THESIS
2013
xx, 140 pages : illustrations (some color) ; 30 cm
Abstract
In this thesis, we propose an approach of estimating lunar regolith properties by
using multichannel brightness temperature T
B observation in passive microwave
remote sensing and a simulation of heat diffusion and radiative transfer models.
The scheme determines the physical properties by optimizing the modeled
brightness temperatures against the Chang’E (CE) microwave soundings at 3.0,
7.8, 19.35 and 37 GHz channels with various lunar regolith physical parameters
such as density profile ρ, specific heat c, thermal conductivity κ and FeO+TiO
2
abundance S.
It has been found that the diurnal variance in brightness temperatures depends
crucially on the Fe-Ti-oxides abundance. Furthermore, by comparison between
the modeled and measured brightness temperatures, as well as the measu...[
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In this thesis, we propose an approach of estimating lunar regolith properties by
using multichannel brightness temperature T
B observation in passive microwave
remote sensing and a simulation of heat diffusion and radiative transfer models.
The scheme determines the physical properties by optimizing the modeled
brightness temperatures against the Chang’E (CE) microwave soundings at 3.0,
7.8, 19.35 and 37 GHz channels with various lunar regolith physical parameters
such as density profile ρ, specific heat c, thermal conductivity κ and FeO+TiO
2
abundance S.
It has been found that the diurnal variance in brightness temperatures depends
crucially on the Fe-Ti-oxides abundance. Furthermore, by comparison between
the modeled and measured brightness temperatures, as well as the measurements
in CE1 and CE2 satellites around the Apollo 15 site, a systematic shift in the
measured brightness temperatures of the CE soundings can be concluded.
In addition, the simulation results suggest that the penetration depths of the
microwave channels of CE soundings are insufficient to accurately determine regolith thickness.
It is hoped that this optimization approach can give an alternative framework
for data calibration and validation of future remote sensing measurements, as
well as an intuitive method for determination of physical quantity via passive
remote sensing technology.
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