Predicting the surface age of chondritic S-type asteroids using the space weathering features in reflectance spectra: Small data machine learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985831%3A_____%2F25%3A00637542" target="_blank" >RIV/67985831:_____/25:00637542 - isvavai.cz</a>

Alternative codes found

RIV/67985815:_____/25:00637542

Result on the web

<a href="https://hdl.handle.net/11104/0368564" target="_blank" >https://hdl.handle.net/11104/0368564</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1051/0004-6361/202554173" target="_blank" >10.1051/0004-6361/202554173</a>

Result language

angličtina

Original language name

Predicting the surface age of chondritic S-type asteroids using the space weathering features in reflectance spectra: Small data machine learning

Original language description

The surfaces of airless planetary bodies, such as S-type asteroids, undergo space weathering (SW) due to exposure to the interplanetary environment, resulting in alterations to their reflectance spectral features (e.g., spectral slope, albedo, and absorption band characteristics). Aims. This study aims to estimate the surface age of S-, Sq-, and Q-type asteroids as a function of SW agents and dose by employing machine learning models. Methods. Two models were developed: an ensemble model (combining a CNN, gradient-boosting regressor, K-nearest neighbor, extratree regressor, and random forest regressor) and a Gaussian process (GP) model. Both models were trained on published reflectance spectra of olivine, pyroxene, their mixtures, and chondritic meteorites, using SW conditions as independent variables and surface age at 1 AU as the dependent variable. Given the limited dataset, k-fold cross-validation was employed for model training. The models were further validated by applying them to S-, Sq-, and Q-type asteroids, evaluating their ability to capture two key trends: the SW progression across chondritic S-type asteroids and the relationship between asteroid size and surface age. Results. Both models successfully identify relatively fresh surfaces in Q-type asteroids and mature surfaces in S-type asteroids, as well as younger surface ages for asteroids with diameters less than 5 km. However, the GP model exhibits higher variability in predictions for the asteroid dataset. While both models effectively capture relative surface age trends, limitations in data availability between 10(3) and 10(7) years hinder precise predictions of asteroid surface ages. Conclusions. These models have significant potential for future applications, such as determining the surface age for individual asteroids and identifying asteroid families, offering valuable tools for advancing our understanding of asteroid evolution and SW processes.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10308 - Astronomy (including astrophysics,space science)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Astronomy & Astrophysics

ISSN

0004-6361

e-ISSN

1432-0746

Volume of the periodical

699

Issue of the periodical within the volume

July

Country of publishing house

FR - FRANCE

Number of pages

15

Pages from-to

A175

UT code for WoS article

001525746000008

EID of the result in the Scopus database

2-s2.0-105010630650