## Final Report for Application of Machine Learning Technology to Martian Geology

**Submitted to:**

###  Applied Information Systems Research Program

Office of Space Science

NASA

Washington, DC

**Prepared by:**

# Ruye Wang

Engineering Department

Harvey Mudd College

Claremont, CA 91711

# James Dohm

# Department of Hydrology and Water Resources

# University of Arizona,

# Tucson, AZ, 85721 

Rebecca Castano

Jet Propulsion Laboratory

Pasadena, CA, 91101

### **Are the Rock Compositions of the Ancient Mountain Range of Mars,**

### **Thaumasia Highlands, Distinct from Tharsis Lavas?:**

### **Machine Learning Evaluation of TES Data**

### **and Implications on Early Evolution of Mars**

# *Abstract*-Prominent characteristics of the Thaumasia highlands mountain range include magnetic signatures, complex tectonic structures, cuestas, hog backs, and valley networks (characteristics similar to the mountain ranges of Earth), revealed through Viking, Mars Odyssey (MO), Mars Express (MEX), and Mars Global Surveyor (MGS) information. We have applied Machine Learning and Geographic Information Systems (GIS) techniques to published geologic and Thermal Emission Spectrometer (TES) hyperspectral image cube information. When compared to the ancient mountain-forming materials, the younger plains-forming materials record a different TES emissivity signature. This finding is consistent with Viking-era, geological mapping-based interpretations that the mountain-forming materials could be comprised of a diversity of rock types, other than lava flow materials. These include ancient highly eroded and geochemically altered crystalline igneous and/or metamorphic rocks that generally underlie sedimentary rock sequences including aeolian, fluvial, alluvial, and colluvial deposits. In contrast, the plains-forming materials are lava flow materials. Here, we describe a useful Machine Learning approach that aids in assessment of the spectral data, the significance of the Thaumasia highlands mountain range to unraveling the early evolutionary phases of Mars, and a rationale for continued investigation of such ancient features including other mountain ranges such as Coprates rise of Mars through MGS, MO, and Mars Reconnaissance Orbiter (MRO).

I. INTRODUCTION

Ancient mountain ranges form the southern and southeastern margins of
the Thaumasia plateau in the southeast part of Tharsis. These are known
as the Thaumasia highlands and Coprates rise, respectively (Fig. 1 and
2) \[1,2\]. Information acquired from the Mars Express (MEX) spacecraft
highlights the significance of the Thaumasia highlands mountain range as
a window into the ancient phase of Mars evolution \[3-4\]. Stratigraphic
and cross-cutting relations, impact crater statistics, an order of
magnitude greater density of tectonic structures in the mountains
compared to the younger lava plains of the shield complex of Syria
Planum, and distinct magnetic signatures indicate that the mountain
ranges began to form before the shut down of the magnetosphere, prior to
the evolution of Tharsis \[5-6\]. Determination of the mineralogic
composition of these ancient structures has the potential to
significantly improve understanding of the early geologic and
geochemical evolution of Mars. For example, are the rock compositions of
the largest mountain range of Mars, Thaumasia highlands, different from
Tharsis lavas? Is there a distinct ancient rock record in the Thaumasia
highlands that is not obscured by Tharsis-era geologic activity,
activity which dates back to at least the Middle Noachian epoch
\[1,2,5,6\] or more than 3.7Ga to present \[7\]? More specifically, are
there rocks other than volcanic compositions (e.g.,
basalt/basaltic-andesite) such as basement complex rocks in the ancient
mountain range (a suite of mostly crystalline igneous and/or metamorphic
rocks that generally underlies the sedimentary rock sequence) that are
poking up through an aeolian mantle chiefly composed of
basaltic/basaltic-andesite materials? In addition, is such a potential
ancient rock record free of thin-skinned secondary weathering products
(e.g., see \[9,10\] for information on MER-based investigations that
reveal secondary weathering rinds) or contributing fragmented materials
to the development of fan materials on and along the southern flanks of
the Thaumasia highlands mountain range \[2\], all at sufficient areal
extent to be detected from orbital platforms ranging from the Thermal
Emission Spectrometer (TES) on Mars Global Surveyor (MGS) to the Compact
Reconnaissance Imaging Spectrometer for Mars (CRISM) on the Mars
Reconnaissance Orbiter (MRO)? Addressing whether the mountain range is
comprised of rocks other than volcanic is further prompted by
similarities to terrestrial mountain ranges of diverse rock compositions
\[1,2\]. These include magnetic signatures \[11-13\], complex tectonic

structures, cuestas, and hog backs, and the potential significance to
the early evolution of Mars \[1,2,5,6\].

