During this module, we used various interpolation methods to create a visual representation of water quality in the Tampa Bay. We utilized Spline (Regular/Tension), Inverse Distance Weighting, and Thiessen methods. The biggest lesson I learned during this module was that the sample point set and surface can affect what interpolation method works best!
The Thiessen method finds the sample values of the "nearest neighbor" and gives a proportionate weight to the value. With Inverse Distance Weighting, weighted values are assigned according to distance. With the Spline Technique, a mathematical equation is used based on surface curvature.
Below is a screenshot of the Inverse Distance Weighting Interpolation Technique:
(Note: The data provided for this exercise was intentionally modified for instructional purposes and is not an accurate representation of the water quality in Tampa Bay.)
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