Mapping the FeO and TiO₂ content of the lunar surface with multispectral imagery

Abstract

Abstract. The derivation of quantitative elemental concentrations from multispectral imaging of the Moon has long been a goal of lunar remote sensing. Concentration maps at the spatial resolutions available from the recent Clementinc mission would provide a revolutionary new tool for understanding the origin and evolution of the lunar crust. Lucey et al. [ 1995] presented a method for extracting the concentration of Fe from multispectral imaging of the Moon. This paper examines and quantifies important aspects of that technique left unexamined by Lucey et al. which had the potential to severely limit its utility. These aspects include the effects of maturity, grain size, mineralogy, shading due to topography, and the presence of glass. We also present a new algorithm for derivation of TiO2 from multispectral imaging of both mare and highland units. We f'md that both techniques are only weakly sensitive to maturity and that they have about 1 wt % accuracy based on examination of the spectral properties and compositions of resolved lunar sampling stations presented by Blewett et al. [ 1997]. We also discuss these f'mdings in the context of two contrasting views of the effect of composition on lunar spectral properties presented by Pieters and coworkers and Hapke and coworkers. We f'md the view of Hapke and coworkers to be more consistent with our observations. Using a global mosaic of Clementinc multispectral data and these element derivation algorithms, we find that the global modal abundance of FeO is 4.5 wt % ñ 1 wt % and the global modal abundance of TiO2 is 0.45 wt % ñ 1 wt. %.

The materials of the lunar Procellarum KREEP Terrane: A synthesis of data from geomorphological mapping, remote sensing, and sample analyses

“…For this work we use three principal data sets for concentrations of chemical elements: the Th data of Lawrence et al [1999] obtained from the Lunar Prospector gamma-ray spectrometer [Binder, 1998], FeO and TiO2 concentrations derived from the Clementine ultraviolet-visible (UVVIS) data [Lucey et al, 1998 Lucchitta, 1978]. To be classified as terra or mare, the mapped terrain under a pixel had to be >90% one or the other.…”

Preliminary results of TiO2 mapping using Imaging Interferometer data from Chang’E-1

“…A series of empirical models have been developed to predict the TiO 2 content from Clementine UVVIS images [29][30][31][32]. Among these models, Lucey's model has been one of the most popular and has undergone a series of refinements [33,34].…”

“…Among these models, Lucey's model has been one of the most popular and has undergone a series of refinements [33,34]. Lucey's method introduces a simple relation between the UV/VIS ratio (415 nm/750 nm) and TiO 2 content in soil of a mature mare to a titanium-sensitive parameter θ Ti , an angular measure of the TiO 2 content of soils taken from landing sites and sample stations in the plot of UV/VIS versus visible reflectance, to suppress the effect of maturity [29][30][31][32]. From analysis of Clementine UVVIS data, Lucey et al [32] derived the following formula for θ Ti and thus wrote an algorithm to predict TiO 2 content:…”

The Chandrayaan-1 X-ray Spectrometer: First results

“…Remote sensing of the Moon reveals on a global scale the compositional (Lucey et al, 1998 The technique is only possible for atmosphere-free bodies in the inner solar system, where the 110 flux of incident solar X-rays is high enough to cause fluorescent X-ray emission from the 111 uppermost hundred microns in the planetary surface (Yin et al, 1993). The emitted X-rays are 112 characteristic of elements from which they originate and they can therefore be used to help 113 constrain variations in local surface geology.…”