![](media/image1.png){width="4.897222222222222in"
height="2.435416666666667in"}

Fig. 1. MOLA-based map showing ancient features such as Thaumasia
highlands (T.H.) and Coprates rise (C.R.) mountain ranges, Phlegra
Montes, Tempe Mareotis Fossae (T.M.F), and ancient geologic provinces
such as Terra Cimmeria and Arabia Terra, all of which are considered as
ancient markers of the early evolution of Mars. The "T" denoting
Thaumasia highlands is approximately located at the central part of the
region under investigation.

Mars is commonly viewed as a one-plate planet based largely on
geophysical and geochemical arguments mainly from analysis of SNC
meteorites \[14-15\]. Just as the ancient rock record may be obscured by
mantling and secondary weathering processes, the SNC---associated
sampling may only reveal a part of the geological and geochemical
histories of Mars. Whether the Thaumasia highlands mountain range is
other than basalt/basaltic andesite is a significant query to address
since the range records an ancient part of Mars' evolution, which
includes hypothesized Earth-like evolutional phases, including plate
tectonism, particularly during its embryonic stages of evolution
\[5,16\]. These are invoked to account for many enigmatic features in
regard to the geological history of Mars. Included in these features are
the ancient mountain ranges, Thaumasia highlands and Coprates rise,
extremely large ancient tectonic structures such as Tempe Mareotis
Fossae and Phlegra Montes, and ancient geologic provinces such as Terra
Cimmeria and Arabia Terra (Fig. 1 and 2) that record pronounced magnetic
anomalies \[5,13,17\].

Below, we discuss the approach that was used to evaluate the TES data,
present the results, and discuss why such an investigation may improve
our understanding of the early geological evolution of Mars. We also
explain why it is necessary for further investigation of ancient
features and geologic provinces of Mars through MGS, MO, and MRO.

II\. METHODOLOGY

As part of the geological investigation of the ancient Thaumasia
highlands mountain range (Fig 1 and 2), the TES data taken by the MGS
spacecraft are analyzed by Machine Learning methodologies using both
unsupervised (clustering) and supervised (classification) techniques.
Canonical spectral endmembers representing atmospheric contributions
\[20\] as well as surface types and pure mineral endmembers from the
Arizona State University (ASU) Spectral Library \[e.g., 17-22\] were
used for the clustering investigation, while the published Viking-era
geologic information \[2\] were used to select prime mountain- and
plains-forming TES spectral types for the supervised investigation.

![](media/image2.png){width="4.350694444444445in"
height="4.938888888888889in"}

Fig. 2. A. MOLA-based 3D projection looking to the west obliquely across
the Thaumasia highlands mountain range (white arrows). **B.** MOLA-based
3D projection looking to the east obliquely across the Thaumasia
highlands mountain range (white arrows). **C.** Based on \[1\], (**i**)
present-day MOLA profile (Transect A-A') across the west-central part of
Thaumasia highlands mountain range, central part of a putative Noachian
drainage basin (queried blue line represents uncertain basin extent),
including west-central Valles Marineris rise (center of tectonic
activity, interpreted to be the result of magmatic-driven uplift \[1\],
and Tempe Terra plateau, (**ii**) MOLA shaded relief map showing
features of interest, including the approximated boundary of the
Noachian drainage basin (dashed blue line) and the central Valles
Marineris rise, and (**iii**) part of the geologic map of the western
equatorial region of Mars (representative map units are shown---\[8\]).

