Composition of Titan’s Dunes:
Constraints from Cassini VIMS and RADAR
Principal Investigator: Dr. Paul O. Hayne (Jet Propulsion Laboratory)
Co-Investigators: Dr. Alexander G. Hayes (Cornell University), Dr. Thomas B. McCord
(Bear Fight Institute), Dr. Jean-Philippe Combe (Bear Fight Institute)
Collaborators: Dr. Jason W. Barnes (University of Idaho), Dr. Oded Aharonson
(Weizmann Institute), Dr. Antoine Lucas (University of Paris), and Dr. Christophe Sotin
(Jet Propulsion Laboratory)
Proposal submitted in response to NASA solicitation NNH13ZDA001N-CDAPS: Cassini
Data Analysis and Participating Scientists
May 3, 2013
Table of Contents
SCIENCE-TECHNICAL-MANAGEMENT ......................................................................................1
1 SCIENTIFIC RATIONALE AND OBJECTIVES........................................................................................... 1
1.1 Motivation and Proposed Research ................................................................................. 1
1.2 Background ...................................................................................................................... 2
2 TECHNICAL APPROACH AND METHODOLOGY .................................................................................... 3
2.1 Data Acquisition and Reduction ....................................................................................... 3
2.2 Atmospheric Correction to VIMS Data ............................................................................. 5
2.3 Dune Mask from De-noised RADAR Data ........................................................................ 7
2.4 Isolation of Dune Reflectance Spectra ............................................................................. 8
2.5 Composition ................................................................................................................... 10
3 PERCEIVED IMPACT..................................................................................................................... 11
4 RELEVANCE ............................................................................................................................... 11
5 WORK PLAN .............................................................................................................................. 12
5.1 Key milestones for accomplishments ............................................................................ 12
5.2 Management structure and role of personnel .............................................................. 13
APPENDIX: PARTICIPATING SCIENTIST REQUEST ................................................................... 15
A.1 OBJECTIVES AND EXPECTED CONTRIBUTIONS .............................................................................. 15
A.1.1 Science background and objectives ........................................................................... 15
A.1.2 Capabilities and Qualifications .................................................................................. 17
A.2 RELEVANCE TO CASSINI SCIENCE GOALS ..................................................................................... 18
A.3 COLLABORATIONS WITH THE CASSINI SCIENCE TEAM .................................................................... 19
A.4 COMPLIANCE WITH CASSINI RULES ............................................................................................ 19
REFERENCES ........................................................................................................................ 20
Composition of Titan’s Dunes
BIOGRAPHICAL SKETCHES .................................................................................................... 25
PAUL OTTINGER HAYNE .................................................................................................................. 25
ALEXANDER GERARD HAYES ............................................................................................................ 28
JEAN-PHILIPPE COMBE ................................................................................................................... 29
THOMAS B. MCCORD .................................................................................................................... 30
CURRENT AND PENDING SUPPORT ....................................................................................... 31
PRINCIPAL INVESTIGATOR: PAUL O. HAYNE ........................................................................................ 31
CO-INVESTIGATOR: ALEXANDER G. HAYES ......................................................................................... 32
CO-INVESTIGATOR: JEAN-PHILIPPE COMBE ........................................................................................ 34
CO-INVESTIGATOR: THOMAS MCCORD ............................................................................................. 35
BUDGET JUSTIFICATION ....................................................................................................... 36
BUDGET JUSTIFICATION: NARRATIVE ................................................................................................. 36
Summary of Personnel and Work Efforts.............................................................................. 36
Facilities and Equipment ....................................................................................................... 36
Rationale and Basis of Estimate ........................................................................................... 36
BUDGET JUSTIFICATION: DETAILS ..................................................................................................... 37
Year 1: ................................................................................................................................... 37
Year 2: ................................................................................................................................... 37
BUDGET DETAILS.................................................................................................................. 39
BUDGET JUSTIFICATION: PARTICIPATING SCIENTIST REQUEST ............................................... 40
NARRATIVE ................................................................................................................................... 40
Summary of Personnel and Work Efforts .............................................................................. 40
Facilities and Equipment ....................................................................................................... 40
Rationale and Basis of Estimate ........................................................................................... 40
DETAILS ....................................................................................................................................... 40
Year 1 .................................................................................................................................... 40
Year 2 .................................................................................................................................... 40
BUDGET DETAILS: PARTICIPATING SCIENTIST REQUEST ......................................................... 41
2
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Science-Technical-Management
1 Scientific Rationale and Objectives
1.1 Motivation and Proposed Research
Titan’s equatorial dune fields constitute a major geologic terrain, extending from
approximately -30 to 30 °N latitude and encompassing nearly all longitudes. While these
features have been studied extensively with a variety of Cassini datasets (e.g. Lorenz
and Radebaugh 2007; Le Gall et al., 2012), their composition remains uncertain (Barnes
et al., 2008). Cassini RADAR data indicate optical behavior consistent with porous solid
hydrocarbons, or even extremely porous water ice deposits (Janssen et al., 2009).
Reflectance data from the Cassini Visual and Infrared Mapping Spectrometer (VIMS)
that are not corrected for atmospheric effects are highly ambiguous, due to the strong
absorption and scattering within Titan’s hazy, methane-rich atmosphere. Preliminary
analysis of the VIMS data indicates that the dunes are somewhat less water ice-rich than
surrounding terrain, possibly indicating a hydrocarbon composition (Barnes et al., 2008).
However, this and other existing studies were limited to relative spectroscopy, due to
variable atmospheric effects. Furthermore, the limited number of VIMS image cubes
that have been analyzed have relatively low signal-to-noise. Finally, individual VIMS
spectra often average together dune and inter-dune deposits due to limitations in
spatial resolution.
We propose a new approach to investigating Titan’s dune composition. In the
proposed research, we will combine dune-fraction maps derived from RADAR data
with atmosphere-corrected VIMS data, in order to extract the unique spectral
signature of the dune material. Resulting spectra will be compared to those of
candidate materials previously measured in the laboratory, and then will be mapped to
units on Titan’s surface. The atmospheric correction has been successfully applied to
several of Titan’s important geologic features, including Tui Regio and the ejecta of
Sinlap crater (Hayne et al.,
2013), but the dunes pose a
challenge due to their sub-pixel
scale in the VIMS data. Our
approach
will
be
to
systematically
derive
atmosphere-corrected surface
reflectance spectra at 2.0, 2.7,
2.8, and 5.0 m for all of the
VIMS cubes publicly available
on the Planetary Data System
Figure 1. Comparison of dunes on Titan and Earth. The
(PDS) that include dunes imaged
dunes within the Belet region are morphologically distinct
from those in Fensal, but are they compositionally distinct?
From Le Gall et al. (2012)
Jet Propulsion Laboratory
Paul O. Hayne
1
Composition of Titan’s Dunes
by RADAR. We will then apply linear and non-linear spectral mixtures analysis (McCord
et al., 2008) to separate the contribution from the dunes, and map their compositional
variations among Titan’s dune fields.
1.2 Background
Sand dunes cover a significant portion (20%) of Titan’s equatorial regions
(Figure 1) and represent a detailed geomorphic record of Titan’s climate and surface
evolution. Previous studies of Titan’s dunes have focused on the spatial variation of
observed dune morphologies and their interactions with local topography (e.g., Lorenz
et al., 2006; Radebaugh et al., 2008, 2010). These studies have provided a basis for
interpreting wind direction (e.g., Lorenz et al., 2006; Radebaugh et al., 2008; Rubin and
Hesp, 2009, Savage et al., 2011) sediment supply (e.g., Radebaugh et al., 2010; LeGall et
al., 2012) and atmospheric conditions, such as boundary layer depth (e.g, Lorenz et al.,
2010) and aridity (e.g., LeGall et al. 2012, LeGall et al. 2013). What these previous
studies have been unable to address, however, is what the dunes are made of. While
dune particles are typically assumed to be derived from organic photolysis products
(e.g., Lorenz et al. 2006), this has yet to be rigorously demonstrated from observation.
We propose to combine the spatial resolution of the Cassini Synthetic Aperture Radar
(SAR) (300 m/pixel) with the spectral information provided by VIMS to derive the
composition of dune and interdune material. The results of the proposed study will be
highly complementary to ongoing studies of dune morphology and spatial variation.
Figure 1. Global mosaic of Synthetic Aperture Radar (SAR) observations of Titan in an equidistant
cylindrical projection. SAR data is shown on top of a Visual Infrared Mapping Spectrometer (VIMS)
basemap. Outlines for each of the major dune fields are shown. Note that dune field borders are not
strictly defined and can vary from study to study. Previous work (Lorenz et al., 2006; Radebaugh et al.,
2008) has identified dunes within all of the targeted study areas.
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Paul O. Hayne
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Composition of Titan’s Dunes
2 Technical Approach and Methodology
Our goal in analyzing the Cassini data is to isolate reflectance spectra of the dune
materials from those of other geologic units, including the inter-dune material. The
approach consists of four interrelated components:
1) Acquire relevant VIMS and RADAR data, and perform basic processing for use in
the following steps
2) Apply atmospheric correction to VIMS reflectance data in order to derive a more
accurate representation of true surface reflectivity spectra
3) Apply ‘de-noising’ algorithm to RADAR data and produce dune fraction maps
coincident with VIMS reflectance maps
4) Isolate dune spectra through convolution of dune fraction with VIMS reflectance
and linear un-mixing of VIMS end-member spectra
Combining the results of these steps, we will compare the corrected dune (and interdune) spectra to those of materials known or expected to exist on Titan’s surface (e.g.
H2O ice, complex hydrocarbon ‘tholin’, solid and liquid CH4 and C2H6, CO2 ice, NH3 ice).
The final products will be compositional maps of the dune fields, and improved
understanding of the nature and origins of the materials comprising the dunes. The
following subsections describe each of the above components of the methodology in
more detail.
2.1 Data Acquisition and Reduction
All of the data needed to perform the proposed investigation are publicly
available on the NASA Planetary Data System as of February 1, 2013. Each member of
our team is experienced with one or both of the datasets, and is familiar with the
calibration pipelines and post-processing steps
required. In the process of preparing this
proposal, we have already identified two key
dune fields with geographically coincident (and
high-quality) RADAR and VIMS data: Fensal
(RADAR flyby T17, VIMS flyby T5 & T9), and Belet
(RADAR flyby T8, VIMS flyby T79). Figure 2 shows
the geographic location of the Belet ‘sand sea’
where the two datasets overlap. Because the
RADAR data are typically acquired at much higher
spatial resolution (300 m) than the VIMS data
(>10 km), sub-pixel un-mixing is required to
determine the contribution of the dunes to the
Figure 2. Example complementary
measured reflectance spectrum. Details of the
datasets from RADAR and VIMS.
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Paul O. Hayne
3
Composition of Titan’s Dunes
approach are given in Section 2.4.
VIMS Data
The Visual and Infrared Mapping Spectrometer (VIMS) (Brown et al., 2004)
consists of two spectrometer channels: the Visual channel covers the spectral range
from about 0.35 to 1.05 µm and the IR channel covers the range from about 0.8 µm to
5.1 µm. Here will use only the IR channel data, where diagnostic molecular vibrational
bands occur for the materials of interest. The pixel size can be as small as 0.25 x 0.5
mrad for the IR channel with nominal spectral sampling of 16.6 nm (256 bands). The
nominal data set is an image cube consisting of two spatial dimensions (typically 64x64)
and one spectral dimension. The data returned by VIMS consist of raw data numbers for
each spectral channel at each spatial pixel. Each spectral channel is assigned a
wavelength determined from the wavelength calibration, and the data numbers, once
the dark and background signal have been subtracted, are multiplied by a radiometric
response function for each pixel that relates raw instrument response to radiance. The
radiometric response function is derived from measurements made on the ground
before launch, enhanced with in-flight measurements of Venus, the Moon, Galilean
satellites, and several stars (cf. McCord et al. 2004).
