Multiscale and multispectral characterization of mineralogy with the ExoMars 2020 rover remote sensing payload

Awduron Sefydliadau
  • E.j. Allender(Awdur)
    University of St Andrews
  • C.r. Cousins(Awdur)
    University of St Andrews
  • Matt Gunn(Awdur)
  • C.m. Caudill(Awdur)
    University of Western Ontario
Math Erthygl
Iaith wreiddiolSaesneg
Rhif yr erthygle2019EA000692
Nifer y tudalennau18
CyfnodolynEarth and Space Science
Rhif y cyfnodolyn4
Dangosyddion eitem ddigidol (DOIs)
StatwsCyhoeddwyd - 22 Ebr 2020
Cysylltiad parhaol
Arddangos ystadegau lawrlwytho
Gweld graff cysylltiadau
Fformatau enwi


In 2020, the European Space Agency and Roscosmos will launch the ExoMars rover, with the scientific objective to detect evidence of life within the Martian surface via the deployment of a 2 m drill. The ExoMars Pasteur payload contains several imaging and spectroscopic instruments key to this objective: the Panoramic Camera (PanCam), Infrared Spectrometer for ExoMars (ISEM), and Close-UP Imager (CLUPI). These instruments are able to collect data at a variety of spatial (sub-mm to decimeter) and spectral (3.3 to 120 nm) resolutions across the 440 to 3,300 nm wavelength range and collectively will form a picture of the geological and morphological characteristics of the surface terrain surrounding the rover. We deployed emulators of this instrument suite at terrestrial analog sites that formed in a range of aqueous environments to test their ability to detect and characterize science targets. We find that the emulator suite is able to effectively detect, characterize, and refine the compositions of multiple targets at working distances spanning from 2 to 18 m. We report on (a) the detection of hydrothermal alteration minerals including Fe-smectites and gypsum from basaltic substrates, (b) the detection of late-stage diagenetic gypsum veins embedded in exposures of sedimentary mudstone, (c) multispectral evidence of compositional differences detected from fossiliferous mudstones, and (d) approaches to cross-referencing multi-scale and multi-resolution data. These findings aid in the development of data products and analysis toolkits in advance of the ExoMars rover mission.