Lab 5: Interpolation

 The lab provided insight into interpolation methods which include:

• Thiessen polygons
• Inverse Distance Weighting (IDW)
• Spline
• Kriging

Thiessen Polygon (a.k.a. Voronoi polygon) 

Thiessen polygon is proximity based interpolation which partitions an area by corresponding point's influence. This method of interpolation provides the means to better understand the distribution or the "points" area of influence.

Inverse Distance Weighting (IDW)

The IDW interpolation operates using the principle that the closer surrounding points are to a given location the more influence (weight) they have on the estimated value. The IDW is best used when the geographic phenomenon is spatially measured uniformly (i.e. relatively uniform distribution). 

Spline

The spline method like linear interpolation pass through the know points but applies a smoothing effect. The smoothing (tension) is adjusted to best fit a natural phenomena which is expected to smoothy transition over distance. 

Kriging

Kriging interpolation is a computational intense geostatistical technique which estimates unknown values at specific location based surrounding point values. There are different types of Kriging but generally is a powerful method which provide a prediction and insight into the reliability of the prediction. 

Spline Interpolation - Water Quality Tamp Bay (instructional purpose only)