To determine whether there are distinctions in spectral signatures among
the ancient mountain-forming materials of Thaumasia highlands and the
younger lava plains of the complex shield volcano, Syria Planum (e.g.,
Syria, Sinai and Solis Planae; for detailed mountain range and shield
complex information, see \[1,2,23\]), our approach requires the
following steps; (1) determine distinguishing TES information using
unsupervised and supervised Machine Learning techniques, which included
TES-based Surface Type 1 vs. Surface Type 2 spectral information \[18\]
and selected mountain-forming pixels vs. plains-forming pixels, (2)
select "quality" tracks of TES data that have the least contributions
from clouds, atmospheric and surface dust, or noise for comprehensive
analysis, (3) apply unsupervised and supervised techniques to the
"quality" tracks of TES data to visualize whether there is a spectral
distinction between the ancient mountain-building materials and
plains-forming materials, (4) separate out ancient mountain-forming
materials from relatively young plains-forming materials based on
published geologic information using Geographic Information Systems
(GIS) for coupling with the Machine Learning-based results, and (5)
quantify the comparison among the Machine Learning-based results and the
published geologic information, which includes determining the density
of untrained Type 1 and Type 2 pixels and trained mountain-forming and
plains-forming pixels (e.g., total amount of pixels of a specific type
divided by the total area of either mountain-forming or plains-forming
units) (Fig. 3 and 4).

![](media/image3.jpeg){width="3.738888888888889in"
height="4.210416666666666in"}

Fig. 3. Map shows TES type 1 and 2 plotted over a MOLA hillshade and a
part of the USGS I-2605 map \[2\] (see corresponding Table 1). The TES
data was classified by applying Machine Learning "untrained" techniques
to Type 1 and Type 2 information \[18,21,22\] using quality TES strips
that cover part of the ancient Thaumasia highlands mountain range and
younger plains-forming materials to the north and south of the mountain
range. The Geology has been reclassified into two units: Ancient (mostly
Early and Middle Noachian---Stage 1 map units) and Young (Late Noachian
and younger---Stages 2-4 map units) based on \[2\]. The histogram chart
shows the density of the type 1 and 2 TES data. This was calculated by
dividing the individual TES points by the area of the ancient and young
terrains. The density results clearly indicate that the mountain-forming
materials are distinct from the plains-forming materials with more
dominant Type-2 and Type-1 signatures, respectively. This is consistent
with Viking-era geologic investigations \[2,8\].

To associate both the Machine Learning "untrained" classified TES type 1
and 2 information and "trained" classified mountain- and plains-forming
TES spectral information with the Thaumasia ancient mountain terrain and
the younger surrounding plains, we co-located all the datasets into a
GIS for analysis. The USGS map publication I-2605 \[2\] was used to
select mountain- and plains-forming pixel types at prime locales, as
well as to segregate geologic map units into two types for comparative
analysis with the Machine Learning-based results: (1) ancient
mountain-forming map units (mostly Stage 1, Early to Late Noachian), and
(2) younger map units (Stages 2-4: Late Noachian to Early Hesperian).
Area calculations for the two types of geologic units were computed
using an Equal-area Sinusoidal projection. The TES-based information of
Fig. 14 and 15 were then read into our GIS as simple point locations.
Because the region for this TES-based investigation was smaller in
extent than the extent of the total area of the I-2605 geologic map, the
geology was clipped to match the study region (matching the limits of
the TES data). Lastly, we intersected the TES points with the two
geologic unit types to create the density calculations (Fig. 14 and 15
and corresponding Tables 1 and 2).

Table 1. Corresponding with Fig 3, the TES data was classified by
applying Machine Learning to Type-1 and Type-2 end member information of
\[18,20\] by selecting pixels of quality TES strips that occur in the
ancient mountain-building materials and younger plains-forming
materials. The Geology has been reclassified into two units: Ancient
(mostly Early and Middle Noachian---Stage 1 map units) and Young (Late
Noachian and younger---Stages 2-4 map units) based on \[2\]. The density
results clearly indicate that the mountain-forming materials are
distinct from the plains-forming materials with more dominant Type-2 and
Type-1 signatures, respectively. This is consistent with Viking-era
geologic investigations \[2,8\].

