Module 1.1 Lab: Calculating Metrics for Spatial Data Quality


 This week’s assignment focused on evaluating the precision and accuracy of GPS data. To do this, we worked with a set of waypoints mapped multiple times at the same location, then calculated an average position and compared it to a known reference point. By creating buffers around the average location and analyzing both horizontal and vertical errors, we explored how GPS measurements vary and how close they come to the true position. This exercise helped demonstrate the difference between accuracy (closeness to truth) and precision (closeness of repeated measurements), as well as the limitations of consumer-grade GPS receivers.

The map shows the projected GPS waypoints, the calculated average location, and circular buffers representing the 50%, 68%, and 95% precision thresholds. These buffers illustrate how far most points fall from the average location, helping visualize the spread of the data.

Results:

  • Horizontal Precision (68%): 6.0 m

  • Horizontal Accuracy: 4.3 m

  • Vertical Precision (68%): 5.9 m

  • Vertical Accuracy: 6.0 m

In this analysis, horizontal precision was determined by calculating the 68th percentile of distances from each waypoint to the average location, showing how tightly the measurements clustered. Horizontal accuracy, on the other hand, was measured as the distance between the average GPS location and the surveyed reference point.

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