Figure 3. T20 VIMS observations of Titan’s dunes in the Fensal region (60°W, 10°N). From Barnes et al.
(2008).
Typically, the dunes themselves are not resolved by VIMS, due to their narrow
width (300 m – 1 km) and inter-dune spacing of 1-5 km (Neish et al., 2010; Le Gall et
al., 2012), compared to typical surface resolutions of > 10 km. An important exception is
the T20 (where “T_” refers to the Titan flyby number) “noodle”, with a spatial resolution
of 500 m, comparable to that of the RADAR instrument (see below). Barnes et al.
(2008) studied these data and performed an initial spectroscopic analysis of the dune
and inter-dune materials (Fig. 3). As part of the proposed work, we will re-analyze these
data, this time correcting for atmospheric effects (Section 2.2) in order to enable
compositional analysis. We will also perform spectral mixtures analysis (Section 2.4) to
extract the T20 dune spectra from those of the inter-dune materials. Many other lowerresolution, high signal-to-noise VIMS observations of Titan’s dune fields are available,
but only a subset of these is spatially coincident with RADAR data. So far, we have
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Jet Propulsion Laboratory
Composition of Titan’s Dunes
identified the T5 and T9 (Fensal), and T79 (Belet) as particularly promising. As part of
this research, we will comb through the VIMS data for any other useful (exposure time >
80 ms, airmass < 3.0) dune field observations, though the aforementioned two datasets
are sufficient for accomplishing the proposed tasks.
RADAR Data
In the proposed investigation, we will utilize Cassini RADAR data acquired in SAR
imaging mode (Elachi et al., 2004). In this mode, topography is revealed by variations in
apparent reflectivity due to surface slopes relative to the angle of incidence. Thus, the
dunes appear as alternating bright/dark pairs and are easily identified in the SAR
images. From these basic data, dunes will be mapped using an automated algorithm and
by hand, as described in Section 2.3.
2.2 Atmospheric Correction to VIMS Data
Figure 4. Example modeled and measured VIMS
reflectance spectra of Titan. The thin solid line is a
spectrum of Enceladus (mostly water ice) mixed with
a neutral component with 2% reflectivity at all
wavelengths, displaying a strongly negative slope
from 2.7 to 2.8 m wavelength. When the darkened
Enceladus spectrum is placed under a simulated Titan
atmosphere (dashed line), it appears very similar to
the actual measured Titan reflectance spectrum
(thick solid line). In contrast, a neutral (2%
reflectance) material under the same atmosphere
(dotted line) is distinct from the measured Titan
spectrum. From Hayne et al. (2013)
Jet Propulsion Laboratory
Titan’s surface is obscured by a
thick absorbing and scattering
atmosphere,
allowing
direct
observation of the surface within only
a few spectral windows in the nearinfrared (Sotin et al., 2005; McCord et
al., 2006). Even within Titan’s near-IR
methane
windows,
radiance
measurements contain significant
contributions from diffusely scattered
radiation, especially at large phase
angles. In a recent publication (Hayne
et al., 2013), we developed a simple
radiative transfer model, constrained
by VIMS solar occultation data, which
can be applied to remove atmospheric
effects
from
reflectance
measurements of Titan’s surface.
Here, we briefly summarize this model
and its applicability to the proposed
research.
Accounting
for
multiple
reflections between the atmosphere
and surface, the reflectance measured
at the top of the atmosphere is then
Paul O. Hayne
5
Composition of Titan’s Dunes
R = Ra + RsTaTa* + Rs2 RaTaTa* +
= Ra + Rs
(1)
TaTa*
1- Rs Ra
where Ra is the reflectance of the atmosphere alone, Rs is the surface reflectance, Ta
and Ta* are the transmission functions for the atmosphere from above and below,
respectively (Liou, 2002, p. 365). The two terms in this equation represent the direct and
diffuse radiation fields, respectively. Under the approximation of an optically thin,
single-scattering atmosphere within the methane windows, equation (1) becomes
R = Rs e-t 0m¢ +
v0P
1- e-t m¢ .
4 ( m0 + m )
(
0
)
(2)
where m and m0 are the cosines of the solar incidence and emergence angles (provided
in the VIMS backplanes), v 0 is the combined single scattering albedo of the haze
particles and gas molecules, and P = P( m0 , m ) is the scattering phase function
(normalized to unity). Inverting this equation leads to an expression for the surface
reflectance, given the measured reflectance I / F , and the given photometric angles:
Rs = ( I / F ) et 0m¢ +
v0P
1- et m¢ .
4 ( m0 + m )
(
0
)
(3)
The coefficient of the second (diffuse) term can be found by fitting Titan’s reflectance as
the airmass grows large, when the surface is no longer visible and the haze reflectance
dominates,
v0P
(4)
R»
, for t 0 m ¢ 1.
4 m0 + m
(
)
This is the so-called atmospheric “path radiance” (Kaufman, 1993). We assume a
(
standard Henyey-Greenstein phase function, P(Q) = 1- g 2
) (1+ g
2
- 2g cosQ
)
32
, and
fit the VIMS reflectance data for    5.0 to determine the single scattering albedo  0
and the asymmetry parameter, g . Combining all data for the region 90-135W and 030N corresponding to Xanadu, we find best fit values at 2.8 m of g  0.4 and  0 
0.3, consistent with the results of Coustenis et al. (2006) for the 3-micron spectral region
(cf. West et al., 2005). For the 5-m window, we find best-fit values of g  0.4 and  0 
0.2. Equation (3), with the normal optical depths  0 ( ) derived from the occultation
measurements, provides a general atmospheric correction for the measured reflectance
within the methane windows subject to the given model assumptions. In practice, the
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Jet Propulsion Laboratory
Composition of Titan’s Dunes
2.0, 2.7, 2.8 and 5.0-m windows are the cleanest, and therefore will be the focus of
this investigation. The values of t 0 determined for these windows are approximately
0.4, 0.9, 0.2, and 0.1, respectively (Hayne et al., 2013). Figure 4 shows an example of
modeled spectra near 2.8-m applied to match VIMS data for the Xanadu region.
2.3 Dune Mask from De-noised RADAR Data
De-Noised
SAR
0
0 dB
0 dB
-15 dB
-15 dB
5
10
20
30
40 0
km
5
Dune Mask
No Dune
10
Dune
20
30
40 0
km
5
10
20
30
40
km
Figure 5. Example SAR image of the Fensal dune field. A: Standard SAR image from the PDS B: De-Noised
SAR image using the algorithm developed by Co-I Lucas C: Dune Mask generated using a threshold level of
-8 dB. At this threshold level, dunes take up 32.4% of the area shown.
In order to better constrain the composition of Titan’s dunes, we will utilize a dune
fraction map, derived from publicly available Cassini RADAR backscatter data. We will
derive these maps from de-noised SAR data (Lucas et al. 2011, 2012). Figure 5 shows the
results of a simple thresholding algorithm applied to the de-noised data in the Fensal
dune field. A classification algorithm (i.e., using ENVI software) has been used on the denoised T17 swath in order to extract a mask that indicates the location of dunes and
inter-dunes as shown on Fig. 6. In the proposed work, we will project the highestresolution atmosphere-corrected VIMS cubes onto this and other dune fraction maps, to
compute a weighted average spectrum of dune and non-dune pixels (Section 2.4). The
creation of dune masks will be the primary responsibility of Co-I Hayes, Collaborator
Lucas, and an undergraduate student supervised by Co-I Hayes. Below is the expected
workflow for dune mask creation:
 PI Hayne and Co-I Combe will deliver the latitude and longitude boundaries of
each pixel in a given VIMS spectral cube encompassing Titan’s dunes
 Co-I Hayes and the UG student will cross-reference each footprint against preexisting maps of the dune areas on Titan and keep only pixels that lie entirely on
dune/interdune material (i.e., obstacle free).
 SAR images of dune-free areas that contain VIMS footprints will be sent to Co-I
Lucas for de-noising, if necessary.
 For a subset of each observation, the student will manually determine
dune/interdune fractions within each VIMS footprint in both the regular and denoised SAR data. These results will be used to validate the output of the
automated classification algorithms.
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7
Composition of Titan’s Dunes



A simple thresholding algorithm (See Figure 5) will be applied to each de-noised
image to determine dune/interdune fraction. The de-noised images will also be
classified using the built-classifications algorithms available in the IDL ENVI
software.
The parameters of both the thresholding and ENVI classification algorithms will
be adjusted to match the results of the manually determine dune/interdune
fractions.
Resulting dune/interdune fractions will be delivered to PI Hayne for use in the
following tasks.
Figure 6. Top: De-noised SAR data from Cassini RADAR, acquired on Titan flyby T17. Bottom: Dune
mask created from the de-noised radar data, where white indicates dune material is present (see text
for methodology).
2.4 Isolation of Dune Reflectance Spectra
To constrain the composition of Titan’s dunes, we will generate corrected
spectra from the highest- resolution VIMS cubes, taking an average weighted by the
fractional area occupied by dunes, based on the RADAR dune mask (Section 2.3). This
weighted-average spectrum will reduce the ambiguity in the spectra of the dune fields,
where it is difficult to distinguish dune from inter-dune. Combined with the above steps,
the procedure is as follows:
1) Perform atmospheric correction on VIMS data
2) Spatially co-register the VIMS and RADAR data
3) Assign a weight to each VIMS pixel based on the area fraction classified as
dune material in the RADAR data
4) Calculate the average spectrum, weighted by the dune-fraction values
Results of a pilot study are summarized in Figure 7. A complementary spectrum
representing the inter-dune materials will also be calculated for each separate dune
field. Variations among the dune field substrates may be related to their observed
morphological differences (Le Gall et al., 2012). Where the signal-to-noise is high
enough, we will also look at spectra of individual VIMS pixels where the dune fraction is
determined to be > 50%. After this process, we will apply the Spectral Mixtures Analysis
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Composition of Titan’s Dunes
(SMA) method to quantitatively separate the components making up the dune and
inter-dune materials.
Figure 7. Preliminary analysis of the co-registered VIMS spectral data in the Fensal dune field
(CM_1514302990_1, upper left inset) and dune mask derived from RADAR data acquired on the T17
flyby. The lower left panel shows the ratio of the VIMS weighted average dune spectrum to the interdune weighted average spectrum. Differences of 5% in reflectivity are apparent, suggesting the dune
spectra can be distinguished from inter-dune spectra. In the proposed research, we will quantify and
map these compositional differences.
Spectral Mixtures Analysis
Spectral Mixing Analysis (SMA) techniques will be used to find compositional
endmembers from the VIMS data, and correlate their contributions with the dune
fraction map from RADAR. This approach is complementary to the weighted-average
technique described above, rather than sequential. Comparing VIMS-derived mixing
coefficient maps to the RADAR dune fraction maps will help us validate the approach
and understand the different contributions to the dune field spectra.
SMA methods are a well-established technique for separating linear (e.g. areal)
mixtures of spectra (Adams and Gillespie, 2006), sharing similarities with the Principal
Component Analysis (PCA) or Karhunen–Loève transformation (KLT) for data de-
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Paul O. Hayne
9
Composition of Titan’s Dunes
correlation and surface unit enhancement (Richards, 1994). The SMA method requires
either the search of pixels corresponding to the purest composition within a scene (the
spectral endmembers), or the use of reference spectra for which the composition is
known, acquired in the laboratory. Taking the average reflectance at all the wavelengths
as a reference, we fit the correlation trend of each wavelength by a straight line to the
data spanning the largest and the smallest values. In order to retrieve potential
additional spectral endmembers, we assume the spectra are mostly a linear mixture of
the brightest and darkest components. If more than two spectral components can be
detected, we remove the linear trend that fits the data in the two-dimensional scatter
plots and then calculate the residual spectral shapes. These residuals are expected to be
representative of spectra of other surface materials, or other effects from the
atmosphere or the instrument.