III\. RESULTS

The density results clearly indicate that the mountain-forming materials
are distinct from the plains-forming materials with more dominant Type 2
and mountain-type for the ancient mountain-forming materials of the
Thaumasia highlands mountain range and Type 1 and plains-forming type
for the plains-forming materials, respectively. This is consistent with
Viking-era geologic investigations \[2,8\], which indicated that the
mountains could be comprised of diverse rock materials such as basement
complex and the plains-forming materials mostly composed of basaltic
lava flows. Those pixels that do not show such a correspondence could be
explained by multiple factors. There may be atmospheric obscuration and
dust loading in some locations. Alternatively, materials shed from the
prominent mountains may create alluvial fan materials comprised of both
mountain-forming materials and plains-forming materials, lateral and
vertical variations in the mantles may obscure bedrock, and younger
volcanoes and lava flows occur in the mountain range \[2\].

![](media/image4.jpeg){width="3.667361111111111in"
height="4.129861111111111in"}

Fig. 4**.** Map shows mountain- and plains-forming- pixel types plotted
over a MOLA hillshade and a part of the USGS I-2605 map \[2\] (see
corresponding Table 1); the pixel location for each type was also based
on the USGS I-2605 map). The TES data was classified by applying Machine
Learning "trained" techniques to identify mountain-forming pixels from
plains-forming pixels using quality TES strips that cover part of the
ancient Thaumasia highlands mountain range and younger plains-forming
materials to the north and south of the mountain range. The Geology has
been reclassified into two units: Ancient (mostly Early and Middle
Noachian---Stage 1 map units) and Young (Late Noachian and
younger---Stages 2-4 map units) based on \[2\]. The histogram chart
shows the density of the mountain-forming and plains-forming TES-based
information. This was calculated by dividing the number of individual
TES pixels by the area of the ancient and young terrains. The longitudes
are positive East. The density results clearly indicate that the
mountain-forming materials are distinct from the plains-forming
materials with corresponding mountain-forming and plains-type
signatures, respectively. This is consistent with Viking-era geologic
investigations \[2,8\].

We have developed an intelligent software system (referred to here as
Machine Learning) for robust analysis of hyper-spectral Thermal Emission
Spectrometer (TES) data (e.g., \[17-20\]) with the impetus to determine
whether the rock materials of the ancient Thaumasia highlands comprise
rock materials beyond just basalt/basaltic andesite as the published TES
maps have portrayed \[17,18,20\]. Through Machine Learning Systems we
can perform expeditious comparative analysis among any type of
multispectral image information. Using Geographic Information Systems,
we can also readily separate out ancient mountain-forming materials from
relatively young plains-forming materials based on published geologic
information and couple the geologic information with the Machine
Learning-based results to determine the density of pixels of both end
member types in both the mountain-forming and plains-forming rock
materials.

The results clearly indicate that there is a spectral distinction
between the two types of materials. But what does the distinction mean?
Clearly from the results at least we can say that the Thaumasia
highlands mountain range comprises a greater diversity of rocks than
just basalt-basaltic andesite. But can we properly identify the rock
types that compose the mountain-forming materials with existing orbital
platforms? For example, will CRISM be able to accurately identify
ancient rock materials that may be poking up through Tharsis-era
mantles?

Table 2. Corresponding with Figure 15, the TES data was classified
through Machine Learning by selecting pixels of quality TES strips that
occur in the ancient mountain-building materials and younger
plains-forming materials. The Geology has been reclassified into two
units: Ancient (mostly Early and Middle Noachian---Stage 1 map units)
and Young (Late Noachian and younger---Stages 2-4 map units) based on
\[2\]. The density results clearly indicate that the mountain-forming
materials are distinct from the plains-forming materials with more
dominant mountain-type and plains-forming-type signatures, respectively.
This is consistent with Viking-era geologic investigations, interpreted
to be largely basement complex and basaltic lava flows, respectively,
based on Viking-era geologic investigations \[2,8\].

