Space Science Reviews

, 214:18 | Cite as

Image Simulation and Assessment of the Colour and Spatial Capabilities of the Colour and Stereo Surface Imaging System (CaSSIS) on the ExoMars Trace Gas Orbiter

  • Livio L. Tornabene
  • Frank P. Seelos
  • Antoine Pommerol
  • Nicholas Thomas
  • C. M. Caudill
  • Patricio Becerra
  • John C. Bridges
  • Shane Byrne
  • Marco Cardinale
  • Matthew Chojnacki
  • Susan J. Conway
  • Gabriele Cremonese
  • Colin M. Dundas
  • M. R. El-Maarry
  • Jennifer Fernando
  • Candice J. Hansen
  • Kayle Hansen
  • Tanya N. Harrison
  • Rachel Henson
  • Lucia Marinangeli
  • Alfred S. McEwen
  • Maurizio Pajola
  • Sarah S. Sutton
  • James J. Wray
Article
Part of the following topical collections:
  1. ExoMars-16

Abstract

This study aims to assess the spatial and visible/near-infrared (VNIR) colour/spectral capabilities of the 4-band Colour and Stereo Surface Imaging System (CaSSIS) aboard the ExoMars 2016 Trace Grace Orbiter (TGO). The instrument response functions for the CaSSIS imager was used to resample spectral libraries, modelled spectra and to construct spectrally (i.e., in I/F space) and spatially consistent simulated CaSSIS image cubes of various key sites of interest and for ongoing scientific investigations on Mars. Coordinated datasets from Mars Reconnaissance Orbiter (MRO) are ideal, and specifically used for simulating CaSSIS. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provides colour information, while the Context Imager (CTX), and in a few cases the High-Resolution Imaging Science Experiment (HiRISE), provides the complementary spatial information at the resampled CaSSIS unbinned/unsummed pixel resolution (4.6 m/pixel from a 400-km altitude). The methodology used herein employs a Gram-Schmidt spectral sharpening algorithm to combine the ∼18–36 m/pixel CRISM-derived CaSSIS colours with I/F images primarily derived from oversampled CTX images. One hundred and eighty-one simulated CaSSIS 4-colour image cubes (at 18–36 m/pixel) were generated (including one of Phobos) based on CRISM data. From these, thirty-three “fully”-simulated image cubes of thirty unique locations on Mars (i.e., with 4 colour bands at 4.6 m/pixel) were made. All simulated image cubes were used to test both the colour capabilities of CaSSIS by producing standard colour RGB images, colour band ratio composites (CBRCs) and spectral parameters. Simulated CaSSIS CBRCs demonstrated that CaSSIS will be able to readily isolate signatures related to ferrous (Fe2+) iron- and ferric (Fe3+) iron-bearing deposits on the surface of Mars, ices and atmospheric phenomena. Despite the lower spatial resolution of CaSSIS when compared to HiRISE, the results of this work demonstrate that CaSSIS will not only compliment HiRISE-scale studies of various geological and seasonal phenomena, it will also enhance them by providing additional colour and geologic context through its wider and longer full-colour coverage (\(\sim9.4 \times 50\) km), and its increased sensitivity to iron-bearing materials from its two IR bands (RED and NIR). In a few examples, subtle surface changes that were not easily detected by HiRISE were identified in the simulated CaSSIS images. This study also demonstrates the utility of the Gram-Schmidt spectral pan-sharpening technique to extend VNIR colour/spectral capabilities from a lower spatial resolution colour/spectral dataset to a single-band or panchromatic image greyscale image with higher resolution. These higher resolution colour products (simulated CaSSIS or otherwise) are useful as means to extend both geologic context and mapping of datasets with coarser spatial resolutions. The results of this study indicate that the TGO mission objectives, as well as the instrument-specific mission objectives, will be achievable with CaSSIS.

