Resumo:
In the present work we performed a study aiming to better understand the origin of Near-Earth Objects (NEOs) using their surface composition distribution, or taxonomic classification, in comparison with those of diverse Main Belt populations. Data from the literature was mainly used as well as some NEOs, with no previous classification, from observations performed at the Observatório Astronômico do Sertão de Itaparica (OASI). The study was performed using two data sets: the first with spectra, totally obtained from the literature, and the other with photometric spectra, the largest part being from the Sloan Digital Spectroscopic Survey (SDSS) and some obtained within this project. The analysis and comparison of the taxonomic class distribution has been performed separately for each one of the data sets and then compared. Among the obtained results we mention the up-to-date compilation of all objects with a taxonomic classification available in the literature and from this the computation of new mean values of the mean albedo for the different classes. From these new values it was then possible to compute the size of objects with taxonomic classification, but without an albedo, and analyze the effect of the diameter on the obtained distributions. We obtained the photometric spectra for six NEOs allowing the taxonomic classification for three of them. The differences among the spectroscopic and spectrophotometric samples were also analyzed and discussed, along with the existing bias. The main result being that the two samples, although complementary in terms of objects size need to be analyzed with care due to different resolutions and bias. Finally, regarding the taxonomic classifications of the NEOs and different Main Belt regions, although the results are not conclusive it is possible to say that the inner main belt and the regions near the mean motion resonance 3:1 with Jupiter and secular resonance $\nu$6 with Saturn, present similar distributions. This indicating these regions as possible origin of the NEOs, as predicted by theoretical models.
