Week 10: Spatial Interpolation and Prediction¶

Core Questions¶

• What is the difference between interpolation and extrapolation?
• How can spatial prediction fill gaps between sampled locations?
• How should prediction uncertainty be interpreted?

Concepts¶

• Spatial prediction.
• Interpolation versus extrapolation.
• Nearest-neighbor prediction.
• Inverse distance weighting.
• Kriging concepts.
• Gaussian processes.
• Prediction uncertainty.

Python Tools¶

• scipy.
• scikit-learn.
• optionally gstools.

Applied Lab¶

Students hide observations from a spatial dataset and reconstruct an environmental or ecological surface using multiple interpolation or prediction methods.

Deliverable¶

Submit a prediction comparison showing observed points, predicted surfaces, held-out error, and uncertainty or limitations.