Date of Original Version

2002

Type

Article

Published In

Data Mining and Knowledge Discovery, Vol. 6 (2002), 277-293. Journal Article: Mineralogy

Rights Management

All Rights Reserved

Abstract or Table of Contents

Reflectance spectroscopy is a standard tool for studying the mineral composition of rock and soil samples and for remote sensing of terrestrial and extraterrestrial surfaces. We describe research on automated methods of mineral identification from reflectance spectra and give evidence that a simple algorithm, adapted from a well-known search procedure for Bayes nets, identifies the most frequently occurring classes of carbonates with reliability equal to or greater than that of human experts. We compare the reliability of the procedure to the reliability of several other automated methods adapted to the same purpose. Evidence is given that the procedure can be applied to some other mineral classes as well. Since the procedure is fast with low memory requirements, it is suitable for on-board scientific analysis by orbiters or surface rovers.

Included in

Philosophy Commons

Share

COinS