Metrics for Spatial Data Quality

The ability to describe, quantify, and understand spatial data quality is an essential function of all GIS practitioners and professionals. Two of the most common metrics used to describe spatial data quality are accuracy and precision. 

The terms accuracy and precision are sometimes used interchangeably. While these metrics of spatial data quality are certainly related, these two terms describe two distinct attributes. Accuracy refers to how close a mapped representation of an object is to the object's actual location, and precision refers to the consistency of a measurement method. 

Precision

The map below shows 50 waypoints that were collected at a single location using a Garmin GPSMAP 76 unit. The yellow star represents the average waypoint, which is the average XY coordinates of all 50 waypoints. The buffers extending out from the average waypoint represent the 50th, 68th, and 95th percentiles. These areas contain 50, 68, and 95 percent of all the waypoints taken. The most commonly used measure of precision is the distance within which 68% of observations fall. In this case, that distance was 4.47 m. 

Accuracy

Horizontal accuracy is simply the distance between the average waypoint and the "true" location of the point being mapped. Determining the "true" location can be very difficult, and even with the use of the most sophisticated survey equipment, the mapped location is never "perfect". When using GPS equipment, we are usually very pleased if we have a reference point accurate to within a few centimeters. In this case, the accuracy of the data was 3.24 m, which again is the distance between the reference point and the average waypoint.