Interpolation and DEM Accuracy

The accuracy of continuous raster surfaces relies on the ability of the interpolation method to calculate values for areas between sample points that are as close as possible to the actual measurements.  This is, of course, determined by taking a measure of the difference between a value taken directly from the field and one produced by an interpolation method- the less difference between these two measures, the more accurate the interpolation.  Vertical (elevation) accuracy in DEM data can be influenced by a number of factors, most notably the features of the ground cover, as these can influence and obscure remotely sensed images and data.  Bias and uncertainty can be introduced rather easily into a data set, and can lead to systematic over or underestimation.  Looking at the summary statistics of the differences between measured and interpolated values for different methods may look something like this:

	IDW elevation	Spline elevation	Kriging elevation
mean (m)	-1.544	-2.365	-1.967
standard deviation (m)	11.695	10.196	12.024
median (m)	-1.759	-1.838	-2.144

The interpolation methods across the top- Inverse Distance Weighting (IDW), spline and kriging- produced elevation values for 63 different points that were then compared to the actual elevations, and the differences between the values are summarized in the table above.  The method with the lowest mean difference- IDW- could be argued as superior to the others, as it produces values that are, on average, closer to the actual measure.