Determining surface characteristics at candidate MSL landing sites using THEMIS high-resolution orbi...
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Robin Fergason Philip Christensen MSL Landing Site Selection Workshop May 31, 2006 PowerPoint PPT Presentation


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Determining surface characteristics at candidate MSL landing sites using THEMIS high-resolution orbital thermal inertia data. Robin Fergason Philip Christensen MSL Landing Site Selection Workshop May 31, 2006. Thermal Inertia Background. Used to infer a particle size of the surface layer

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Robin Fergason Philip Christensen MSL Landing Site Selection Workshop May 31, 2006

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Determining surface characteristics at candidate MSL landing sites using THEMIS high-resolution orbital thermal inertia data

Robin Fergason

Philip Christensen

MSL Landing Site Selection Workshop

May 31, 2006


Thermal Inertia Background

  • Used to infer a particle size of the surface layer

  • Helps to identify features, their location and extent on the surface, and their particle size

  • Detect exposed bedrock and dust


Ares Valles

Exposed Bedrock

6.4 N

Nili Patera

9.5 N

Christensen et al., 2003a; 2005

Rogers et al., 2005

3.4 km

3.5 km

5.9 N

8.7 N

66.9 E

67.6 E

341.3 E

341.6 E

800

260

950

190

THEMIS-derived thermal inertia overlain onto THEMIS visible


Hebes Chasma Interior Layered Deposits

TI: 125-145

TI: 190-245

TI: 275-360

TI: 290-420

125

615

800 m

Fergason et al., submitted

V10052001


I = (ρkc)1/2

ρ – bulk density

k – conductivity

c – specific heat

Thermal inertia measures a material’s resistance to change in temperature

Thermal Inertia Background


THEMIS-derived thermal inertia

  • Use thermal model developed by H. H. Kieffer

    • Ls, latitude, local time from spacecraft ephemeris

    • TES-derived albedo (8ppd)

    • MOLA-derived elevations (128 epd)

    • TES-derived dust opacity (2 ppd) every 30° Ls

  • Radiance at 12.57 μm (Band 9) is converted to brightness temperature, correcting for drift and wobble of the spacecraft

  • Interpolate upon a 7-D look-up table


THEMIS-derived Thermal Inertia Uncertainties

  • Uncertainties are primarily due to:

    (1) instrument calibration

    (2) uncertainties in model input parameters

    (3) thermal model uncertainties

  • Variations in thermal inertia within a single image are accurate and represent differences in the physical properties of the surface


Comparison with TES

TES

40 N

40 S

180 E

180 E

THEMIS

40 N

40 S

180 E

180 E

Fergason et al., submitted

25

600


Comparison of Mini-TES and THEMISThermal Inertia

250

430

Fergason et al., 2006


Landing Site Characterization

  • Identify regions of very high or very low thermal inertia

    • TI > 400 likely has rocky surface [Nowicki, 2006]

    • TI < 100 is likely dusty and not drivable

  • Evaluate surface properties of the candidate landing sites

  • Predicted surface temperature for the primary mission

    • Rover design temperature limits: 145 - 310 K

    • Maximum diurnal temperature range: 145 K


Opportunity THEMIS Temperature Mosaic - 2003


Opportunity THEMIS Temperature Mosaic - 2006


26.8 N

26.3 N

62.6 E

63.2 E

175

570

Fergason et al., submitted


THEMIS Day and Night IR


Thermal inertia is derived from THEMIS image

The derived thermal inertia value is then used to calculate the surface temperature for a given local time and season

Can predict the minimum surface kinetic temperature during the primary mission

Predicting Surface Temperature


ASU Will Provide

  • Interpretations of THEMIS and TES thermal inertia data for all candidate landing sites

  • Thermal inertia mosaics of candidate landing site regions (100 m)

    • Relative thermal inertia values


ASU Will Provide

  • Individual thermal inertia images of specific areas of interest (100 m)

    • Thermal inertia values of specific morphologies

  • Predicted temperature maps of candidate landing site regions (100 m)

    • Predict range of temperatures

    • Derive maximum diurnal temperature range


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