Relative abundances of surface materials can be retrieved by assuming that each
observed spectrum is a linear combination of endmember spectra. In practice, we
perform the SMA of VIMS data by using the Multiple-Endmember Linear Spectral
Unmixing Model (MELSUM) (Combe et al., 2008). This model has been developed to
account for mixtures and to map areal proportions of materials. The algorithm
guarantees mixing coefficients to be strictly positive, and the sum of the fractions to
equal unity. The spectral library of image endmembers is given as input for MELSUM. A
spectrally neutral (flat), dark (set with zero values) endmember can be used to account
for shading effects. Image fractions for all the image spectral endmembers are
interpreted as contextual compositional maps of the main surface materials. For the
present study, we will retrieve relative abundances of dune and inter-dune materials
using the weighted average spectra (see above), and then also retrieve abundances
using endmembers derived independently using the VIMS data alone. The latter can be
correlated with the RADAR dune fraction maps to ensure that the compositional
differences are in fact associated with the dune/interdune materials.
2.5 Composition
After atmospheric correction and endmember extraction, the VIMS data give a
more accurate representation of Titan’s surface spectral units, whose reflectivity is
diagnostic of the materials’ composition and physical state (i.e. chemical makeup, solid
or liquid phase, particle size). Uncertainties in reflectivity are determined by standard
error propagation for each model parameter. In our pilot studies of the dune fields, we
find uncertainties < 20% in surface reflectivity for the 2.0, 2.8, and 5.0-μm windows,
with better precision at the longer wavelengths. We will compare corrected surface
reflectivity values to simulated and laboratory-measured spectra of candidate materials
for Titan’s dunes. Some materials for which we have optical constants include: water ice
(Warren and Brandt 2008), alkanes (Clark et al. 2009), carbon dioxide ice (Hansen 1997),
and “tholin” (e.g. Imanaka et al. 2012). Other possibilities will also be considered,
including materials known to be present on other icy satellites (Dalton et al. 2010). To
calculate reflectivity spectra (including non-linear mixtures), we utilize a standard deltaEddington model (Wiscombe and Warren, 1980), which accounts for multiple scattering
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Composition of Titan’s Dunes
and absorption within particulate
media with arbitrary grain size
distribution (Hayne et al., 2012).
Variations in reflectivity among the
candidate materials are significantly
larger than the uncertainties in the
atmospheric correction, and the
multi-dimensional spectral space
allows even greater leverage on
identification.
3 Perceived Impact
Figure 8. High-resolution reflectance spectra compared
This investigation into the to atmosphere-corrected VIMS spectra of three surface
composition of Titan’s dune fields features. The dune field spectrum (in the Shangri-La
has fundamental importance for the region) averages both dune and inter-dune materials.
understanding of Titan’s geological
evolution and the processes shaping the surface. Dunes represent a link between the
geology and the recent climate, through the active redistribution of granular materials
under dry, desert-like conditions. Hypotheses concerning the origin of the particles
making up the dunes can be directly tested through knowledge of their composition. For
example, inter-particle cohesion is strongly dependent on composition, which may
therefore distinguish between merger/growth and breakup/erosion formation
mechanisms (Aharonson et al., 2012). Furthermore, if the dunes are in fact composed of
hydrocarbons precipitated from the atmosphere, they may represent the largest known
reservoir of such materials on Titan (Le Gall et al., 2011), which has important
implications for the moon’s evolving climate (Lorenz, 1996). Up to now, very little work
has been done to rigorously constrain the composition of Titan’s dunes using the VIMS
data, due to the typically coarse spatial resolution relative to the dune scale. The results
of this study will therefore fill a critical gap in understanding, by leveraging the spatial
resolution of the RADAR data and the spectral information contained in the VIMS data.
Our results will inform future observational investigations using more sophisticated
techniques, as well as theoretical studies of the origins, formation, and transport of
Titan’s dune material. Another benefit to the community will be the availability of the
dune mask data for future investigations.
4 Relevance
This research will contribute to the main purposes of CDAPS, as described in
ROSES 2013 in that it will “enhance the scientific return of the Cassini mission by
broadening scientific participation in the analysis and interpretation of the data
returned by the mission.” It also will contribute to NASA’s intent to plan, develop and fly
new Outer Solar System missions, such as to Titan. Both the knowledge gained by this
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Composition of Titan’s Dunes
proposed research and the new young scientists educated by this effort will directly
support new NASA mission development to Titan. The proposal topic and expected
results are very relevant to the most recent roadmap recommendations by the NRC
“Vision and Voyages for Planetary Science in the decade 2013-2022.” For example the
Priority Questions and all three Crosscutting Themes (3-1) are addressed in that Titan’s
composition and the processes altering it yields information on each: “Building New
Worlds—understanding solar system beginnings, Planetary Habitats—searching for the
requirements for life, and Workings of Solar Systems— revealing planetary processes
through time.” Titan is specifically addressed in Section 8: Active Worlds and Extreme
Environments. Further, the most recent document states that “All three of the
crosscutting science themes for the exploration of the solar system motivate further
exploration of the outer planet satellites,” especially Titan. Finally, the effort has a major
educational aspect in that it will significantly contribute to the career development of
two early-career Ph.D. scientists (PI Hayne, Co-I Hayes, and Co-I Combe) and further
acquaint them with Cassini and the NASA research community, programs and missions
in general.
5 Work Plan
5.1 Key milestones for accomplishments
5.1.1 First year
We will acquire and process the Titan VIMS data (Hayne, Combe, Barnes), as well
as the RADAR data (Hayes, Lucas) for selected regions of interest, notably the Belet and
Fensal ‘sand seas’. From these data, classification maps of dune and inter-dune will be
generated (Lucas, Hayes/student). After applying and validating the atmospheric
correction to the VIMS data (Hayne), we will use the corrected VIMS data along with our
established spectral mixture analysis (SMA) technique to derive the dune spectra and
map surface constituents (Combe). In the first year, we will make preliminary
comparisons to specific candidate molecules and mixtures suspected to compose the
dunes (McCord, Hayne, Barnes, Sotin, Aharonson, Hayes). These results will be written
up and presented at the LPSC conference in The Woodlands, TX, after then end of the
first year.
5.1.2 Second year
In the second year, we will shift focus to the spectral analysis (Combe, Hayne),
while continuing to incorporate newly available data (Hayne, Hayes, Lucas) and improve
the atmospheric correction (Hayne). Accurate dune and inter-dune spectra will enable
quantitative comparison with candidate materials (McCord, Barnes, Hayne, Sotin,
Aharonson). We will also investigate similarities and differences in composition among
the different dune fields (All). At least one publication in a major journal will result from
the two years of effort. We will also make the dune masks and resulting dune and inter-
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Composition of Titan’s Dunes
dune VIMS spectra available to other researchers, through either the NASA PDS or
supplementary materials of our publications, whichever is deemed appropriate.
5.2 Management structure and role of personnel
We have assembled the proposing interdisciplinary team and have constructed
and utilized custom designed data processing and analysis systems to specifically
analyze the VIMS spectral data and the RADAR data. The team includes (1) very
experienced scientists familiar with the VIMS IR data and (2) several young scientists
developing their careers. Each team member has an extensive track record of
productivity, and each has made major contributions to the science of Titan in the past.
We also bring to bear young, well-qualified scientists who are not members of the
Cassini teams or the Cassini Data Analysis Program (CDAP). Our efforts will provide a
base of results that will enable a much broader community of scientists to use the
VIMS data, because these data, although powerful, are not easily utilized. An
important aspect of the proposed research is the participation of an undergraduate
student (supervised by Co-I Hayes and PI Hayne) in mapping dunes using the Cassini
RADAR dataset.
PI Paul Hayne will lead the scientific efforts of the proposed investigation. He
will also contribute his knowledge and understanding of spectral analysis and noise
statistics, gained partly through his active role over the past several years in VIMS Titan
data analysis. He has led recent attempts to demonstrate the value of solar occultations
by VIMS for surface composition analysis and has published the results in the peerreviewed literature.
Co-I Alexander Hayes will lead the RADAR data analysis and dune mapping. Dr.
Hayes is a recognized expert on these data and the geological evolution and present
state of Titan, in general. He will also co-advise a summer undergraduate student based
at Cornell University, who will learn to use existing software to identify and map dune
and inter-dune materials on Titan’s surface.
Co-I Jean-Philippe Combe will focus on VIMS IR spectral image analysis using the
various methods and tools, especially Spectral Mixing Analysis and his additional
technique developments. Dr. Combe will also apply his extensive experience with VIMS
image data and their manipulation using ENVI as well as other mission spectral imagery,
including for his Ph.D. dissertation research (Combe 2005).
Co-I Thomas McCord will apply his extensive experience in the physics of
planetary solid-state materials, spacecraft and laboratory experimental studies, data
analysis, with space missions and in particular his recent experience analyzing Titan
surface composition, and with mentoring young scientists. Dr. McCord has extensive
experience over 40 years processing and analyzing telescopic and spacecraft
spectroscopic data and leading group efforts to study planetary objects including for
VIMS and Titan. He has been consistently very productive, as his publications indicate.
Collaborator Jason Barnes has published numerous papers on the surface
composition, morphology, and geologic history of Titan, primarily using the VIMS
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Composition of Titan’s Dunes
dataset. Dr. Barnes will assist in the acquisition of appropriate datasets, spectral
analysis, and interpretation of results.
Collaborator Christophe Sotin has extensive experience with the VIMS Titan
measurements (having designed many of the observations), and will aid in their
interpretation.
Collaborator Antoine Lucas has expertise in processing RADAR data, and will
generate masks of the dunes for comparison with VIMS.
Collaborator Oded Aharonson has wide ranging expertise on the geophysics,
climate, and active processes shaping the surface of Titan, as well as RADAR data, and
will consult primarily on the interpretation of the compositional data.
Table: Summary of tasks and description of efforts (working months *) for all team members
Description of Effort
Task 1
Obtain and process VIMS and RADAR data
Task 2
Apply atmospheric correction to VIMS data
Team member Year 1 Year 2 Total
P. Hayne
0.25 0.25 0.50
J-P. Combe
0.05 0.00 0.05
A. Hayes
0.10 0.05 0.15
J. Barnes
0.10 0.00 0.10
A. Lucas
0.15 0.15 0.30
P. Hayne
1.00
0.75 1.75
A. Hayes
Task 3
Apply de-noising algorithm and classify dune material in A. Lucas
RADAR data
O. Aharonson
0.25 0.20 0.45
0.25 0.25 0.50
0.05 0.05 0.10
P. Hayne
1.00 0.50 1.50
J-P.
Combe
0.50 1.00 1.50
Task 4
Isolate dune and inter-dune spectral components,
T. McCord
0.05 0.05 0.10
perform SMA
J. Barnes
0.10 0.05 0.15
C. Sotin
0.05 0.05 0.10
P. Hayne
0.25 1.00 1.25
T. McCord
0.20 0.20 0.40
Task 5
A. Hayes
0.05 0.05 0.10
Compare dune and inter-dune spectra with candidate
C. Sotin
0.20 0.20 0.40
materials, produce maps
O. Aharonson
0.05 0.05 0.10
J. Barnes
0.05 0.20 0.25
P. Hayne
2.50 2.50 5.00
J-P. Combe
0.55 1.00 1.55
TOTAL (those requesting funding only)
A. Hayes†
0.40 0.30 0.70
T. McCord
0.25 0.25 0.50
*Note: Hours listed for Collaborators (gray) are funded by other sources. Dr. Aharonson and Dr. Sotin are
funded by the Cassini science investigation, and Dr. Lucas is funded at the University of Paris. Dr. Barnes is
funded by the University of Idaho for 9 months per year, with 60% time devoted to scholarly activity such as
the proposed work.
