closely track environmental variation along gradients. Within such gradients, adaptation to local conditions might be due to heritable and non-heritable, environmentally induced variation. Disentangling these sources of phenotypic variation requires studying, in nature and the laboratory, closely related populations experiencing different environments. The Nicaraguan great and crater lakes show an environmental gradient in photic conditions extending from clear crater lakes to very turbid great lakes. From two old, turbid great lakes, Midas cichlid fish (<em>Amphilophus </em>cf.<em> citrinellus</em>) independently colonized seven isolated crater lakes of varying light conditions, resulting in a small adaptive radiation. We estimated the variation in visual sensitivities along this photic gradient by measuring differential cone opsin gene expression among populations from different lakes. The visual sensitivities observed in all seven derived crater lake populations have not changed randomly but shifted predictably in direction and magnitude, repeatedly mirroring changes in photic conditions. Intrapopulation phenotypic variation decreases as environments become spectrally narrower suggesting different selective landscapes within the gradient. Comparing wild-caught and lab-reared fish revealed that 48% of this phenotypic variation is genetically determined and evolved rapidly. Our results demonstrate deterministic, rapid phenotypic evolution that fine-tunes visual sensitivity to fine-scale environmental variation.</span></p> <p class="MsoCommentText"><span> </span></p> </div> </div> </div>
Lagain et al., (2023) - Icarus - Recalibration of the lunar chronology due to spatial cratering-rate variability - Data and Code
<ul> <li>CR_moon.csv: Relative cratering rate shown in Fig.3. The<strong> </strong>data are provided over the full range of latitudes and longitudes, with a 1-degree bin.</li> <li>SI_convert_age.m: Matlab code converting model ages of Plutarch and Kirkwood craters from Neukum et al. (2001) chronology into the one presented in this study. </li> </ul>
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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.