DocumentCode :
143593
Title :
Simulating the spectral properties of iron-bearing regions of Mars using the SPLITS model
Author :
Baranoski, Gladimir V. G. ; Kimmel, Bradley W. ; Chen, Tenn F. ; Miranda, Erik
Author_Institution :
Natural Phenomena Simulation Group, Univ. of Waterloo, Waterloo, ON, Canada
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
3013
Lastpage :
3016
Abstract :
The mineralogy and environmental history of Mars are been extensively investigated through remote sensing observations paired with laboratory and in situ experiments. A significant portion of these experiments is being devoted to the identification and quantification of different iron oxides present in the Martian terrains. Although such experiments can provide valuable information regarding the presence of these minerals, the scope of the resulting observations may be hindered by logistics and cost-related constraints. We believe that predictive computer simulations can be employed to mitigate some of these constraints and contribute to the generation and validation of hypotheses in this area. Accordingly, we propose the use of SPLITS (Spectral Light Transport Model for Sand) in investigations involving the spectral signatures of iron-rich sand-textured soils found on Mars, and demonstrate its predictive capabilities in this context through comparisons of modeled results with actual measured data.
Keywords :
Mars; iron compounds; minerals; planetary rocks; planetary surfaces; remote sensing; sand; Mars environmental history; Mars mineralogy history; Martian terrain; SPLITS model; constraint mitigation; cost-related constraint; hypothesis generation; hypothesis validation; in situ experiment; iron oxide identification; iron oxide quantification; iron-bearing region spectral property simulation; iron-rich sand-textured soil spectral signature; laboratory experiment; logistic constraint; predictive capability; predictive computer simulation; remote sensing observation; spectral light transport model for sand; Atmospheric modeling; Computational modeling; Data models; Iron; Mars; Materials; Soil; Mars; iron oxide; regolith; sand; simulation; spectral reflectance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6947111
Filename :
6947111
Link To Document :
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