†
Much of the effort allocated to Dr. Hayes will be performed by an undergraduate student.
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Composition of Titan’s Dunes
APPENDIX: PARTICIPATING SCIENTIST REQUEST
Abstract:
The proposed research will benefit through PI Paul Hayne serving as
Cassini Participating Scientist by: 1) enhancing the geographic coverage of the
atmosphere-corrected VIMS reflectance observations of Titan’s surface; 2) affording
closer collaboration with key VIMS science team members experienced in the study of
Titan’s surface composition; 3) improving the atmospheric correction by expanding the
number of available observations and viewing geometries. In addition, Dr. Hayne brings
expertise and capabilities in several areas complementary to the present VIMS science
team, including atmospheric radiative transfer and albedo modeling of granular
mixtures.
A.1 Objectives and Expected Contributions
Study of Titan’s surface composition using VIMS hinges on the accurate
interpretation of near-infrared reflectance spectra, which are known to be
contaminated by scattering and absorption in the atmosphere. The VIMS science team
has explored several techniques for accounting for these atmospheric effects, but no
standard correction has yet emerged. In the attached CDAPS proposal, we described a
method leading to a simple, yet accurate atmospheric correction to the VIMS
reflectance spectra of Titan’s surface. In this appendix we describe how this research
will benefit from Science PI Paul Hayne serving as a Cassini Participating Scientist. This
role will allow greater interaction with the Cassini science team and enable access to
critical datasets needed in order to maximize the usefulness of the proposed
investigation. Dr. Hayne’s extensive experience in analyzing VIMS Titan reflectance and
occultation data, as well as expertise in radiative transfer theory, will complement the
existing strengths of the VIMS science team and further the goals of the Cassini Solstice
Mission (CSM).
A.1.1 Science background and objectives
In the attached proposal, we provided the science justification for the proposed
investigation; here we highlight some of the outstanding issues motivating participation
in the PS program. Geologic units on Titan’s surface have been mapped in some detail
using VIMS and other Cassini instruments (notably RADAR and ISS), yet their surface
composition remains ambiguous. Ground truth measurements from the Huygens GCMS
revealed an assortment of volatiles, including hydrocarbons likely precipitated from the
atmosphere (Niemann et al. 2010). Water ice – likely the bulk crustal component – was
evidently observed by the descent imager/spectral radiometer (DISR) in the floodplain
where Huygens touched down (Keller et al. 2008). Despite this observation, and
evidence from ground-based telescopes (Griffith et al. 2003), no large scale exposures of
pure water ice have been definitively identified so far using VIMS, although water ice
mixtures are possible (McCord et al. 2007). Soderblom et al. (2007) noted discrepancies
in the boundaries of geologic units mapped using VIMS and RADAR, suggesting the
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Composition of Titan’s Dunes
presence of a thin mantling unit of atmosphere-derived hydrocarbons, which is
somewhat transparent at radar wavelengths (of order centimeters). However, this
model has yet to be rigorously tested with atmosphere-corrected spectra.
The vast equatorial dune fields are spectrally more neutral in the near-IR than other
surface units, consistent with the hypothesis that the grains are composed of a tholinlike substance formed through photochemical reactions in the atmosphere and
precipitated to the surface (Barnes et al. 2008). This interpretation is broadly consistent
with RADAR scattering cross sections near those of porous solid hydrocarbons, but the
measurements are also consistent with solid CO2 (Zebker et al. 2008). Benzene, simple
alkanes and nitriles have been reported recently by Clark et al. (2010), though the low
signal-to-noise ratio of VIMS observations in the 5-m window makes mapping their
distribution on Titan’s surface challenging. Especially interesting is the identification of
liquid ethane in one of Titan’s south polar
lakes (Ontario Lacus; Brown et al. 2008), an
observation that might be repeated for the
north polar lakes as the sun illuminates them
during the CSM. Some fluvial features (e.g.
channels and floodplains) are spatially
resolved at the sub-kilometer scale by VIMS
(Jaumann et al. 2008), such that accurate
reflectance measurements could provide
insight into Titan’s unique “methanological”
cycle. We will be especially interested in
identifying any compositional changes
resulting from active weather systems (Turtle Figure A1. False-color (R=5.0 m, G=2.0m,
et al. 2011). Finally, putative cryovolcanic B=1.6m) VIMS images of (A) Tui Regio, and (B)
Hotei Regio (bright feature at limb), and (C) 4.92features (notably Hotei Regio) must be tested m band depth (left panel) and 2.8/2.7-m
for compositional characteristics consistent reflectance ratio (right panel) for Tui Regio.
with an endogenic origin, which has so far not
been demonstrated.
As a Participating Scientist, Dr. Hayne will address these ambiguities in the
present understanding of Titan’s surface composition as an expression of the underlying
geology, by working with the VIMS team to develop and apply a simple and accurate
method of atmospheric correction for the Titan reflectance measurements. Selection
for this program will improve the outcome of the proposed investigation in the
following ways: 1) Geographic coverage (particularly in longitude) of the corrected Titan
reflectance measurements will be greatly expanded through the use of more recent
proprietary data; 2) Analysis of occultation data will be more rapid and potentially more
accurate, owing to the unique knowledge of these sequences by the VIMS team (e.g. Dr.
Christophe Sotin, a collaborator on this proposal); 3) Interpretation and mapping of
compositional units on Titan’s surface will greatly benefit from the collective experience
of the VIMS science team in remote reflectance spectroscopy and icy satellite geology.
The expanded geographic coverage will also allow improvements in the atmospheric
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Composition of Titan’s Dunes
correction derived from on-planet reflectance measurements (Section 2.3.2), and aid in
estimating errors associated with temporal variations in atmospheric properties.
A.1.2 Capabilities and Qualifications
As a Participating Scientist, Dr. Hayne will bring complementary capabilities to
the science team, in addition to a wealth of experience analyzing VIMS observations of
Titan. These capabilities include: 1) An atmospheric radiative transfer model developed
for the calculation of infrared scattering and absorption by aerosols, and 2) a surface
reflectance model allowing mixtures of two or more constituents. Each of these is
described below.
Experience with VIMS data
The team of investigators on this proposal has been studying Titan with VIMS for
over five years, and has developed specialized software and other tools specifically for
analyzing this dataset. Dr. Hayne has led several focused efforts, including a substantial
portion of the work leading to the McCord et al. (2007) paper, which delineated the
compositional endmembers of Titan’s surface and mapped their distribution. He
developed a set of IDL routines for finding and measuring narrow absorption features
within the methane windows, which led to the discovery that the (so far unidentified)
4.92-m absorption feature is strongly correlated with the anomalous bright features
Tui and Hotei Regio, which have been suggested to be cryovolcanic features (Figure A1).
Without atmospheric correction, the VIMS reflectance data can only be used to infer
relative compositional differences (i.e. absolute reflectance is poorly constrained, but
ratios are meaningful). In this way, we deduced that if water ice is present on the
surface of Titan, these anomalous geologic features must be depleted in H 2O relative to
the average Titan terrain, perhaps placing constraints on the composition of the
putative cryolava (Hayne et al. 2008). In fact, the ammonia hydrate cryolava preferred
by most models for eruptive volcanism on icy satellites (Kargel 1994) is not consistent
with the compositional differences we inferred from the VIMS data, suggesting further
work is needed to confirm or disprove cryovolcanism as the formation mechanism for
Tui and Hotei Regio.
So far, only one of the Titan solar occultations has been analyzed in detail, which
was used to infer atmospheric properties (Bellucci et al. 2009). Clark et al. (2010) also
used one of the occultations to derive a first-order correction to the 2.8/2.7-m ratio.
Dr. Hayne has extensive experience with these observations, and has already made
significant progress in calculating atmospheric transmission spectra for each of the high
quality solar occultations (Hayne and McCord 2009). This is a unique capability that he
will bring to the science team, while at the same time learning from those who originally
designed the observation sequences. He also brings a demonstrated track record
collaborating with the VIMS science team, for example contributing to the paper
describing the VIMS Titan dataset (Barnes et al. 2009).
Atmospheric radiative transfer
While a graduate student at UCLA, Dr. Hayne developed a radiative transfer
model for the calculation of intensities in the cloudy polar atmosphere of Mars (Hayne
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Composition of Titan’s Dunes
2010; Hayne et al, 2012). This model, based on a two-stream -Eddington
approximation for multiple scattering in an inhomogeneous atmosphere, is extremely
efficient and has been shown to be accurate under a range of realistic planetary
conditions within ~1% in radiance in the mid-infrared. The model was designed using a
modular approach, so that the source function can be swapped in and out depending on
the application; for instance, solar versus thermal radiation. The internal radiation field
is calculated assuming a plane parallel atmosphere, but spherical geometry is employed
in integrating the formal solution along an arbitrary path, such that any viewing
geometry is allowed with consistent accuracy. This model has direct applicability to
calculating intensities including scattering by Titan’s aerosols in the near-IR wavelengths
covered by VIMS. We have begun preliminary discussions with VIMS associate Dr. Jason
Barnes (U. Idaho) and various VIMS team members about incorporating this model in
simulating atmospheric scattering, and correcting surface reflectance data under a
variety of illumination and viewing conditions. Involvement as a Cassini PS would allow
closer collaboration and development of this model in order to improve Titan surface
science.
Granular surface reflectance model
We also have extensive experience in simulating the reflectivities of granular
mixtures, based on the snow albedo model of Wiscombe and Warren (1980), and using
scattering parameters calculated from Mie theory (e.g. Hansen and Travis 1974). Given
optical constants of candidate materials on Titan’s surface, we calculate theoretical
reflectance spectra of the pure substances and mixtures, which can then be compared
to VIMS observations after atmospheric correction. For instance, mixtures of water ice
and solid hydrocarbons might match the reflectance spectra of Titan’s equatorial dunes
(Barnes et al. 2008) – a hypothesis we can readily test with this model and the
atmosphere-corrected VIMS data (cf. Hayne 2010).
A.2 Relevance to Cassini Science Goals
The proposed investigation will address the surface composition of Titan, the
distribution of geologic units, as well as their origin and subsequent modification.
Interpreting any surface changes occurring during the CSM will rely on accurate
compositional information. For instance, changes in methane concentration in the very
near-surface pore space (cf. Niemann et al. 2005) due to seasonal transport or sudden
rainstorms (Turtle et al. 2011) might have a subtle, yet measurable effect on surface
reflectance. Quantifying these changes will require accurate atmospheric correction, as
proposed here. More specifically, the proposed investigation, and Dr. Hayne’s
involvement as a Cassini PS will address the “Cassini Solstice Mission Science Objectives:
Prioritized Summary” goal TN1a: “Determine the types, composition, distribution, and
ages, of surface units and materials, most notably lakes (i.e. filled vs. dry & depth; liquid
vs. solid & composition; polar vs. other latitudes & lake basin origin).”
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A.3 Collaborations with the Cassini Science Team
The primary collaboration will be with the VIMS team, though other datasets,
notably RADAR and ISS may prove to be complementary. For example, dielectric
properties inferred from RADAR can be compared with those from VIMS in order to
place better constraints on surface composition and subsurface structure (e.g. Tosi et al.
2010). After deriving and mapping atmosphere-corrected surface reflectance, Dr.
Hayne will make these maps available first to the Cassini science team for interpretation
and further refinement. Several investigators on the VIMS science team, in addition to
Dr. McCord, have expertise on Titan’s surface composition, notably Dr. Lawrence
Soderblom, Dr. Roger Clark, and Dr. Christophe Sotin. These will be the primary
collaborators with whom Dr. Hayne will work as a Cassini PS, and he has already
collaborated to some degree with each of them on related topics. Determining Titan’s
surface composition is an immensely challenging problem, involving a wide range of
disciplines and observation techniques; expanding the cohort of investigators (especially
to those beginning their careers) will advance this endeavor greatly.
