Efficient Material Mapping Using Clementine Multispectral Data

Workshop on Moon Beyond 2002 3058.pdf

EFFICIENT MATERIAL MAPPING USING CLEMENTINE MULTISPECTRAL DATA. D. Steutel1, P. G. Lucey1, M. E. Winter1, and S. LeMouélic2, 1Hawai‘i Institute of Geophysics and Planetology, 1680 East-West Road, University of Hawai‘i, Honolulu, HI 96822, [email protected]. 2Institut d'Astrophysique Spatiale, Université Paris-Sud, bâtiment 121, F-91405 Orsay, France.

Introduction: Clementine UVVIS and NIR images have References: [1] LeMouélic, S. et al. (1999) JGR, 104, been used to interpret mineralogy of the lunar surface [1,2]. E2, 3833-3843. [2] LeMouélic, S. et al. (2000) JGR, 105, E4, We have applied two algorithms to the mosaic of the Aris- 9445-9455. [3] Winter, M.E. (1999) Proc. SPIE, 3753, 266- tarchus plateau produced by [1,2] which efficiently map the 275. [4] Hapke, B. (1993) Theory of Reflectance and Emit- regional mineralogy. This technique may be applied to the tance Spectroscopy, Cambridge Univ. Press, Cambridge. [5] entirety of Clementine data now available. Lucey, P.G. (1998) JGR, 103, E1, 1703-1714. [6] Lucey, Algorithms: First, we applied an endmember detec- P.G. et al. (1998) JGR, 103, E2, 3679-3700. [7] Hapke, B. tor/linear unmixing algorithm (N-FINDR,[3]) to the multis- (2001) JGR, 106, E5, 10,039-10,073. [8] Stöffler, D. et al. pectral data. Endmember detection is accomplished by a (1980) Proc. Conf. Lunar Crust, 51-70. simplex volume expansion process which evaluates each pixel Spectral Endmember in the image. Final endmembers are spectra from the image. These endmembers are used to linearly unmix all spectra in 1 2 3 4 5 6 olivine* 39.9 17.9 42.7 20.8 11.8

the image. Mature mare Second, we applied a Hapke-based [4] iterative nonlinear orthopyrox- 9.6 30.1 10.4 14.1 8.0 ene* mixture spectral analysis model to identify the modal abun- clinopyrox- 42.3 5.6 0.0 0.5 0.0 dance, grain size, Mg-number [5], glass abundance and com- ene*

position [6], and submicroscopic iron [7]. anorthite* 3.4 41.0 46.8 61.6 75.1 Results: Six spectral endmembers were identified, includ- ilmenite* 4.8 5.4 0.1 3.1 5.2 ing one endmember of mature mare with little mineralogic minerals** 69.1 99.1 75.2 83.3 94.6 information. The spectral analysis model spectra converged glass** 30.7 0.1 24.0 16.4 5.1 very closely to endmember spectra. Table 1 lists the end- SMFe** 1.8 0.3 0.8 0.8 0.3 0.3 member compositions corresponding to the spectral analysis model. Endmember compositions were then mapped onto *Wt% of minerals present **Wt% of minerals, glass, and SMFe the linearly unmixed fraction planes to produce a mineral Table 1. Endmember spectra and spectral analysis model map. No mineralogy was mapped onto the fraction plane spectra. represented by endmember 1. The rock type [8] of each Plagioclase Plagioclase pixel was determined based on the pixel mineralogy. Figure 1 Endmember 2 Endmember 3 shows the rock type represented by spectral endmembers 2- Endmember 4 Endmember 5 6. Figure 2 shows a map of rock types. The mappable por- Endmember 6 tion of the scene is dominated by olivine norite (8%), olivine gabbro (62%), and anorthositic troctolite (30%). Conclusions: By applying automated endmember detec- Orthopyroxene tion, spectral mixing analysis, and spectral composition Pyroxene Olivine Clinopyroxene analysis, mineralogic, rock type, and elemental abundance Figure 1. Rock types of spectral endmembers. maps can be produced efficiently. The technique used can be applied to scenes such as the Aristarchus mosaic used here in just a few minutes. With planned improvements in the effi- Olivine norite ciency of the spectral composition analysis, an analysis of Olivine gabbro the entire Clementine data set could be done in days. Anorthositic Future work: Most importantly, the spectral composi- Troctolite tion analysis algorithm must be validated (preliminary work Not mapped on this has been done.) Also, the algorithm should be im- proved. We estimate that at least one order of magnitude improvement is possible. Finally, errors in the endmember detection/linear unmixing analysis and the spectral composi-

tion analysis must be incorporated to yield an uncertainty in Figure 2. Three mapable rock types at Aristarchus. the final mineralogic, rock type, and elemental maps produced.