We study the taxonomic classification of asteroids observed by as a continuation of the lightcurve inversion work presented in Paper I. Gaia We examine the taxonomic classification of asteroids by using both Data Release 3 (DR3) photometric and spectroscopic data. Particular focus is placed on Ch-class asteroids, as their potentially hydrated nature makes them promising candidates for sample-return missions and the asteroid mining industry. Gaia We utilized the photometric slopes and geometric albedos (via absolute magnitudes) derived from lightcurve inversion, and the DR3 spectra (from 418 nm to 770 nm) as classification parameters. We also considered how different parameter sets affect classification accuracies for separate asteroid classes. We classified the asteroids with a combination of linear discriminant analysis and a nearest neighbor classifier. Gaia We achieve a classification accuracy of 92% for known S-class asteroids and an accuracy of 85% for Ch-class asteroids with a known set of 328 asteroids. Given the three classification parameters, tentative class designations for 1668 previously unclassified asteroids are provided in the Mahlke taxonomy. We also show that the photometric slope values vary significantly within asteroid classes, with a standard deviation three to four times the mean slope uncertainties. We show that the combination of photometry and spectroscopy can be useful in the taxonomic classification of asteroids observed by . Further studies of the surface roughness at different scales could help clarify the potential of the photometric slope in classification efforts. Gaia
Pentikäinen et al. (Fri,) studied this question.