Source regions for near-Earth objects sharing taxonomical classification

One of the long-standing questions in planetary science concerns the origins of meteorites and their immediate precursors, near-Earth objects (NEOs). It is well-established that most of them originate in the main asteroid belt, which has a complex spatial distribution of taxonomies (DeMeo & Carry, 2014; Carvano et al., 2010; Erasmus et al., 2019), even within asteroid families. However, due to the chaotic long-term orbital evolution of NEOs, tracing the orbit of a single NEO back to its source region in the main belt is impossible. 

The current state-of-the-art process for evaluating source regions of NEOs is to utilize orbital models of the NEO population built on forward modeling starting from the source regions in the asteroid belt and the cometary regions (e.g. Nesvorny et al., 2023; Granvik et al., 2018). Such evolutionary models retain probabilistic information of where NEOs on different orbits are most likely to originate. While scientifically useful, the analyses suffer from partly overlapping orbital distributions that lead to the most important source regions carrying too much weight when applied to individual NEOs (e.g. Granvik & Brown, 2018). However, if all NEOs of, say, a given taxonomic class are treated as a group when constructing the orbital model–similar to using all detected NEOs when constructing a generic NEO orbital model—the resulting model will provide a probabilistic assessment of the source regions for that taxonomic class. A practical challenge with this alternative approach is that the construction of an orbital model requires quantitative knowledge about observational selection effects pertaining to the known NEOs used for estimating the model parameters. We investigate the use of the NEO model by Granvik et al. (2018) to determine the selection effects for NEOs with taxonomical information, and present our results for the likely source regions for NEOs belonging to major taxonomic classes.

We also discuss this work in anticipation of Vera C. Rubin Observatory’s upcoming Legacy Survey of Space and Time (LSST), which will obtain multiband photometry in the griz bands for ~4000 NEOs with diameters d≥10 m (Kurlander et al., 2025). While spectroscopy is the primary method for taxonomic classification of small bodies and has been performed for ~1000 NEOs to date (Thomas et al., 2025), it is a follow-up technique that requires high signal-to-noise and therefore has a complex selection bias. Since multiband photometry can also be used to assign taxonomic types to asteroids (Mo et al., 2026; Navarro-Meza et al., 2024) and LSST will be an extremely well-characterised survey (LSST Science Collaborations et al., 2009), the resulting photometric NEO dataset will be the the largest self-consistent sampling of the NEO population compared to current photometric colour surveys (e.g. Birlan et al., 2024; Moskovitz et al., 2026) by a factor of ~20. Complementary near-infrared observations by Euclid (Carry, 2018) will also provide valuable taxonomy information for ~10⁴ moderately-inclined (i≥15°) NEOs, a subset of which will be discovered by LSST.

 

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