Special Topics in GIS Lab 8

This week in the lab we focused in using interpolation methods to analyse water quality data near Tampa Bay, FL. The data given was point data for water quality levels over a body of water near Tampa Bay. The interpolations we used were the Thiessen, IDW, and Spline methods. All three are used popularly today for many applications. The image below is a representation of an Inverse Distance Weighting (IDW) interpolation.

I like the representation of this interpolation because it is visually pleasing even though it is not always the most accurate of the interpolations. The Thiessen or Nearest Neighbor or polygon (all the same) method basically divides up the area into polygons around the individual data points. This method keeps the integrity of the original data and uses that value for the rest of the polygon area. This method is not a very aesthetically pleasing one, but is more accurate than the IDW at times. Finally the spline method uses trends in the data to smooth out the visual to best represent the data as a whole. There are many ways to set up a spline, but as we learned in the lab they are not always the most accurate and are dependent upon the correctness of the collected data.