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| Titel |
The SMART-1 AMIE, SIR, and D-CIXS data sets in ESA's Planetary Science Archive |
| VerfasserIn |
Björn Grieger, Jean-Luc Josset, Horst Uwe Keller, Manuel Grande, Bernard H. Foing |
| Konferenz |
EGU General Assembly 2011
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 13 (2011) |
| Datensatznummer |
250051490
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| Zusammenfassung |
| In August 2010, the European Space Agency (ESA) has published the complete data
acquired by the lunar mission SMART-1 during its 14 month cruise and 22 month in
lunar orbit. The data are available on ESA’s Planetary Science Archive (PSA) in
Planetary Data Format (PDF). There are data sets from five instruments: the Advanced
Moon MicroImaging Experiment (AMIE), the Demonstration of a Compact Imaging
Spectrometer (D-CIXS), the SMART-1 Infrared Spectrometer (SIR), the Spacecraft
Potential, Electron and Dust Experiment (SPEDE), and the X-ray Solar Monitor
(XSM).
We discuss the data from the remote sensing instruments AMIE, SIR, and D-CIXS and
show the coverage and resolution on the lunar surface. For these instruments, geometry tables
are provided to facilitate searching. We describe the formats of the geometry tables and
demonstrate how searches for certain locations and for certain observation types can be
performed. We describe the formats of the actual data products and show how the data can be
accessed using either PDS, FITS, or homegrown tools. For AMIE, we also briefly discuss the
data calibration.
The calibrated AMIE data sets comprise a total binary data volume (without
metadata overhead) of 130 GB. This can of course not be loaded completely into
the RAM of a (contemporary) computer system. If we want to visually browse
the complete AMIE data (or other large planetary data sets), we need a system
employing advanced visualization technologies. An example of such a system is
GeoVisionary, the result of a collaboration between the Virtalis company and the British
Geological Survey. GeoVisionary combines a powerful data engine with a virtual
geological toolkit. We demonstrate some possibilities of its application to the AMIE
data. |
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