This week we are identifying the advantages, disadvantages, and differences between common surface interpolations tools!
While assessing the difference between the different surface interpolation tools this week, we learned that there are many options and variables to consider when deciding what tool to use and when. To examine this closely, we ran the IDW, Spline, and Thiessen Polygon tools and visualized the output differences using classifications, histograms, layouts, and tables. It was easy to notice right away that, even when a good number of samples are available, there can be drastic differences in how predictions are made by specific deterministic methods. In the simple map below of Tampa Bay, the Biochemical Oxygen Demand (BOD) is displayed in milligrams per liter, a popular water quality parameter.
This screenshot of the output, created from the Spline tool using the tension option, appeared to combine the advantages of the IDW with a low standard deviation, or error, and resulted in no drastic changes in the minimum, maximum, or mean values:
The original Spline output, that was not regularized with average values, had distorted results caused by two points in extremely close proximity with a large difference in value, which caused the sample containing a high value to be mostly ignored. The IDW result was decent, but still had broad inaccuracies caused by points being too far apart. The best seemed to be the Spine with the tension option (seen above), which resulted in a smooth map with accurate results.
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