A.4 Compliance with Cassini Rules
As a member of the Cassini science team, Dr. Hayne will comply with all aspects
of the “Rules of the Road Science Policy Document”, as well as any team-specific
guidelines.
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References
Adams, J. B. and A.R. Gillespie (2006), Remote Sensing of Landscapes with Spectral
Images: A Physical Modeling Approach. Cambridge University Press. 362pp.
Baines, K.H., Brown, R. H., Cruikshank, D.P., Clark, R.N., Nelson, R.M., Matson, D.L.,
Buratti, B.J., Carusi, A., Coradini, A., Bibring, J.P., Sotin, C., Langevin, Y., Jaumann, R.,
Formisano, V., Combes, M., Drossart, P., Langevin, Y., Sicardy, B., 1992.
VIMS/Cassini, at Titan: scientific objectives and observational scenarios. In:
Symposium on Titan, Conference Proceedings, ESA SP 338, pp. 215– 219.
Barnes, J. W. et al. (2008) "Spectroscopy, morphometry, and photoclinometry of Titan's
dunefields from Cassini/VIMS" Icarus 195, 400-414.
Barnes, J. W. et al. (2009) "VIMS spectral mapping observations of Titan during the
Cassini prime mission" Planetary and Space Science, Volume 57, Issue 14-15, p.
1950-1962.
Bellucci, A. et al. (2009), Titan solar occultation observed by Cassini/VIMS: Gas
absorption and constraints on aerosol composition, Icarus 201, 198-216.
doi:10.1016/j.icarus.2008.12.024Boardman, J. W., Kruse, F. A., and Green, R. O.,
1995, Mapping target signatures via partial unmixing of AVIRIS data: in Summaries,
Fifth JPL Airborne Earth Science Workshop, JPL Publication 95-1, v. 1, pp. 23-26.
Brown, R. H., Baines, K.H., Bellucci, G., Bibring, J.P., Buratti, B.J., Bussoletti, E.,
Capaccioni, F., Cerroni, P., Clark, R.N., Coradini, A.,Cruikshank, D.P., Drossart, P.,
Formisano, V., Jaumann, R., Langevin, Y., Matson, D.L., McCord, T.B., Mennella,
V.,Miller, E.,Nelson, R.M., Nicholson, P.D., Sicardy, B., Sotin C., 2004. The Cassini
Visual and Infrared Mapping Spectrometer Investigation. Space Sci. Revs., 115, 111168.
Brown, R. H. et al. (2008), The identification of liquid ethane in Titan's Ontario Lacus,
Nature 454, 607- 610. doi:10.1038/nature07100 Clark, R. N., J. M. Curchin, R. H
Brown, J. H. Waite, D. P. Cruikshank, R. Jaumann, J. Lunine, T. M Hoefen, T. E.
Cravens, R. V. Yelle, V. Vuitton, K. H. Baines, B. J. Buratti, J. Barnes, T. B. McCord, P.
D. Nicholson, 2006a. Detection of widespread aromatic and aliphatic hydrocarbon
deposits on Titan’s surface observed by VIMS and excess benzene observed in
Titan’s thermosphere observed by INMS, Bull. Am Ast. Soc., 38, 3, 574. Abst 48-04.
Clark, R. N., J. M. Curchin, R. H Brown, D. P. Cruikshank, R. Jaumann, J. Lunine, T. M
Hoefen, K. H. Baines, B. J. Buratti, J. Barnes, P. D. Nicholson, 2006b. Detection of
widespread aromatic and aliphatic hydrocarbon deposits on Titan’s surface observed
by VIMS, Am. Geophys U. annual fall meeting proceedings, p. 21, Abst P11A-03.
Clark, R. N. et al. (2010) "Detection and mapping of hydrocarbon deposits on Titan"
Journal of Geophysical Research 115, E10005
Combe J.-Ph., 2005, Etudes des surfaces planétaires par télédétection visible infrarouge
hyperspectrale, PhD thesis, Université de Nantes, 300p
20
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Combe, J.-Ph.; Le Mouélic, S.; Sotin, C.; Gendrin, A.; Le Deit, L.; Mustard, J. F.; Bibring, J.P.; Gondet, B.; Langevin, Y.; Omega Science TeamAnalysis of OMEGA/Mars Express
Hyperspectral Data Using a Linear Unmixing Model: Methods and Preliminary
Results, abstract no. 2115, 37th LPSC, 13-17 March 2006.
Combe J.-Ph., Le Mouélic S., Sotin C., Gendrin A., Mustard J. F., Le Deit L., Launeau P.,
Bibring J.-P., Gondet B., Langevin Y., Pinet P., and the OMEGA Science team, Analysis
of OMEGA / Mars Express data hyperspectral data using a Multiple-Endmember
Linear Spectral Unmixing Model (MELSUM): Methodology and first results, Planetary
and Space Science, 2008, vol 56/7, 951-975, doi: 10.1016/j.pss.2007.12.007.
Coustenis, A., Lellouch, E., Maillard, J.P., McKay, C.P., 1995. Titan’s surface: composition
and variability from the near-infrared albedo. Icarus 118, 87–104.
Coustenis, A., A. Negrão, A. Salama, B. Schulz, E. Lellouch, P. Rannou, P. Drossart, T.
Encrenaz, B. Schmitt, V. Boudon and A. Nikitin, 2006, Titan's 3-micron spectral region
from ISO high-resolution spectroscopy. Icarus, 180, Pages 176-185
Flasar, F.M., 1983. Oceans on Titan? Science 221, 55–57.
Flasar, F. M., et al., 2005. Titan’s atmospheric temperatures, winds, and composition.
Science 308, 975- 978.
Fulchignoni, M., Ferri, F, Colombatti, G., Zarnecki, J. C., Harri, A-M., Girard, R.,
Schwingenschuh, K., Hamelin, M. Lopez Moreno, J.J., Svedhem, H., the HASI team,
2005. First results on the characteristics of Titan’s atmosphere by the Huygens
Atmospheric Structure instrument 9HASI) measurements. European Geophysical
Union Abstract -A-05792; US9/PS1.5-1MO1O-006.
Griffith, C.A., Owen, T., Wagener, R., 1991. Titan’s surface and troposphere, investigated
with groundbased, near-infrared observations. Icarus 93, 362–378.
Griffith, C.A., 1993. Evidence for surface heterogeneity on Titan. Nature 364, 511–514.
Griffith, C. A., Owen, T. , Geballe, T. R. , Rayner, J., Rannou, P., 2003. Evidence for the
exposure of water ice on Titan’s surface. Science 300, 628-630.
Hansen, G. B., T. B. McCord, C. A. Hibbitts, and L. W. Kamp, 2006. Progress on the
recalibration and rectification of Galileo NIMS spectral images of the Galilean
satellites (abstract), Eos Trans. AGU, 87(36), Jt. Assem. Suppl., Abstract P41B-05.
Hapke, B., Theory of Reflectance and Emittance Spectroscopy, Cambridge University
Press, 455 pp., 1993.
Hayne, P. et al. (2008), Titan: Observational Constraints on Cryovolcanism. Lunar and
Planetary Science XXXIX, p. 2010.
Hayne, P. O. et al. (2009), Titan's Near Infrared Atmospheric Transmission and Surface
Reflectance from the Cassini Visual and Infrared Mapping Spectrometer, Lunar and
Planetary Science XL.
Hayne, P. O., 2010. Snow Clouds on Mars and Ice on the Moon: Infrared Observations
and Models, PhD thesis, University of California, Los Angeles, 227 pp.
Hayne, P. O., D. A. Paige, J. T. Schofield, D. M. Kass, A. Kleinbohl, N. G. Heavens, and D. J.
McCleese (2012), Carbon dioxide snow clouds on Mars: South polar winter
observations by the Mars Climate Sounder, J. Geophys. Res., 117, E08014,
doi:10.1029/2011JE004040.
Jet Propulsion Laboratory
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Composition of Titan’s Dunes
Hayne, P. O., T. B. McCord, and C. Sotin (2013), Titan’s surface composition: correction
for atmospheric effects derived from near-infrared solar occultation measurements
by Cassini-VIMS, Icarus, in press.
Jaumann, R.; Stephan, K.; Brown, R. H.; Buratti, B. J.; Clark, R. N.; McCord, T. B.; Coradini,
A.; Capaccioni, F.; Filacchione, G.; Cerroni, P.; Baines, K. H.; Bellucci, G.; Bibring, J.-P.;
Combes, M.; Cruikshank, D. P.; Drossart, P.; Formisano, V.; Langevin, Y.; Matson, D.
L.; Nelson, R. M.; Nicholson, P. D.; Sicardy, B.; Sotin, C.; Soderbloom, L. A.; Griffith,
C.; Matz, K.-D.; Roatsch, Th.; Scholten, F.; Porco, C. C., 2006, High-resolution
CASSINI-VIMS mosaics of Titan and the icy Saturnian satellites, Planetary and Space
Science, 4, Issue 12, 1146-1155.
Kargel, J. S. (1994) "Cryovolcanism on the icy satellites" Earth, Moon, and Planets 67,
101-113.
Le Gall, A., Janssen, M. a., Wye, L. C., Hayes, A. G., Radebaugh, J., Savage, C., Zebker, H.,
et al. (2011). Cassini SAR, radiometry, scatterometry and altimetry observations of
Titan’s
dune
fields.
Icarus,
213(2),
608-624.
Elsevier
Inc.
doi:10.1016/j.icarus.2011.03.026
Le Gall, A., Hayes, A. G., Ewing, R. C., Janssen, M. A., Radibaugh, J., Savage, C., Encrenaz,
P., et al. (2012). Latitudinal and altitudinal controls of Titan’s dune fid morphometry.
Icarus, 217, 231-242. doi:10.1016/j.icarus.2011.10.024.
Liou, K. N. (2002), Introduction to Atmospheric Radiation, Academic Press, San Diego,
579 pp.
Lorenz, R. D. 1996. Pillow lava on Titan: expectations and con- straints on cryovolcanic
processes. Planet. Spac. Sci., 44, 1021–1028. doi: 10.1016/0032-0633(95)00139-5.
Lorenz, R D, Wall, S., Radebaugh, J., Boubin, G., Reffet, E., Janssen, M., Stofan, E., et al.
(2006). The sand seas of Titan: Cassini RADAR observations of longitudinal dunes.
Science (New York, N.Y.), 312(5774), 724-7. doi:10.1126/science.1123257
Lorenz, R. D., & Radebaugh, J. (2009). Global pattern of Titan’s dunes: Radar survey from
the Cassini prime mission. Geophysical Research Letters, 36(3), 9-12.
doi:10.1029/2008GL036850.
Lorenz, R. D., Claudin, P., Andreotti, B., Radebaugh, J., & Tokano, T. (2010). A 3km
atmospheric boundary layer on Titan indicated by dune spacing and Huygens data.
Icarus, 205(2), 719–721. doi:10.1016/j.icarus.2009.08.002.
Lucas, A., O. Aharonson, A. G. Hayes, C. A. Deledalle, and R. L. Kirk (2011), Enhanced
processing and analysis of Cassini SAR images of Titan, AGU Fall Meeting, abstract
no. P33E-1795.
Lucas, A., O. Aharonson, A. G. Hayes, C. Deledalle, L. Wye, R. Kirk, E. Howington-Kraus,
and the Cassini RADAR Science Team (2012), Clues to Titan hydrology from
enhanced SAR image processing, 43rd Lunar and Planet. Sci. Conf., The Woodlands,
TX, abstract no. 1659.
McCord, T. B., A. Coradini, C. A. Hibbitts, F. Capaccioni, G. b. Hansen, G. Filacchione, R.
