Machine learning regressor predicts Martian thermal inertia at 12 m/pixel from CRISM VIR data with R² ≈ 0.90 and RMSE ≈ 23.6 TIU, producing downscaled maps an order of magnitude finer than THEMIS.
Hook, et al., The MODIS/ASTER airborne simulator (MASTER) — a new instrument for earth science studies, Remote Sensing of Environment 76 (2001) 93-102
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Producing High-Resolution Martian Surface Temperature Maps Using VIR-TIR Relationships
Machine learning regressor predicts Martian thermal inertia at 12 m/pixel from CRISM VIR data with R² ≈ 0.90 and RMSE ≈ 23.6 TIU, producing downscaled maps an order of magnitude finer than THEMIS.