Precision and Accuracy

 This week we explored the concepts of precision and accuracy and how to analyze the effectiveness of data collected in the real world.  Below is a map of an average waypoint generated from a collection of 50 data points collected in the field.  From the average, we can generate error buffers and determine if this is statistically significant in relation to the actual location of our waypoint (not represented on this map layout).  We can also use this data to determine outliers and to see which data points are actually useful in our location assessment.

For the discussion below, horizontal accuracy is measured as the difference between the true location of our waypoint and the average waypoint as calculated from our GPS collected data points.  Horizontal precision is a measure of how closely grouped together our field collected data points are and is a measure of the location consistency of the data collected.

Our average waypoint was 3.29 Meters from being truly accurate. Our acceptable precision is represented by a 4.55 meter (68%) buffer. The true waypoint falls within the range of the 68% buffer of our average waypoint and therefore falls within our general rule of acceptable accuracy estimation and is not significantly different when going by the established criteria. Even though this does fall within our 68% buffer, I would argue that the purpose of this waypoint would have a big impact on whether or not this level of precision is truly enough to be of concern. For some applications, I believe it would be.

The difference between the average elevation and the true elevation is 5.962 meters. This falls outside of our 68% vertical precision buffer of 5.888 meters. This difference is significant and could be very confusing if you were to try and determine a location based on average elevation from our data.

There is bias towards a higher elevation and a south and east location when using our average location in comparison to the true location.