N. Clark, P. Cerroni, R. H. Brown, K. H. Baines, G. Bellucci, J.-P. Bibring, B. J. Buratti, E.
Bussoletti, M. Combes, D. P. Cruikshank, P. Crossart, V. Formisano, R. Jaumann, Y.
Langevin, D. L. Matson, R. M. Nelson, P. D. Nichoson, B. Sicardy, and C. Sotin, 2004.
22
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Cassini VIMS Global observations of the Galilean Satellites including the VIMS
calibration procedure. Icarus, 172, 104-126.
McCord, T. B., Hansen, G. B., Buratti, B. J., Clark, R. N., Cruikshank, D. P., D’Aversa, E.,
Griffith, C. A., Baines, E. K. H., Brown, R. H., Dalle Ore, C. M., Filacchione, G.,
Formisano, V., Hibbits, C. A., Jaumann, R., Lunine, J. I., Nelson, R. M., Sotin, C., and
the Cassini VIMS Team, 2006a. Composition of Titan’s Surface from Cassini VIMS.
Planetary and Space Science 54, 1524-1539.
McCord, T. B., P. Hayne, J-P. Combe, G. B. Hansen, K. H. Baines, R. H. Brown, B. J. Buratti,
R. N. Clark, P. Nicholson, 2006b. Titan surface composition analysis using VIMS, Bull.
Am Ast. Soc., 38, 3, 574-575. Abst 48-05.
McCord T. B., Hayne P. G., Combe J.-Ph., Hansen G. B., Barnes J. W., Rodriguez S., Le
Mouélic S., Baines K. H., Buratti B. J., Sotin C., Nicholson Ph., Jaumann R., Nelson R.,
and the Cassini VIMS Team, Titan’s Surface: Search for spectral diversity and
composition using the Cassini VIMS investigation, Icarus, 2007a, Volume 194, 212242, doi: 10.1016/j.icarus.2007.08.039.
McCord, T. B., P. Hayne, J-P. Combe, G. B. Hansen, J. W. Barnes, B. Buratti, K. H. Haines,
R. H. Brown, and P. Nicholson, 2007b, Titan: Surface composition from Cassini VIMS,
European Geosciences Union General Assembly, Geophys. Res. Abst. ISSN: 10297006.
McCord, T. B., P. O. Hayne, J.-P. Combe, and G. B. Hansen (2008), Titan: The case for
CO2 on the surface, paper presented at EGU 2008 General Assembly, Geophysical
Research Abstracts, Vienna, Austria, April 13-18, 2008, EGU2008-A-05368.
McCord, T. B., and P. O. Hayne (2009), Nature of the 2.8-um window in Titan's
atmosphere and effects on detection of surface reflectance characteristics, paper
presented at European Planetary Science Congress, Potsdam, Germany, September
14-18, 2009.
Le Mouelic, S. et al. (2010a), Empirical Approaches To Reduce The Atmospheric
Component In VIMS Surface Images Of Titan, American Geophysical Union, Fall
Meeting 2010, abstract #P31C-1546
Le Mouelic, S. et al. (2010), Imaging of Titan in the infrared with Cassini/VIMS : Toward
homogeneous surface maps, EGU General Assembly 2010, held 2-7 May, 2010 in
Vienna, Austria, p.8483
Lodders, K. and Fegley, B. (1998), The planetary scientist's companion. New York :
Oxford University Press, 1998. QB601 .L84 1998Lunine, J.I., Stevenson, D.J., Yung,
Y.L., 1983. Ethane ocean on Titan. Science 222, 1229.
Neish, C. D., R. D. Lorenz, R. L. Kirk, and L. C. Wye (2010), Radarclinometry of the sand
seas of Africa’s Namibia and Saturn’s moon Titan, Icarus, 208, 385-394, doi:
10.1016/j.icarus.2010.01.023.
Niemann, H. B., S. K. Atreya, J. E. Demick, D. Gautier, J. A. Haberman, D. N. Harpold, W.
T. Kasprzak, J. I. Lunine, T. C. Owen, R. Raulin, 2010, Composition of Titan’s lower
atmosphere and simple surface volatiles as measured by the Cassini-Huygens probe
gas chromatograph mass spectrometer experiment, J. Geophys. Res. 115, DOI:
10.1029/2010JE003659.
Jet Propulsion Laboratory
Paul O. Hayne
23
Composition of Titan’s Dunes
Radebaugh, J., Lorenz, R. D., Lunine, J. I., Wall, S. D., Boubin, G., Reffet, E., Kirk, R. L., et
al. (2008). Dunes on Titan observed by Cassini Radar. Icarus, 194(2), 690-703.
doi:10.1016/j.icarus.2007.10.015
Radebaugh, J., Lorenz, R., Farr, T., Paillou, P., Savage, C., & Spencer, C. (2010). Linear
dunes on Titan and earth: Initial remote sensing comparisons. Geomorphology,
121(1-2), 122-132. doi:10.1016/j.geomorph.2009.02.022
Rubin, D. M., & Hesp, P. a. (2009). Multiple origins of linear dunes on Earth and Titan.
Nature Geoscience, 2(9), 653-658. Nature Publishing Group. doi:10.1038/ngeo610
Savage, C. J., & Radebaugh, J. (2011). Parameter analysis of Titan’s dunes reveals surface
evolution history. Lunar and Planetary Science Conference XLII, (2261). Houston.
Stofan, E. R.; Elachi, C.; Lunine, J. I.; Lorenz, R. D.; Stiles, B.; Mitchell, K. L.; Ostro, S.;
Soderblom, L.; Wood, C.; Zebker, H.; Wall, S.; Janssen, M.; Kirk, R.; Lopes, R.;
Paganelli, F.; Radebaugh, J.; Wye, L.; Anderson, Y.; Allison, M.; Boehmer, R.;
Callahan, P.; Encrenaz, P.; Flamini, E.; Francescetti, G.; Gim, Y.; Hamilton, G.;
Hensley, S.; Johnson, W. T. K.; Kelleher, K.; Muhleman, D.; Paillou, P.; Picardi, G.;
Posa, F.; Roth, L.; Seu, R.; Shaffer, S.; Vetrella, S.; West, R., 2007, The lakes of Titan,
Nature, 445, Issue 7123, 61-64, 10.1038/nature05438
Tobie, G., Grasset, O., Lunine, J., Mocquet, A., Sotin, C., 2005. Titan’s internal structure
inferred from a coupled thermal-orbital model. Icarus 175, 496–502.
Tomasko, M.G., Archinal, B., Becker, T., Be ́ zard, B., Bushroe, M., Combes, M., Cook, D.,
Coustenis, A., de Bergh, C., Dafoe, L.E., Doose, L., Doute , S., Eibl, A., Engel, S., Gliem,
F., Grieger, B., Holso, K., Howington-Kraus, E., Karkoschka, E., Keller, H.U., Kirk, R.,
Kramm, R., Kuppers, M., Lanagan, P., Lellouch, E., Lemmon, M., Lunine, J.,
McFarlane, E., Moores, J., Prout, G.M., Rizk, B., Rosiek, M., Rueffer, P., Schro d
̈ er,
S.E., Schmitt, B., See, C., Smith, P., Soderblom, L., Thomas, N., West, R., 2005., Rain,
winds and haze during the Huygens probe’s descent to Titan’s surface", Nature 438
(7069), 765–778
Turtle, E. P. et al. (2011) "Rapid and Extensive Surface Changes Near Titan's Equator:
Evidence of April Showers" Science 331, 1414.
Yung, Y. L.; Allen, M.; Pinto, J. P., 1984, Photochemistry of the atmosphere of Titan Comparison between model and observations, Astrophysical Journal Supplement
Series, vol. 55, 465-506, 10.1086/190963
24
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Biographical Sketches
Paul Ottinger Hayne
Geophysics and Planetary Geosciences Section
Jet Propulsion Laboratory, California Institute of Technology
MS 183-301, Pasadena, CA 91109
Paul.O.Hayne@jpl.nasa.gov
T: 818.354.0137
F: 818.393.4445
Research emphases: Planetary geophysics and remote sensing; thermal environments and polar volatiles
on the Moon and other airless bodies; Mars polar energy balance, seasonal cycles and climate; icy satellite
surface composition, geological evolution, and habitability
EDUCATION
2010
2005
2003
PhD
MS
BS
Geophysics and Space Physics
Geophysics
Geophysics
UCLA
Stanford University
Stanford University
NASA Jet Propulsion Laboratory
California Institute of Technology
University of California, Los Angeles
Staff Scientist
Postdoctoral Scholar
Graduate Student Researcher
EMPLOYMENT
2012–present
2010–2012
2006–2010
MISSION EXPERIENCE
NASA Lunar Reconnaissance Orbiter / Diviner Lunar Radiometer – Co-Investigator (2011 – present)
Designed remote infrared observations of the LCROSS impact and modeled volatile behavior;
characterized lunar regolith structure using Diviner observations of the Moon’s cooling during
eclipse
NASA Mars Reconnaissance Orbiter / Mars Climate Sounder – Science Team member (2007 – present)
Led polar science investigation, including first infrared identification of polar carbon dioxide snow
clouds and their role in regulating the present-day climate of Mars
NASA/ESA Cassini-Huygens / VIMS – science team collaborator (2006 – present)
NASA Galileo / NIMS – science team collaborator/data analysis (2009)
ESA Mars Express / HRSC – data analysis (2006)
SELECTED PUBLICATIONS
Hayne, P. O., and O. Aharonson (2013), Topographically shadowed ice on Ceres, in prep. for JGR.
Hayne, P. O., D. A. Paige, N. G. Heavens (2013), The role of snowfall in forming the seasonal ice caps of
Mars : Models and constraints from the Mars Climate Sounder, submitted to Icarus.
Hayne, P. O., T. B. McCord, and C. Sotin (2013), Titan’s surface composition : Correction for atmospheric
effects derived from near-infrared solar occultation measurements by Cassini VIMS, submitted to
Icarus.
Barnes, J. W., B. J. Buratti, E. P. Turtle, J. Bow, P. A. Dalba, J. Perry, R. H. Brown, S. Rodriguez, S. Le
Mouelic, K. H. Baines, C. Sotin, R. D. Lorenz, M. J. Malaska, T. B. McCord, R. N. Clark, R. Jaumann, P.
Jet Propulsion Laboratory
Paul O. Hayne
25
Composition of Titan’s Dunes
O. Hayne, et al. (2013), Precipitation-Induced Surface Brightenings Seen on Titan by Cassini VIMS
and ISS, Planetary Science, 2, p. 1.
Hayne, P. O., D. A. Paige, J. T. Schofield, D. M. Kass, A. Kleinböhl, N. G. Heavens, and D. J. McCleese
(2012), Carbon dioxide snow clouds on Mars: South polar winter observations by the Mars Climate
Sounder, J. Geophys. Res., 117, E08014, doi:10.1029/2011JE004040.
Vasavada, A. R., J. L. Bandfield, B. T. Greenhagen, P. O. Hayne, et al. (2012), Lunar Equatorial Surface
Temperatures and Regolith Properties from the Diviner Lunar Radiometer Experiment, Journal of
Geophysical Research 117, E00H18.
Hayne, P. O., B. T. Greenhagen, M. C. Foote, M. A. Siegler, A. R. Vasavada, and D. A. Paige (2010),
Diviner Lunar Radiometer Observations of the LCROSS Impact, Science, 330, 477.
Paige, D. A., M. A. Siegler, J. A. Zhang, P. O. Hayne, et al. (2010), Diviner Observations of Cold Traps in
the Lunar South Polar Region: Spatial Distribution and Temperature, Science 330, 479.
Greenhagen, B. T., P. G. Lucey, M. B. Wyatt, T. D. Glotch, C. C. Allen, J. A. Arnold, J. L. Bandfield, N. E.
