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juliensimon/lunar-craters-robbins

Lunar Crater Database (Robbins 2019) Part of the Planetary Science Datasets collection on Hugging Face. The definitive lunar impact crater database, containing 384,278 craters with diameter >= 1 km. Essential reference for Artemis mission planning and lunar surface studies. Dataset description This database was compiled by Stuart J. Robbins (2019) using Lunar Reconnaissance Orbiter (LRO) imagery and LOLA topography. It is the most comprehensive catalog of lunar… See the full description on the dataset page: https://huggingface.co/datasets/juliensimon/lunar-craters-robbins.

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Dataset Card

Lunar Crater Database (Robbins 2019)

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

The definitive lunar impact crater database, containing 384,278 craters with diameter >= 1 km. Essential reference for Artemis mission planning and lunar surface studies.

Dataset description

This database was compiled by Stuart J. Robbins (2019) using Lunar Reconnaissance Orbiter (LRO) imagery and LOLA topography. It is the most comprehensive catalog of lunar impact craters, covering the entire lunar surface with consistent methodology.

Schema

Column	Type	Description
`crater_id`	int64	Unique crater identifier
`latitude_deg`	float64	Crater center latitude (degrees, planetocentric)
`longitude_deg`	float64	Crater center longitude (degrees, 0-360 E)
`diameter_km`	float64	Crater rim-to-rim diameter (km)
`depth_km`	float64	Rim-to-floor depth (km)
`floor_elevation_km`	float64	Floor elevation (km)
`depth_rim_sd_km`	float64	Rim depth standard deviation (km)
`size_class`	string	Derived: small (<5 km), medium (5-20), large (20-100), giant (>100)

Quick stats

—384,278 total craters
—Size distribution: 336,675 small, 36,690 medium, 10,602 large, 311 giant
—Diameter range: 1.00 -- 3411.7 km

Usage

python

from datasets import load_dataset

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

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

# South pole region (Artemis-relevant)
south_pole = df[(df["latitude_deg"] < -80)]
print(f"Craters near south pole: {len(south_pole):,}")
plt.scatter(south_pole["longitude_deg"], south_pole["latitude_deg"],
            s=south_pole["diameter_km"], alpha=0.5)
plt.title("Lunar South Pole Craters")
plt.show()

Data source

Robbins, S.J. (2019), *A New Global Database of Lunar Impact Craters >1-2 km:

1.Crater Locations and Sizes, Comparisons With Published Databases, and Global Analysis.* Journal of Geophysical Research: Planets, 124, 871-892. Distributed by USGS Astrogeology Science Center.

Pipeline

Source code: juliensimon/space-datasets

Support

If you find this dataset useful, please give it a ❤️ on the dataset page and share feedback in the Community tab! Also consider giving a ⭐️ to the space-datasets repo.

Citation

bibtex

@dataset{lunar_craters_robbins,
  author = {Simon, Julien},
  title = {Lunar Crater Database (Robbins 2019)},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/lunar-craters-robbins},
  note = {Based on Robbins (2019) via USGS Astrogeology}
}

License

CC-BY-4.0