In this week's module we examined the differences between various surface interpolation methods. We went through the steps to create rasters using the Thiessen, IDW and Spline methods, then we compared the results.
This screenshot is of our study area, Tampa Bay, where we were given sample points representing the BOD of the bay. The first raster I made was the Thiessen raster. This involved using the Create Thiessen Polygons tool and converting the resulting shapefile into a raster. Thiessen interpolation creates proximal zones around the sample points and it can act as a starting point for greater data collection.
The second method involved using the IDW tool to create a DEM of the BOD points. IDW interpolation can be more sensitive to outliers than other interpolation methods. We also used the Spline method in this module.
We had to modify the original dataset in order to allow the Spline tool to function correctly. The northern portion of the bay had overlapping sample points, causing an area of unusually high BOD concentration to be generated by the Spline tool. To rectify this, I averaged the results of the overlapping points, overwrote one of the results with the average and deleted the other point. This way, the data would not be simply disregarded.
The Spline method can be split into two different methods: the regularized method and the tension method. The screenshot included in this blog post was created using the Tension method, which is a method that creates an output that stays closer to the known sample points when compared to the regularized method.
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