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Soil Temperature Dataset Analysis: Gap-Filling and Fault Detection

Explore fault detection and gap-filling in soil temperature dataset using principal components analysis. Learn about censoring, outliers, and reconstruction techniques.

juliet-joseph
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Soil Temperature Dataset Analysis: Gap-Filling and Fault Detection

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  1. Gap-filling and Fault-detection for the life under your feet dataset

  2. Locations

  3. Soil Temperature Dataset

  4. Splitting into PC’s [raw] (notice faults) mean slope PC2 PC1

  5. Splitting into PC’s [censor + correct] mean slope PC2 PC1

  6. Example of censoring Good location Outliers

  7. Reconstruction using first 4 temporal PC’s

  8. With PC’s / Without PC’s

  9. Ciprians approximate trick Y’Y = VD2V’ Let U = YVD-1 Y = UDV’ YY’ = UDV’VDU’ = UD2U’

  10. Reconstruction using first 4 temporal PC’s

  11. Right eigenvector reconstruction

  12. Left eigenvector reconstruction

  13. Right vector / Left vector map

  14. Right Eigenvectors

  15. Left Eigenvectors

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