Varatharajan, Indhu and D'Amore, Mario and Maturilli, Alessandro and Helbert, Jörn and Hiesinger, H. (2018) Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo. Lunar and Planetary Institute. Planetary Science Informatics and Data Analytics Conference, 2018-04-24 - 2018-04-26, St. Louis, Missouri, USA.
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Official URL: https://psida.rsl.wustl.edu/
Abstract
Spectroscopy is the powerful tech- nique to study the surface mineralogy of any planetary body from its orbit. Spectrometers with wide spectral range, greater spectral and spatial resolution with re- peated orbital coverage are helping us to map the sur- face mineralogy of planets in greater detail. Various spectral ranges tell different stories and properties of the surface we look at. For eg., VIS-IR spectroscopy for a rocky planet would tell us about the distribution of Fe,Ti,Mg,Ca rich minerals for both its igneous and sedimentary phases whereas thermal IR spectroscopy reveals the Si-O abundance on the bulk mineralogy of the pixel we look at. By carefully understanding the spectral behavior of various planetary analogues in laboratory experiments at the planetary surface and environmental conditions, one can map the mineral abundance and distribution globally from orbit.
| Item URL in elib: | https://elib.dlr.de/125535/ | ||||||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Keynote) | ||||||||||||||||||||||||
| Title: | Machine Learning Approach to Deconvolution of Thermal Infrared (TIR) Spectrum of Mercury Supporting MERTIS Onboard ESA/JAXA BepiColombo | ||||||||||||||||||||||||
| Authors: |
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| Date: | 2018 | ||||||||||||||||||||||||
| Refereed publication: | No | ||||||||||||||||||||||||
| Open Access: | Yes | ||||||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||||||
| In SCOPUS: | No | ||||||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||||||
| Page Range: | p. 6015 | ||||||||||||||||||||||||
| Publisher: | Lunar and Planetary Institute | ||||||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||||||
| Keywords: | Machine Learning Approach, Deconvolution, Thermal Infrared, Mercury, MERTIS, BepiColombo | ||||||||||||||||||||||||
| Event Title: | Planetary Science Informatics and Data Analytics Conference | ||||||||||||||||||||||||
| Event Location: | St. Louis, Missouri, USA | ||||||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||||||
| Event Start Date: | 24 April 2018 | ||||||||||||||||||||||||
| Event End Date: | 26 April 2018 | ||||||||||||||||||||||||
| Organizer: | Lunar and Planetary Institute | ||||||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||||||
| HGF - Program Themes: | Space Exploration | ||||||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||
| DLR - Program: | R EW - Space Exploration | ||||||||||||||||||||||||
| DLR - Research theme (Project): | R - Project BepiColombo - MERTIS and BELA | ||||||||||||||||||||||||
| Location: | Berlin-Adlershof | ||||||||||||||||||||||||
| Institutes and Institutions: | Institute of Planetary Research > Leitungsbereich PF | ||||||||||||||||||||||||
| Deposited By: | Amore, Dr. Mario | ||||||||||||||||||||||||
| Deposited On: | 03 Jan 2019 13:22 | ||||||||||||||||||||||||
| Last Modified: | 24 Apr 2024 20:29 |
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