GIS 4930, Lab 5, interpolation methods

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This was a fun lab, we got to experiment with various interpolation methods to produce continuous data from discrete data points. A significant part of the lab was comparing and contrasting each interpolation method, and finding out ways to recognize and account for the possible ways interpolation could distort or misrepresent data.

For example, spline interpolation is like a plane that is forced to meet every data point, and distorts itself to do so. One of the exercises featured us having a spline reult with anomalously high concentrations of pollution, and finding a way to normalize the data.

IDW is an interpolation method that uses a weighted average of known data points, proportional to the distance they are from the interpolated area. We also created Thiessen polygons, which are irregularly shaped polygons where every point inside the polygon is closer to the sampling point than any other point.

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