Determining the composition of the Thaumasia highlands mountain range is
of first order importance since the range records an ancient part of
Mars' evolution, which includes possible Earth-like evolutional phases
such as plate tectonism, particularly during its embryonic stages of
evolution \[5\]. In addition to the Thaumasia highlands mountain range,
there are other markers of an ancient Mars that are difficult to explain
in the absence of plate tectonism \[3\], including the Coprates rise
mountain range \[1,2\] and other tens to thousands-km-long structures
such as Tempe Mareotis Fossae and Phlegra Montes (Fig. 1). Many of the
features (a) are interpreted to be the result of compressional
deformation such as thrust faulting \[2-4\], (b) occur among highly
degraded promontories (interpreted to be silicate-rich constructs or
intrusives \[8\]), (c) are embayed by relatively younger rock materials
\[8\], and (d) form the margins of elongated basins and "banded"
magnetic anomalies \[11\] (such as those in the Terra Cimmeria and Terra
Sirenum regions), similar to what is observed in geologic terrains of
Earth that have recorded plate tectonism (e.g., for further details on
why the banded anomalies in Arabia Terra and Terra Cimmeria may be
explained by plate tectonism, see \[13,24\], respectively). Other
seemingly anomalous observations in regard to the geological evolution
of Mars include major variations in crustal thickness, from thin beneath
the northern plains (\~30 km) to thick (\~60 km) beneath the southern
highlands and Tharsis \[25\], and linear crustal magnetization anomalies
of remarkable intensity that occur in the southern highlands \[11-13\].

Though Mars is commonly viewed as a one plate planet based largely on
geophysical and geochemical arguments, mainly from analysis of SNC
meteorites \[14,15\], MO, MEX, MRO, and the Mars Exploration Rovers are
increasingly showing a greater diversity of rock types for Mars such as
hematite, andesite, sulfates, and even quartz-bearing granitoids, etc.
\[18, 26-30\]. For example, detailed chemical compositional studies of
volcanic plains and adjacent ancient uplands are available for the
Spirit landing site in Gusev Crater. The plains consist of olivine-rich
basalts \[31\]. The adjacent Columbia Hills contain a more ancient suite
of complex alkali volcanic rocks \[32\]. Locally these include rocks
highly enriched in volatile elements, and there is evidence of explosive
volcanism followed by aeolian reworking of pyroclastic materials \[33\].

Basement complex may present an alternative to hematite, sulfates,
basalt, and basaltic andesite in the ancient rock record. With
resolutions as high as 25 centimeters per pixel, CRISM should shed
further light on the potential for such an ancient rock record.

IV\. Summary

The results of our investigation coupled with recent MGS-, MO-, and Mars
Express-based findings, which indicate a greater diversity of rock types
through recent data acquisitions, are promising, and designing an
effective system to perform expeditious analysis of huge data sets such
as TES and THEMIS will ultimately lead to an improved understanding into
the geological evolution of Mars. The results presented here indicate
that the ancient mountain-forming materials record a distinct thermal
infrared emission signature from the plains-forming materials. This is
consistent with Viking-era, geological mapping-based interpretations
that the mountain-forming materials could be comprised of a diversity of
rock types, which includes basement complex, whereas the plains-forming
materials are mostly volcanic. Such a potential rock record and possible
implications on Mars' embryonic stages of planetary evolution underscore
the necessity for further investigation through MGS, MO, Mars
Reconnaissance Orbiter (MRO), and future science-driven reconnaissance
missions. Ongoing investigation includes refining the fidelity of the
mineral mapping through the addition and deletion of materials from the
spectral database. This will produce a suite of minerals most suited to
modeling the actual surface materials. Through application of the
refined spectral database, we anticipate modest improvements to the
preliminary mineral interpretations. A mixing model will also be applied
in a couple of different configurations such as in the case of the
clustering results from the artificial intelligence algorithm, which
will be used to separate contiguous regions of specific spectral types.
This information will then be modeled using a linear mixing algorithm to
determine if previously separated spectral classes can reveal more
detailed mineralogical analyses using TES.

Moreover, in addition to the scientific results obtained as discussed
above, this study has also demonstrated clearly that the machine
learning methods are effective in unraveling geologic histories of Mars
and other planetary bodies, as it allows expeditious comparative
analysis of tier-scalable information. In this particular investigation,
various algorithms in machina learning (endmember separation, supervised
classification, clustering análisis, etc.) appled to the TES data show
that there is a clear distinction between the ancient mountain ranges
and the much younger lava plains. The same approach could be used for
identifying anomalies through robotic reconnaissance (e.g., transient
events such as spring-fed activity or volatile release, water-ice vs.
rocks, etc.) while in transit (e.g., rovers) using diverse information
sets at varying scales.