Bowles, K. L. Hanna, P. O. Hayne, E. Song, I. R. Thomas, and D. A. Paige (2010) Global Silicate
Mineralogy of the Moon from the Diviner Lunar Radiometer, Science 329, 1507.
McCord, T. B., …, and P. O. Hayne (2010), Hydrated minerals on Europa's surface: An improved look
from the Galileo NIMS investigation, Icarus 209, 639-650.
Barnes, J. W., …, P. O. Hayne, et al. (2009), VIMS Spectral Mapping Observations of Titan during the
Cassini Prime Mission, Planetary and Space Sciences, vol. 57, issue 14-15, pp. 1950-1962.
McCord, T. B., P. Hayne, et al. (2008), Titan's surface: Search for spectral diversity and composition using
the Cassini VIMS investigation, Icarus, vol. 194, pp. 212-242.
BOOK CHAPTER:
Aharonson, O., A. Hayes, P. O. Hayne, R. Lopes, A. Lucas, J. T. Perron, (2012), Titan's Surface Geology,
in: C. G. Mueller-Wodarg, T. Cravens and E. Lellouch (Ed.), Titan: Surface, Atmosphere and
Magnetosphere, Cambridge University Press, Cambridge, UK.
RECENT CONFERENCE ABSTRACTS AND PRESENTATIONS:
Hayne, P. O. and O. Aharonson (2012), Polar ice caps on Ceres: predictions for Dawn, Bulletin of the
American Astronomical Society, 44.
Hayne, P. O., et al. (2011), The Moon’s Extremely Insulating Near-Surface: Diviner Observations of a
Total Lunar Eclipse, American Geophysical Union Fall Meeting 2011.
Hayne, P. O., and D. A. Paige (2009), Clouds in the Polar Night of Mars: Modeling and Observations with
the Mars Climate Sounder, paper presented at LPSC XL, p. 1849.
Hayne, P. O., et al. (2009), Titan's Near Infrared Atmospheric Transmission and Surface Reflectance from
the Cassini Visual and Infrared Mapping Spectrometer, paper presented at LPSC XL, p. 1863.
HONORS








26
Keck Institute of Space Studies, Lead: “New Approaches to Lunar Ice Detection and Mapping”
(2013)
NASA Group Achievement Awards: Mars Climate Sounder Science Team (2010, 2011), Diviner
Lunar Radiometer Science Team (2011) and Operations Team (2011)
Best Student Paper, NASA Lunar Science Forum (2010)
Simon Latimer Award for Service, Dept. of Earth & Space Sciences, UCLA (2008)
NASA Astrobiology Institute Scholarship – Astrobiology Summer School, Spain (2008)
Institute of Geophysics and Planetary Physics (IGPP) Graduate Fellowship (2006 – 2008)
Chancellor’s Prize, UCLA – Awarded to top incoming graduate students (2006)
Graduate Research and Teaching Assistantship, Stanford University (2003 – 2005)
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes

Physics Department Undergraduate Fellowship, Stanford University – Summer support (2001)
Jet Propulsion Laboratory
Paul O. Hayne
27
Composition of Titan’s Dunes
Current Address
412 Space Science Bldg.
Ithaca, NY 14853-6801
Alexander Gerard Hayes
http://www.alexanderghayes.com
hayes@astro.cornell.edu
(607) 793-7531
EDUCATION
Ph.D. Planetary Science
M.Eng. Applied & Engineering Physics
B.A.
Astronomy / Physics, Summa Cum Laude
B.A.
Astrobiology, Summa Cum Laude
SELECTED AWARDS
Ronald Greeley Early Career Award (2012)
Sigma Xi Young Scholar Procter Prize (2008)
Permanent Address
219 Buttermilk Lane
Ithaca, NY 14850
California Institute of Technology
Cornell University
Cornell University
Cornell University
April 2011
Dec. 2003
May 2003
May 2003
David Delano Clark Award [Best Thesis] (2004)
NASA Group Achievement Awards (MER/Cassini)
PROFESSIONAL POSITIONS
-
Assistant Professor; Cornell University, January 2013-Present
Miller Research Fellow; University of California at Berkeley, July 2011-December 2012
Post-Doctoral Scholar / Graduate Student; Caltech, April 2011 – July 2011 / Sep. 2006 – March 2011
Consultant / Associate Staff; MIT Lincoln Laboratory, Sep. 2006 – Sep. 2007 / May 2004 – Sep. 2006
Remote Software Consultant; Arizona State University, May 2004 – Sep. 2006
MER Science Team Affiliate; Jet Propulsion Laboratory, Jan. 2004 – May 2004
SELECTED PUBLICATIONS
[-] O. Aharonson, A. G. Hayes, R. M. C. Lopes, A. Lucas, P. Hayne, T. Perron, and L. A. Soderblom .
Titan’s Surface Geology (2012), In: I. Mueller-Wodarg (Ed) Titan: Surface, Atmosphere, and
Magnetosphere. 646pp., Cambridge Planetary Science Series, Cambridge University Press.
[-] J. Grotzinger, A. G. Hayes, M. O. Lamb, S. M. McLennan. Sedimentary Processes on the Earth, Mars,
Titan, and Venus (in-press), In: M. Bullock and M. Mackwell (Eds) Comparative Climatology of
Terrestrial Planets. 600pp., Space Science Series, University of Arizona Press, Tucson.
[-] A. G. Hayes, R. D. Lorenz, M. Manga, M. A. Donelan, H. L. Tolman, W. W. Fischer, S. D. Graves,
M. P. Lamb, J. I. Lunine, P. Encrenaz, O. Aharonson, and the Cassini RADAR Team. Wind driven
capillary-gravity waves on Titan’s Lakes: Hard to Detect or Non-Existent? Icarus 2013.
[-] A. Le Gall, A. G. Hayes, and R. C. Ewing, M. A. Janssen,J. Radebaugh, C. Savage, and P. Encrenaz.
Latitudinal and altitudinal controls of Titan’s dune field morphometry. Icarus, 2012.
[-] E. P. Turtle, J. E. Perry, A. G Hayes, R. D. Lorenz, J. W. Barnes, A. S. McEwen, R. A. West, T. L.
Ray, A. D. Del Genio, J. M. Barbara, and E. L. Schaller. Extensive and Rapid Surface changes near
Titan’s equator: Evidence for April Showers? Science, 2011.
[-] A. G. Hayes, O. Aharonson, J. Lunine, H. Zebker, L. Wye, R. Lorenz, E. Turtle, P. Paillou,G. Mitri, S.
Wall, E R. Stofan, C. Elachi, and The Cassini RADAR Team. Transient Surface Liquid in Titan's
Polar Regions from Cassini. Icarus, vol. 211, January 2011
[-] A. G. Hayes, J. Grotzinger, L. Edgar, W. Watters, S. Squyres, and J. Sohl-Dickstien. Reconstruction
of Ancient Eolian Bed Forms and Paleo-Currents from Cross-Bedded Strata at Merdiani Planum,
Mars. Journal of Geophysical Research: Planets, Vol. 116, E00F21, April 2011.
[-] A. G. Hayes, A. S. Wolf, O. Aharonson, H. Zebker, R. Lorenz, P. Paillou, S. Wall, and C. Elachi.
Bathymetry and Absorptivity of Titan's Ontario Lacus. JGR: Planets, Vol. 115, E09009, Sep. 2010.
[-] O. Aharonson, A. G. Hayes, J.I. Lunine, R.D. Lorenz, M.D. Allison, and C. Elachi. An asymmetric
distribution of lakes on Titan as a possible consequence of orbital forcing. Nature Geo., Nov. 2009.
[-] A. G. Hayes, O. Aharonson, P. Callahan, C. Elachi, Y. Gim, R. Kirk, K. Lewis, R. Lopes, R. Lorenz, J.
Lunine, K. Mitchell, G. Mitri, E. Stofan, and S. Wall. Hydrocarbon lakes on Titan: Distribution and
interaction with a porous regolith. Geophysical Research Letters, 35:9204, May 2008.
28
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Jean-Philippe Combe
The Bear Fight Institute
Box 667, 22 Fiddler’s Road Winthrop WA 98862
email: jean-philippe_combe @ bearfightinstitute.com
Professional Experience
June 2006 – present
Research Scientist at the Bear Fight Institute in Winthrop, WA
Research activities:
- Mineralogy, photometry and thermal emission of the Moon with Chandrayaan-1 Moon
Mineralogy Mapper hyperspectral images, the Diviner Lunar Radiometer Experiment
and Clementine UVVIS + NIR multispectral images
- Preparation of future observations of asteroid 4-Vesta by the imaging spectrometer VIR
on the Dawn spacecraft.
- Mapping of mineralogical surface composition and geology of Mars with Mars Express
OMEGA and HRSC, and Mars Reconnaissance Orbiter CRISM spectral data
- Surface composition and atmospheric spectrophotometric properties of Titan with the
Cassini VIMS imaging spectrometer
- Identification of hydrated salts on Europa with the Galileo NIMS imaging spectrometer
- Recent development of spectral unmixing algorithms and absorption band identification.
- Surface composition and roughness of telluric planets and satellites of the solar system
February – March 2006
Visiting Postdoctoral Fellow at the Bear Fight Center in
Winthrop, WA
October 2005 – June 2006
Post-doc and graduate assistant at University of Nantes, France
October 2005
Visiting Ph.D. Student Fellow at the Space Science Institute in
Winthrop, WA
September 2001 – October 2005 Graduate assistant at University of Nantes, France
Education and academic degrees
October 2005 Graduated from the University of Nantes, France, with a Ph.D. in Planetary
Sciences – Remote Sensing; thesis advisor Pr. Christophe Sotin
Thesis title: Studies of planetary surfaces by hyperspectral visible-infrared remote
sensing (in french: Etudes des surfaces planétaires par télédétection visible
infrarouge hyperspectrale)
June 2001
Graduated from the University of Toulouse, France, with a Master in Earth and
Environmental Sciences; speciality: Dynamics of the Earth and Telluric Planets;
advisors Pr. Claude d’Uston and Dr. Serge Chevrel
Computer skills
Platforms: UNIX, Linux, PC
Packages: IDL, ENVI, Excel
Jet Propulsion Laboratory
Paul O. Hayne
29
Composition of Titan’s Dunes
Thomas B. McCord
Contacts:
Bear Fight Institute
Box 667, 22 Fiddler’s Road
Winthrop WA 98862
509 996 3933 ph; 509 996 3772 fax+
email: mccordtb@bearfightcenter.com
Ph.D.
M.S.
B.S.
FORMAL EDUCATION
Planetary Science and Astronomy (double degree), California Institute of
Technology, Pasadena, CA, 1968
Geology, California Institute of Technology, Pasadena, CA, 1966
Physics, Pennsylvania State University, State College, PA, 1964
FIELDS OF ACTIVITY
Research into Physics of surfaces of the Earth and Planets, and
Science and application of remote sensing from the ground, air and space.
Develop instrumentation and software for remote sensing research and applications,
Plan and execute air and space missions and experiments,
Process and analyze image, spectral and other databases.
Education and training of graduate students and young scientists
Advise private and public institutions.
CURRENT POSITIONS
Senior Research Scientist, Director, The Bear Fight Center (2002 – present)
Professor emeritus University of Hawaii (2002 - present)
Adjunct Professor, University of Washington (2002 – present)
Distinguished Visiting Scientists, Jet Propulsion Laboratory (2002 – present)
MAJOR PREVIOUS POSITIONS
Visitor in Planetary Sciences, California Institute of Technology (2004-2008)
Senior scientists, Space Sciences Institute (2004 – 2007).
Senior scientists and Division Director, Planetary Science Institute (2002 - 2004).
Distinguished Visiting Scientist, Inst. for Space Physics, CNR, Italy (March-May 2003; MarchApril, 2005)
Distinguished Invited Professor, University of Nantes, France (March-June 2002).
