Analysing Rock Samples for the Mars Lander

In the near future NASA intends to explore various regions of our solar system using robotic devices such as rovers, spacecraft, airplanes, 2ind/or balloons. Such platforms will carry imsiging devices, and a variety of analytical instruments intended to evaluate the chemical and mineralogical nature of the environment(s) that they encounter. The imeiging and/or spectroscopic devices will acquire tremendous volumes of data. The communication band-widths are restrictive enough so that only a smedl portion of these data can actually be sent to Earth. The sim of this research was to develop a system which analyses rock spectra to automatically determine which spectra are interesting, and to compress the spectral data for communication to Earth. In the research we report here we classify laboratory data using clustering techniques (ACPro cm enhanced version of Auto-class) and provide the planetary scientists with a rapid, visually oriented method of eveduating the underlying chemical and mineralogical information contained within the clusters. We show how clustering can be used to identify interesting rock samples and estimate the compression that using such a system can achieve.