REFERENCES

\[1\] J.M. Dohm, J.C. Ferris, V.R. Baker, R.C. Anderson, T.M. Hare, R.G.
Strom, N.G. Barlow, K.L. Tanaka, J.E. Klemaszewski, D.H. Scott, "Ancient
drainage basin of the Tharsis region, Mars: Potential source for outflow
channel systems and putative oceans or paleolakes," *J. Geophys. Res.*,
vol. 106, pp. 32,943-32,958, 2001a.

\[2\] J.M. Dohm, K.L. Tanaka, T.M. Hare, "Geologic map of the Thaumasia
region of Mars," *US Geol. Survey Map I-2650*, 2001b.

\[3\] F. Anguita, C. Fernández, G. Cordero, S. Carrasquilla, J. Anguita,
A. Núñez, S. Rodriguez, and J. Garcia, "Evidences for a
Noachian-Hesperian orogeny in mars," *Icarus*, vol. 185, pp. 331-357,
2006.

\[4\] M. Grott, E. Hauber, S.C. Werner, P. Krongberg, and G. Nuekum,
"Mechanical modeling of thrust faults in the Thaumasia region, Mars, and
implications for the Noachian heat flux," *Icarus*, vol. 186, pp.
517-526, 2007.

\[5\] V.R. Baker, S. Maruyama, J.M. Dohm, "Tharsis superplume and the
geological evolution of early Mars, in *Superplume: beyond plate
tectonics*, D.A. Yuen, S. Maruyama, S.-i. Karato, and B.F. Windley, B.F.
Eds. Springer, Geophysics and Geodesy.

\[6\] J.M. Dohm, V.R. Baker, S. Maruyama, R.C. Anderson, "Traits and
evolution of the Tharsis superplume, Mars," in *Superplume: beyond plate
tectonics*, D.A. Yuen, S. Maruyama, S.-i. Karato, and B.F. Windley, B.F.
Eds. Springer, Geophysics and Geodesy, in press.

\[7\] W.K. Hartmann, and G. Neukum, "Cratering chronology and the
evolution of Mars," *Spa. Sci. Rev.*, vol. 96, pp. 165-194, 2001.

\[8\] D.H. Scott, and K.L. Tanaka, "Geologic map of the western
equatorial region of Mars," *USGS Misc. Inv. Ser. Map I-1802-A*
(1:15,000,000).

\[9\] Squyres, S. W. et al., "The Spirit Rover\'s Athena Science
Investigation at Gusev Crater, Mars," *Science*, vol. 305, pp. 794-799,
2004a.

\[10\] S.W. Squyres, et al., "In situ evidence for an ancient aqueous
environment at Meridiani Planum, Mars," *Science*, vol. 306, p. 1709,
2004b.

\[11\] M.H. Acuña, et al., "Global distribution of crustal magnetization
discovered by the Mars Global Surveyor MAG/ER experiment," Science, vol.
284, pp. 790-793, 1999.

\[12\] J. Arkani-Hamed, "Thermoremanent magnetization of the martian
lithosphere," *J. Geophys. Res.*, vol. 108, 10.1029/2003JE002049, 2003.

\[13\] J.E.P. Connerney, et al. (2005), Tectonic implications of Mars
crustal magnetism, *Science*, *102*, 14970--14975.

\[14\] A.N. Halliday, H. Wanke, J-L Birck, R.N. Clayton, "The accretion,
composition andearly differentiation of Mars," *Space Sci. Rev.,* vol.
96, 197--230, 2001.

\[15\] F. Nimmo, K.L. Tanaka, "Early crustal evolution of Mars," Ann.
Rev. Earth Planet. Sci., vol. 33, pp. 133-161, 2005.

\[16\] A.G. Fairén, J. Ruiz, F. Anguita, "An origin for the linear
magnetic anomalies on Mars through accretion of terranes: implications
for dynamo timing," Icarus 160, pp. 220-223, 2002.