Keywords

Mars Mars, geology Mars, surface processes Mars, climate Mars, change detection Mars, landing sites Multispectral imaging Image processing Band ratios Pan-sharpening 

Notes

Acknowledgements

The authors wish to thank the spacecraft and instrument engineering teams for the successful completion of the instrument. CaSSIS is a project of the University of Bern and funded through the Swiss Space Office via ESA’s PRODEX programme. The instrument hardware development was also supported by the Italian Space Agency (ASI) (ASI-INAF agreement no. I/018/12/0), INAF/Astronomical Observatory of Padova, and the Space Research Center (CBK) in Warsaw. Support from SGF (Budapest), the University of Arizona (Lunar and Planetary Lab.) and NASA are also gratefully acknowledged.

The lead author wishes to personally acknowledge funding and support through the Planetary [ExoMars] Co-Investigator programme from the Canadian Space Agency (CSA) (14EXPUWO-002) and a Canadian NSERC Discovery Grant programme (RGPIN/04215-2014). A special thanks to the science and operations teams of the CRISM, CTX and HiRISE instruments, from which the spectacular coordinated datasets/images, which were required to simulate CaSSIS, would not be possible.

We would also like to acknowledge DTM technician Allison McGraw at University of Arizona for her contribution towards generating the HiRISE and CTX stereo-derived DTMs used in this study.

Supplementary material

11214_2017_436_MOESM1_ESM.docx (1.5 mb)
CRISM-CaSSIS Transform Heritage—CRISM-HiRISE Compatible Data Processing (DOCX 1.5 MB)
11214_2017_436_MOESM2_ESM.docx (94.6 mb)
(DOCX 94.6 MB)
11214_2017_436_MOESM3_ESM.gif (2.4 mb)
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Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2017

Authors and Affiliations

  • Livio L. Tornabene
    • 1
  • Frank P. Seelos
    • 2
  • Antoine Pommerol
    • 3
  • Nicholas Thomas
    • 3
  • C. M. Caudill
    • 1
  • Patricio Becerra
    • 3
  • John C. Bridges
    • 4
  • Shane Byrne
    • 5
  • Marco Cardinale
    • 6
  • Matthew Chojnacki
    • 5
  • Susan J. Conway
    • 7
  • Gabriele Cremonese
    • 8
  • Colin M. Dundas
    • 9
  • M. R. El-Maarry
    • 10
  • Jennifer Fernando
    • 5
  • Candice J. Hansen
    • 11
  • Kayle Hansen
    • 1
  • Tanya N. Harrison
    • 12
  • Rachel Henson
    • 4
  • Lucia Marinangeli
    • 6
  • Alfred S. McEwen
    • 5
  • Maurizio Pajola
    • 13
  • Sarah S. Sutton
    • 5
  • James J. Wray
    • 14
  1. 1.Centre for Planetary Science and Exploration/Department of Earth SciencesUniversity of Western OntarioLondonCanada
  2. 2.Johns Hopkins University Applied Physics LaboratoryLaurelUSA
  3. 3.Physikalisches InstitutUniversity of BernBernSwitzerland
  4. 4.Space Research Centre, Leicester Institute for Space and Earth ObservationUniversity of LeicesterLeicesterUK
  5. 5.Lunar and Planetary LaboratoryUniversity of ArizonaTucsonUSA
  6. 6.DiSPUTERUniversità G. d’AnnunzioChietiItaly
  7. 7.CNRS, Laboratoire de Planétologie et Géodynamique, CNRS/INSU UMR 6112Université de NantesNantes Cedex 3France
  8. 8.INAF—Osservatorio Astronomicodi PadovaPadovaItaly
  9. 9.U.S. Geological SurveyAstrogeology Science CenterFlagstaffUSA
  10. 10.Laboratory of Atmospheric and Space Physics (LASP)University of ColoradoBoulderUSA
  11. 11.Planetary Science InstituteTucsonUSA
  12. 12.NewSpace InitiativeArizona State UniversityTempeUSA
  13. 13.NASA Ames Research CenterMoffett FieldUSA
  14. 14.School of Earth and Atmospheric SciencesGeorgia Institute of TechnologyAtlantaUSA

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