Testing the Bus–DeMeo Asteroid Taxonomy Using Meteorite Spectra

Abstract The most widely used method to spectrally classify asteroids is the Bus–DeMeo taxonomy. To test how well the Bus–DeMeo taxonomy groups asteroids on the basis of their mineralogy, we have classified ∼1500 meteorite spectra using this Bus–DeMeo system. Some asteroid classes group together meteorites with similar compositions better than others. Howardite, eucrite, and diogenite spectra tend to be classified as V-types, while ordinary chondrite spectra tend to be classified as S-complex or Q-type bodies. The relatively featureless D- and X-types tend to be dominated by CM carbonaceous chondrites but with a substantial number of matches also with iron meteorites. The large proportion of CM chondrite matches for the D- and X-classes is most likely due to the large number of CM chondrite spectra and the rarity of spectra of more fragile carbonaceous chondrites in our data set. A number of relatively featureless asteroid classes like the C-, B-, L-, and Xc-types group meteorite types together with a wide variety of mineralogies and thermal histories. Visual albedos are vital for distinguishing between many of these assemblages. The Bus–DeMeo taxonomy does have trouble classifying olivine-dominated meteorites that do not have red-sloped spectra because this type of spectrum is rare among asteroids. For many asteroid classes, care must be used when making mineralogical interpretations based solely on spectral type.

Authors

Institutions

Publication Details

Journal
The Planetary Science Journal
Published
2024-09-01
DOI
https://doi.org/10.3847/psj/ad57b6
Citations
5
Primary Topic
Astro and Planetary Science
Type
article
Field-Weighted Citation Impact
1.66

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Testing the Bus–DeMeo Asteroid Taxonomy Using Meteorite Spectra

Deepika Kumawat, Sydney M. Wallace, M. D. Dyar, Ahlay Hussain et al.
5 citations
The Planetary Science Journal
Astro and Planetary Science
1.66
article

Testing the Bus–DeMeo Asteroid Taxonomy Using Meteorite Spectra

Deepika Kumawat, Sydney M. Wallace, M. D. Dyar, Ahlay Hussain, Iman Khanani, T. H. Burbine
article en
5 citations

Abstract

Abstract The most widely used method to spectrally classify asteroids is the Bus–DeMeo taxonomy. To test how well the Bus–DeMeo taxonomy groups asteroids on the basis of their mineralogy, we have classified ∼1500 meteorite spectra using this Bus–DeMeo system. Some asteroid classes group together meteorites with similar compositions better than others. Howardite, eucrite, and diogenite spectra tend to be classified as V-types, while ordinary chondrite spectra tend to be classified as S-complex or Q-type bodies. The relatively featureless D- and X-types tend to be dominated by CM carbonaceous chondrites but with a substantial number of matches also with iron meteorites. The large proportion of CM chondrite matches for the D- and X-classes is most likely due to the large number of CM chondrite spectra and the rarity of spectra of more fragile carbonaceous chondrites in our data set. A number of relatively featureless asteroid classes like the C-, B-, L-, and Xc-types group meteorite types together with a wide variety of mineralogies and thermal histories. Visual albedos are vital for distinguishing between many of these assemblages. The Bus–DeMeo taxonomy does have trouble classifying olivine-dominated meteorites that do not have red-sloped spectra because this type of spectrum is rare among asteroids. For many asteroid classes, care must be used when making mineralogical interpretations based solely on spectral type.

The Planetary Science JournalVol. 5(9)
Planetary Science Institute (US), Mount Holyoke College (US), Georgetown University (US)
National Science Foundation, National Aeronautics and Space Administration, Brown University, Nuclear Safety and Security Commission, Solar System Exploration Research Virtual Institute, Planetary Science Division
Openalex Percentile: Top 17%
Astro and Planetary Science
1.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.