Professor Planetary Sciences (tenured), University of Hawaii (1979-2001). [Retired and elected
emeritus professor]
Chairman and Chief Scientist, SETS, Inc. (1980-1996). [Successfully sold company.]
Asst. Director, Institute for Astronomy, University of Hawaii (1976-1979) (head, observatories
development and operations and head engineering division). [Resigned to focus on research
and education.]
Professor, Earth and Planetary Sci. (tenured), Mass. Inst. of Technology (1968-1978). [Resigned
tenured position to move to University of Hawaii and Mauna Kea Observatory. Maintained
position in M.I.T. Center for Space Research until 1986.]
Post Doctoral Research Fellow, California Institute of Technology (1967-1968).
[Resigned to move to M.I.T.]
Graduate Student, California Institute of Technology (1964-1967) [Graduated]
Undergraduate Student, Pennsylvania State University (1991-1964) [Graduated]
U.S. Air Force (1958-1961) [Honorably discharged]
30
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Current and Pending Support
Principal Investigator: Paul O. Hayne
Sponsoring Agency
Title of award or project Program Name (if appropriate)
or Institution
CURRENT SUPPORT
Proposed
period of
performance
Budget
Commitment in
fractions of a full
time Work Year
Mars Climate Sounder
Extended Mission 2
Mars Reconnaissance Orbiter
NASA
Michael Kelley
(202) 358-0607
10/2012 3/2015
$30M/FY
0.48
Diviner Radiometer (JPL
Tasks)
Lunar Reconnaissance Orbiter
NASA
Robert Fogal
(202) 358-2289
10/2012 3/2015
$4M/FY
0.48
New Approaches to
Lunar Ice Detection and
Mapping
Keck Institute of Space Studies
2013 Study Program
JPL
Katherine Dumas
(818) 354-6546
3/2013 2/2014
$50k/FY
0.04
The Virtual Planet
Modeling Team
SSERVI
NASA
Yvonne Pendleton
(650) 604-1850
10/2013 10/2018
$6 Million
0.2
Applied Physics Lab
SSERVI Team
SSERVI
NASA
Yvonne Pendleton
(650) 604-1850
10/2013 10/2018
$6 Million
0.2
Georgia Tech SSERVI
Team
SSERVI
NASA
Yvonne Pendleton
(650) 604-1850
10/2013 10/2018
$6 Million
0.2
Effects of Small Scale
Hypervelocity Impact
Cratering on the Moon
Lunar Advanced Science and
Exploration Research (LASER)
NASA
Robert Fogal
(202) 358-2289
10/2013 10/2016
$100k
0.08
Thermal Modeling for
Lunar AtmosphereSurface Interactions
Lunar Atmosphere and Dust
Explorer (LADEE) Guest
Investigator Program
NASA
Sarah Noble
(202) 643-5862
8/2013 7/2015
$200k
0.2
NASA
Henry Throop
(202) 358-1364
8/2013 7/2015
$200k
0.2
PENDING SUPPORT
Composition of Titan's
Cassini Data Analysis and
Dunes: Constraints from
Participating Scientists (CDAPS)
Cassini VIMS and RADAR
NOTE: If the proposed investigation is funded, the PI will decrease his level of effort on
the Lunar Reconnaissance Orbiter and Mars Reconnaissance Orbiter science teams in
order to fully complete the tasks in this proposal. Other members of those teams are
willing and able to increase their efforts by a commensurate amount, as deemed
necessary by their respective PIs.
Jet Propulsion Laboratory
Paul O. Hayne
31
Composition of Titan’s Dunes
Co-Investigator: Alexander G. Hayes
Current Support:
X Current
Pending
Submission Planned in Near Future
Project/Proposal Title:
Seas, Lakes, Channel Networks, and Hillslopes: a coupled analysis to explore the
evolution of Titan’s Polar Landscapes [NNX13AG03G]
Role of A. Hayes:
Principal Investigator
Source of Support:
ROSES 2012, CASSINI DATA ANALYSIS AND PARTICIPATING SCIENTSIST
PROGRAM
Point of Contact:
Chritina Richey (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-1364 E-mail: HQ-CDAP@mail.nasa.gov
Award Amount:
$537,045 ($300,000 to A. Hayes) Period Covered: 1/1/2013-12/31/2015
Person-Months Commitment to the Project: 2 MM Fraction
of
Work
Year:
16%
X Current
Pending
Submission Planned in Near Future
Project/Proposal Title:
Role of A. Hayes:
Source of Support:
Point of Contact:
Cornell / NASA Spacecraft Planetary Imaging Facility (SPIF) [NNX13AC79G]
Principal Investigator
ROSES 2012, PLANETARY GEOLOGY AND GEOPHYSICS PROGRAM
Michael S. Kelley (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-0607 E-mail: HQ-PGG@mail.nasa.gov
Award Amount:
$120,000 ($120,000 to A. Hayes) Period Covered: 1/1/2013-12/31/2013
Person-Months Commitment to the Project: 1 MM Fraction of Work Year: 8%
Pending Support:
Current
Pending
X Submission Planned in Near Future
Microwave Observations of Saturn’s Rings From Cassini
Principal Investigator
ROSES 2013, CASSINI DATA ANALYSIS AND PARTICIPATING SCIENTSIST
PROGRAM
Point of Contact:
Chritina Richey (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-1364 E-mail: HQ-CDAP@mail.nasa.gov
Award Amount:
$125,507
Period Covered: 1/1/2014-12/31/2014
Person-Months Commitment to the Project: 1 MM Fraction
of
Work
Year:
8%
Project/Proposal Title:
Role of A. Hayes:
Source of Support:
Current
Project/Proposal Title:
Role of A. Hayes:
Source of Support:
Point of Contact:
Award Amount:
32
Pending
X Submission Planned in Near Future
Investigation of Titan's geological structures and surface materials from coanalysis of Cassini ISS, VIMS, and RADAR data
Co-Investigator (PI is Elizabeth Turtle, JHU/APL)
ROSES 2013, CASSINI DATA ANALYSIS AND PARTICIPATING SCIENTSIST
PROGRAM
Chritina Richey (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-1364 E-mail: HQ-CDAP@mail.nasa.gov
$TBD ($48,914 to A. Hayes)
Period Covered: 1/1/2014-12/31/2016
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Person-Months Commitment to the Project: 0 MM
Intern)
Current
Pending
Fraction of Work Year: 0% (Support for UG Summer
X Submission Planned in Near Future
EXPLORING TITAN’S GEOLOGY IN THREE DIMENSIONS WITH
DIGITAL TOPOGRAPHIC MODELS FROM CASSINI RADAR STEREO
Role of A. Hayes:
Co-Investigator (Principal Investigator is Randolph Kirk, USGS)
Source of Support:
ROSES 2013, CASSINI DATA ANALYSIS AND PARTICIPATING SCIENTSIST
PROGRAM
Point of Contact:
Chritina Richey (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-1364 E-mail: HQ-CDAP@mail.nasa.gov
Award Amount:
$TBD ($33,184 to A. Hayes)
Period Covered: 1/1/2014-12/31/2016
Person-Months Commitment to the Project: 0.25 MM
Fraction of Work Year: 2%
Project/Proposal Title:
Current
Pending
X Submission Planned in Near Future
Characterizing Titan's dunes and dune-topography interactions: Implications for
climate change in Titan's equatorial region
Role of A. Hayes:
Co-Investigator (Principal Investigator is Ryan Ewing, Texas A&M)
Source of Support:
ROSES 2013, CASSINI DATA ANALYSIS AND PARTICIPATING SCIENTSIST
PROGRAM
Point of Contact:
Chritina Richey (Planetary Science Div. Science Mission Directorate NASA)
Ph. (202) 358-1364 E-mail: HQ-CDAP@mail.nasa.gov
Award Amount:
$TBD ($105, 697 to A. Hayes)
Period Covered: 1/1/2014-12/31/2016
Person-Months Commitment to the Project: 1 MM Fraction of Work Year: 8%
Project/Proposal Title:
Jet Propulsion Laboratory
Paul O. Hayne
33
Composition of Titan’s Dunes
Co-Investigator: Jean-Philippe Combe
34
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Co-Investigator: Thomas McCord
Jet Propulsion Laboratory
Paul O. Hayne
35
Composition of Titan’s Dunes
Budget Justification
Budget Justification: Narrative
Summary of Personnel and Work Efforts
Name
Dr. Paul Hayne
Dr. Jean-Philippe
Combe
Dr. Thomas McCord
Dr. Alexander Hayes
Organization
JPL
Bear Fight
Institute
Bear Fight
Institute
Cornell U.
Role
PI
Co-I
Co-I
Work Commitment
Fraction of Work
Year (1840 hours)
Year 1
Year 2
.21
.21
.05
.08
.02
.02
Co-I
Facilities and Equipment
Standard computer equipment and data processing software (including existing
ENVI licenses) are available at no additional cost. The undergraduate student will use
SOCET SET® and ArcGIS to map dunes, using software and workstations already
available in Co-I Hayes’ lab at Cornell.
Rationale and Basis of Estimate
The cost proposal was prepared using JPL’s Pricing System and the current
internally published Cost Estimation Rates and Factors, dated April, 2013.
The derivation of the cost estimate is a grassroots methodology based on the
expert judgment from a team of experienced individuals who have performed similar
work. The team provides the necessary relevant experience to develop a credible and
realistic cost estimate. The cognizant individuals identify and define the products and
the schedule needed to complete the tasks for each work element. Then they generate
the resource estimates for labor, procurements, travel, and other direct costs for each
work element. The resource estimates are aggregated and priced using JPL’s Pricing
System. JPL’s process assures that lower level estimates are developed and reviewed by
the performing organizations and their management who will be accountable for
successfully completing the proposed work scope within their estimated cost.
36
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Budget Justification: Details
Year 1:
Direct Labor:
 Dr. Paul Hayne is the PI and will oversee all aspects of the proposed work. Dr.
Hayne will perform … ($X requested salary with $Y fringe benefits)
Equipment: There are no major equipment purchases necessary
Travel: The PI will travel to the LPSC meeting in The Woodlands, TX, to present the
results of this investigation.
Other:
 Multiple Program Support (MPS): $XX
Facilities and Administrative Costs:
 Allocated Direct Costs (ADC): $XX
 General and Admin: $XX
Subcontracts/Subawards:
 Desktop Network Chargebacks (calculated at $6.06/hr.): All JPL computers are
subject to a monthly service charge that includes hardware, software, and
technical support. ($XX)
Total Estimated Cost for Year 1: $XX
Year 2:
Direct Labor:
 Dr. Paul Hayne is the PI and will oversee all aspects of the proposed work. In Year
2, Dr. Hayne will focus on … ($XX requested salary with $XX fringe benefits)
Equipment: There are no major equipment purchases necessary
Travel: The PI will travel to …
Other:
 Multiple Program Support (MPS): $XX
Facilities and Administrative Costs:
 Allocated Direct Costs (ADC): $XX
 General and Admin: $XX
Subcontracts/Subawards:
Jet Propulsion Laboratory
Paul O. Hayne
37
Composition of Titan’s Dunes
Desktop Network Chargebacks (calculated at $6.06/hr.): All JPL computers are subject
to a monthly service charge that includes hardware, software, and technical support.
($XX)
Total Estimated Cost for Year 2: $XX
38
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Budget Details
Jet Propulsion Laboratory
Paul O. Hayne
39
Composition of Titan’s Dunes
Budget Justification: Participating Scientist Request
Narrative
Summary of Personnel and Work Efforts
Facilities and Equipment
Rationale and Basis of Estimate
Details
Year 1
Year 2
40
Paul O. Hayne
Jet Propulsion Laboratory
Composition of Titan’s Dunes
Budget Details: Participating Scientist Request
Jet Propulsion Laboratory
Paul O. Hayne
41