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juliensimon/ceres-craters-dawn

Ceres Crater Database (Zeilnhofer 2020, Dawn FC2) Credit: NASA/JPL-Caltech Part of a dataset collection on Hugging Face. Dataset description The most comprehensive catalog of impact craters on dwarf planet Ceres, containing craters with diameter >= 1 km identified from Dawn Framing Camera (FC2) imagery. This database was compiled by M. F. Zeilnhofer and N. G. Barlow (2021) using images from NASA's Dawn spacecraft Framing Camera 2. Every crater >= 1 km in… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/ceres-craters-dawn.

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Ceres Crater Database (Zeilnhofer 2020, Dawn FC2)

<div align="center"> <img src="banner.jpg" alt="Dawn spacecraft orbiting Ceres (artist concept)" width="400"> <p><em>Credit: NASA/JPL-Caltech</em></p> </div>

Part of a [dataset collection](https://huggingface.co/collections/juliensimon/planetary-science-datasets-69c2d4683bd6a66c34fb4af2) on Hugging Face.

Dataset description

The most comprehensive catalog of impact craters on dwarf planet Ceres, containing craters with diameter >= 1 km identified from Dawn Framing Camera (FC2) imagery.

This database was compiled by M. F. Zeilnhofer and N. G. Barlow (2021) using images from NASA's Dawn spacecraft Framing Camera 2. Every crater >= 1 km in diameter on Ceres was identified and measured, providing positions, diameters, and depth measurements where available.

Ceres occupies a unique position in solar system science as a volatile-rich body that has remained largely intact since the early stages of planetary formation. With a mean diameter of approximately 940 km and a bulk density of about 2.16 g/cm3, Ceres is thought to harbor a substantial water ice component beneath its regolith, and possibly a residual subsurface brine layer. The Dawn spacecraft's orbital observations revealed bright deposits of sodium carbonate and ammonium-bearing minerals in several craters -- most famously in Occator crater -- interpreted as recent or ongoing cryovolcanic activity where brines have migrated to the surface.

The crater population on Ceres provides key constraints on the age and evolution of the asteroid belt. Notably, Ceres has a deficit of large craters (greater than 100 km) compared to predictions from collisional models, suggesting that viscous relaxation of the ice-rich crust has erased large basins over geological time. The depth-to-diameter ratios of Cerean craters are systematically shallower than those on Vesta or the Moon, consistent with a mechanically weak, ice-bearing lithosphere.

This dataset is suitable for tabular classification, tabular regression tasks.

Schema

ColumnTypeDescriptionSampleNull %
longitude_degfloat64Crater centre east longitude in degrees (0-360), measured in JMARS103.930.0%
latitude_degfloat64Crater centre latitude in degrees, positive north, measured in JMARS; coverage runs 84.66S to 89.62N-84.660.0%
crater_idstrCrater identifier built from its centre coordinates: the first four digits of the longitude and the first three of the latitude, separated by the latitude sign (e.g. '1039-846' is 103.93E, 84.66S)1039-8460.0%
diameter_kmfloat64Crater (major) diameter in km, measured in JMARS to the nearest tenth of a km; range 1.0-282.0 km3.00.0%
minor_diameter_kmfloat64Minor-axis diameter in km, reported only where it differs from the major diameter by at least 0.1 km; 0.0 means the crater is effectively circular, not that the value is missing0.00.0%
preservation_stateint64Preservation on a 0-5 scale: 1 highly degraded to the point of erasure, 2 highly degraded, 3 moderate, 4 slight, 5 fresh; 0 would be a 'ghost' crater but none are reported30.0%
ejecta_morphologystrEjecta morphology from Low Altitude Mapping Orbit images: 'CE' for a continuous ejecta blanket, 'No' where none is visibleNo0.0%
interior_morphology_1strMost prominent interior morphology: BA/DA bright or dark albedo feature, EB external ejecta blanket deposit, Pk central peak, SP summit pit, SY floor pit, FD floor deposit, WT wall terrace; 'No' where none is presentNo0.0%
interior_morphology_2strSecond most prominent interior morphology, same coding as interiormorphology1No0.0%
central_peak_diameter_kmfloat64Basal diameter of the central peak in km, averaged over three measurements; applies to craters with a central peak (Pk) or summit pit (SP); 0.0 where not applicable0.00.0%
peak_crater_diameter_ratiofloat64Central peak basal diameter divided by crater diameter; 0.0 where no peak was measured0.00.0%
central_pit_diameter_kmfloat64Diameter of the central pit in km, averaged over three measurements; applies to floor pits (SY) and summit pits (SP); 0.0 where not applicable0.00.0%
pit_crater_diameter_ratiofloat64Central pit diameter divided by crater diameter; 0.0 where no pit was measured0.00.0%
rim_height_km_mean_spherefloat64Crater rim height in km under the Mean Spheroid model of Ceres topography, averaged over three profiles taken out to about two crater radii0.890.0%
depth_km_mean_spherefloat64Crater depth in km under the Mean Spheroid model, averaged over three profiles taken out to about two crater radii0.790.0%
rim_height_km_oblate_spherefloat64Crater rim height in km under the Oblate Spheroid model, same three-profile method0.150.0%
depth_km_oblate_spherefloat64Crater depth in km under the Oblate Spheroid model, same three-profile method0.280.0%
depth_diameter_ratiofloat64depthkmmeansphere divided by diameterkm; derived, not in the source file. Fresh craters sit near 0.15-0.20 and the ratio falls as craters degrade or relax viscously0.26330.0%
size_classstrDerived size category: small (<5 km), medium (5-20 km), large (20-100 km), giant (>100 km)small0.0%

Quick stats

  • —44,594 total craters on Ceres
  • —Size distribution: 41,379 small, 2,572 medium, 620 large, 23 giant
  • —Diameter range: 1.00 -- 282.0 km
  • —44,440 craters with depth measurements

Usage

python
from datasets import load_dataset

ds = load_dataset("juliensimon/ceres-craters-dawn", split="train")
df = ds.to_pandas()
python
from datasets import load_dataset

ds = load_dataset("juliensimon/ceres-craters-dawn", split="train")
df = ds.to_pandas()

# Size distribution histogram
import matplotlib.pyplot as plt
df["diameter_km"].hist(bins=100, log=True)
plt.xlabel("Diameter (km)")
plt.ylabel("Count")
plt.title("Ceres Crater Size Distribution")
plt.show()

# Map of craters
plt.scatter(df["longitude_deg"], df["latitude_deg"],
            s=df["diameter_km"] / 5, alpha=0.3)
plt.xlabel("Longitude (deg)")
plt.ylabel("Latitude (deg)")
plt.title("Ceres Impact Craters (Dawn FC2)")
plt.show()

# Large craters (>50 km)
large = df[df["diameter_km"] > 50].sort_values("diameter_km", ascending=False)
print(f"Craters >50 km: {len(large)}")

Data source

https://astrogeology.usgs.gov/search/map/ceresdawnzeilnhofercraterdatabase_2020

Related datasets

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About the author

Created by Julien Simon — AI Operating Partner at Fortino Capital. Part of the Space Datasets collection.

Citation

bibtex
@dataset{ceres_craters_dawn,
  title = {Ceres Crater Database (Zeilnhofer 2020, Dawn FC2)},
  author = {Simon, Julien},
  year = {2026},
  url = {https://huggingface.co/datasets/juliensimon/ceres-craters-dawn},
  note = {Derived from USGS Astrogeology Science Center, https://astrogeology.usgs.gov/search/map/ceres_dawn_zeilnhofer_crater_database_2020},
  publisher = {Hugging Face}
}

License

CC-BY-4.0