Lunar provenance moon markLunar Meteorite Provenance Explorer
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Lunar provenance analysis

From meteorite chemistry to candidate source craters.

Enter a lunar meteorite's geochemical signature. The explorer compares it with lunar orbital chemistry, fresh-crater spectroscopy, mineralogy and geological context, then returns a ranked set of candidate source-crater observations for follow-up. The Dhofar reference case reproduces the dissertation ranking; the analysis mode extends the same regional-to-crater logic to new meteorite inputs.

Built for renewed lunar exploration and rapidly expanding planetary datasets.

Analyse a meteoriteView validation
Interpretation: Higher scores indicate stronger agreement with the selected meteorite constraints. The ranking is designed to identify the most plausible candidate source-crater observations and focus subsequent geological, geochemical and remote-sensing investigation.

01

Analysis

Use the reference case to reproduce the Dhofar thesis result, or choose “Analyse a meteorite” to enter a new geochemical signature and generate a ranked candidate list.

Reference mode: the regional screen is not rerun here because the exact historical Th reclassification/weighting/cutoff was not recovered. This mode starts from the verified final set of 400 observations and reproduces crater-level scoring exactly.
Rank 1—
Score—
Spearman ρ vs A—
Top-25 overlap vs A—

Dhofar candidate observations

Top 25 shown

0 plotted
USGS Unified Geologic Map of the Moon
lower score higher score
Equirectangular display (−180° to 180° longitude, −90° to 90° latitude). Shaded polar bands indicate areas outside the Kaguya fresh-crater archive's ±50° ranking coverage.

Leading observations

0 observations

Selected observation

Component scores and spatial context

Select an observation from the map, ranking or table.

Current Top 25

02

Method

The tool keeps the validated Dhofar implementation separate from the general analysis model, while exposing every criterion, threshold and weight used in a custom run.

Dhofar reference case

  1. Regional Lunar Prospector FeO + Th screening reduced 8,183 Kaguya observations to 1,314.
  2. A 7–10 wt.% Kaguya FeO filter retained 400 observations.
  3. USGS geology was joined spatially.
  4. FeO, mineralogy, geology and OMAT were combined into a continuous ranking.
  5. Three weighting scenarios tested ranking sensitivity.
FeOScore = 1 − |FeO − 8.3| / 1.7
MineralScore = (max(Plag,0)+max(Opx,0)) / Σ max(mineral,0)
OMATScore = (OMAT − OMATmin) / (OMATmax − OMATmin)
FinalScore = 0.40 FeO + 0.30 Mineral + 0.20 Geology + 0.10 OMAT

Custom composition model

For an active regional variable x, target t and user-supplied accepted difference (±) h:

s = max(0, 1 − |x − t| / h)

Active regional scores are combined by a normalised weighted mean. Only observations meeting the chosen regional threshold proceed.

Mineral similarity uses the four Kaguya mineral fractions after negative estimates are set to zero and both candidate and target vectors are normalised:

Mineral similarity = 1 − 0.5 Σ |candidateᵢ − targetᵢ|

Optional geology uses explicit user-defined unit scores. OMAT is min–max normalised within the retained observation set. Missing criteria are excluded and the remaining observation-level weights are renormalised.

Ti handling: Lunar Prospector provides elemental Ti wt.%. Meteorite major-element data are commonly reported as TiO₂. The site converts TiO₂ to elemental Ti before comparison using stoichiometric mass fraction.

03

Validation

Automated checks are packaged with this release and are intended to catch changes that would break the verified reference implementation.

Independent known-location regional checks: Using the site’s built-in exploratory screening widths and the default regional threshold, Apollo 17 mare soil 71501 (FeO 17.4 wt.%, TiO₂ 9.5 wt.%) retained five Kaguya observations within 200 km of the Taurus–Littrow landing site; the nearest retained observation was 165.5 km away with regional similarity 0.823. Apollo 16 highland soil 64421 (FeO 4.71 wt.%, TiO₂ 0.53 wt.%) retained eight observations within 200 km of the Descartes landing site; the nearest was 105.6 km away. The much broader Apollo 16 solution is consistent with the known difficulty of geographically constraining feldspathic highland compositions. These checks assess regional screening behaviour only; Apollo surface soils are not expected to reproduce a fresh-crater ejection ranking.

A full machine-readable summary is included in data/validation.json.

04

Data and scope

The tool combines datasets with different spatial resolution, coverage and physical meaning. Those differences are part of the uncertainty and should not be hidden by a single combined score.

DatasetUseImportant scope
Kaguya Spectral Profiler small fresh-crater spectraObservation coordinates, FeO, OMAT, estimated mineralogy8,183 spectra representing 3,622 unique <1 km craters; archive confined to ±50° latitude and mission lighting conditions.
Lunar Prospector half-degree FeORegional FeO screening0.5° map cells; FeO wt.%; low-altitude GRS-derived product.
Lunar Prospector half-degree ThRegional Th screening0.5° map cells; Th ppm; low-altitude GRS-derived product.
Lunar Prospector 2-degree TiOptional regional titanium screening~60 km equal-area bins; elemental Ti wt.% — not TiO₂.
USGS Unified Geologic Map of the Moon v2Geological unit attached to each Kaguya observationGlobal 1:5,000,000 geologic framework; 12,247 GeoUnits polygons in the supplied dataset.
WUSTL lunar meteorite compilationConvenience lookup for published FeO and Th valuesLookup snapshot only; values should be traced to primary literature for publication-grade work.
Analysis master CSVMeteorite lookup CSVValidation CSVMethodsValidation

Known limitations

  • The Kaguya fresh-crater archive used here is limited to approximately ±50° latitude and does not provide a complete polar candidate population.
  • The 8,183 records are spectral observations, not 8,183 unique craters; repeated spectra can represent the same crater.
  • Laboratory meteorite compositions and orbital products differ in spatial scale and measurement context. Similarity does not establish genetic equivalence.
  • The custom composition model is a transparent generalisation of the dissertation workflow and has not been externally validated across the lunar meteorite collection.
  • The WUSTL lookup is a convenience index. Publication-grade work should trace selected values and uncertainty to the primary analytical literature.

05

References and source products

Dataset identifiers and direct source links used by this release.

Lucey, P.G. & Lemelin, M. (2014). Kaguya SP Spectra of Small Lunar Craters, KAGUYA-L-SP-5-SPECTRA-V1.0, NASA Planetary Data System. DOI: 10.17189/1520090.

Lunar Prospector reduced spectrometer special products. Half-degree FeO and Th abundance products and 2-degree Ti abundance product, NASA PDS Geosciences Node. Product documentation.

Fortezzo, C.M., Spudis, P.D. & Harrel, S.L. (2020). Unified Geologic Map of the Moon, 1:5M, version 2. USGS Astropedia.

Washington University in St. Louis. List of Lunar Meteorites — Feldspathic to Basaltic Order, lookup snapshot dated 11 September 2026. Compilation.

Astromat Team (2025). Astromat Synthesis Compilation: Lunar meteorite samples v.1 February 2025. DOI: 10.60520/IEDA/113699. Recommended for broader sample chemistry and analytical metadata.