Data Quality-Standards

This week in class we examined the accuracy of two road networks, Street Map and City of Albuquerque.  We calculated accuracy with procedures provided by the National Standard for Spatial Data Accuracy (NSSDA).  We selected 20 street intersection locations and marked the location of the intersection provided in the Street Map data as well as the same intersection location for the City data.  We referenced each of these data sets with ortho-rectified imagery.  The test points are shown above in green for the city data, red for the street map and blue (slightly larger symbol) for the reference.  Finding appropriate test points was more challenging that I initially thought.  20 minimum points, with a minimum of 20% in each quadrant with minimum separation between points of 10% of the diagonal of the study area.

Accuracy Statistics were calculated seperately for City data and Street Map each utilizing the Ortho points as the reference.  The XY data of each point was obtained in ArcPro.  Those points were exported to Excel.  The calculations included differences for X & Y coordinates, each difference squared, and then the sum of X & Y.  Those sets were summarized as Sum, Average, RMSE, and NSSDA.

Formal accuracy statements as per the NSSDA guidelines are:

Horizontal positional accuracy for Street Map:  Tested 70,116.2 Feet horizontal accuracy at 95% confidence level.

Horizontal positional accuracy for City of Albuquerque: Tested 605.8 Feet horizontal accuracy at 95% confidence level.

 
The accuracy position at 95% confidence is quite different:  City data at 605.8 feet; Street Map at 70,116.2 feet.  The importance of knowing the source of your data as well as its accuracy became abundantly apparent!