\[17\] P.R. Christensen, et al., "Identification of a basaltic component
on the martian surface from Thermal Emission Spectrometer data," *J.
Geophys. Res.* 105, pp. 9609-9621, 2000.

\[18\] J.L. Bandfield, V.E. Hamilton, and P.R. Christensen, "A global
view of Martian surface compositions from MGS-TES," *Science,* vol. 287,
p. 1626, 2000.

\[19\] M.D. Smith, J.L. Bandfield, and P.R. Christensen, "Separation of
atmospheric and surface spectral features in Mars Global Surveyor
Thermal Emission Spectrometer (TES) spectra," *J. Geophys. Res.*, vol.
104 pp. 9589-9608, 2000.

\[20\] J.L. Bandfield, and M.D. Smith, "Multiple emission angle
surface-atmosphere separations of Thermal Emission Spectrometer data,"
*Icarus* vol. 161, 47-65, 2003.

\[21\] M.B. Wyatt, and H.Y. McSween, "Spectral evidence for weathered
basalt as an alternative to andesite in the northern lowlands of Mars,"
*Nature*, vol. 417, pp. 263-266, 2002.

\[22\] Ruff, S. W., "Basaltic Andesite or Weathered Basalt: A New
Assessment," *paper presented at Sixth International Conference on
Mars*, Lunar and Planetary Institute, Pasadena, California, July 20-25
2003.

\[23\] R.C. Anderson, J.M. Dohm, A.F.C. Haldemann, T.M. Hare, V.R.
Baker, "Tectonic histories between Alba Patera and Syria Planum, Mars,
Mars," *Icarus*, vol. 171, pp. 31-38, 2004.

\[24\] A.G. Fairén, J. Ruiz, and F. Anguita, "An origin for the linear
magnetic anomalies on Mars through accretion of terranes: implications
for dynamo timing," *Icarus*, vol. 160, pp. 220-223, 2002.

\[25\] M.T. Zuber, et al., "Internal structure and early thermal
evolution of Mars from Mars Global Surveyor topography and gravity,"
*Science*, vol. 287, pp. 1788-1793, 2000.

\[26\] P.R. Christensen, et al., "The Mars Global Surveyor Thermal
Emission Spectrometer experiment: Investigation description and surface
science results," *J. Geophys. Res.*, vol. 106, pp. 23,823-23,871,
2001a.

\[27\] P.R. Christensen, R.V. Morris, M.D. Lane, J.L. Banfield, M.C.
Malin, "Global mapping of Martian hematite mineral deposits: Remnants of
water-driven processes on early Mars," *J. Geophys. Res.*, vol. 106, pp.
23,873-23,885, 2001b.

\[28\] P.R. Christensen, et al., "The Igneous Diversity of Mars:
Evidence for Magmatic Evolution Analogous to Earth," *Lunar Planet. Sci.
Conf., XXXVI*, #1273 (abstract) \[CD-ROM\], 2005.

\[29\] A. Gendrin, et al., "Sulfates in martian layered terrains: The
OMEGA/Mars Express view," *Science*, vol. 307, pp. 1587-1591, 2005.

\[30\] R. Rieder, et al., "Chemistry of rocks and soils at Meridiani
Planum from the Alpha Particle X-ray Spectrometer, *Science,* vol.
306*,* pp. 1746-1749, 2004.

\[31\] H.Y. McSween, et al., "Characterization and petrologic
interpretation of olivine-rich basalts at Gusev Crater, Mars," *J.
Geophys. Res.*, vol. 111, E02S10, doi:10.1029/2005JE002477, 2006a.

\[32\] H.Y. McSween, et al., "Alkaline volcanic rocks from the Columbia
Hills, Gusev crater, Mars," *J. Geophys. Res.*, vol. 111, E09S91,
doi:10.1029/2006JE002698, 2006b.

\[33\] S.W. Squyres, et al., 2007, "Pryroclastic activity at Home Plate
in Gusev Crater, Mars," *Science*, v. 316, pp. 738-742, 2007.

\[34\] G.J. Taylor, et al., "Bulk composition and early differentiation
of Mars,"*J. Geophys. Res.*, vol. 111, E03S10, doi:10.1029/2005JE002645,
2006.