Wednesday, September 10, 2025

Module 2 - Data Quality Standards

 The purpose of this lab was to determine the quality of road networks and to determine the positional accuracy of two road networks by comparison. To be able to determine the quality and positional accuracy of the road networks, we needed to understand and employ the methodology of procedures set by the National Standard for Spatial Data Accuracy (NSSDA). 

To begin the analysis, 60 test points in total were added to a project area in equal distribution. Twenty test points were placed on ABQ intersections, and 20 test points were placed on USA intersections immediately adjacent to the ABQ intersections. Then, 20 reference points were placed in the immediate vicinity of those intersections to get the most accurate measurement of the actual intersection. Here is what this looked like:



 Then to confirm the accuracy of the ABQ points and USA points, we needed to add point X and Y coordinates to each point to get the coordinates to calculate the accuracy. To begin calculating the accuracy, we needed to export the table to Excel, and once added to Excel, I formatted my table to find these calculations:


Diff in X is X(ABQ) - X(Ref), then Diff in X^2 is the value gotten from subtracting squared; the same steps were done for Y. Then to be able to calculate the sum, average, Root Mean Square Error (RMSE), and the actual NSSDA accuracy, you needed to add the Diff in X^2 and Diff in Y^2 values together. To get the average, I took the sum and then divided by 20, and then to get the RMSE, I square rooted the average, and then to get the final NSSDA accuracy, I multiplied the RMSE by 1.7308 to get the horizontal accuracy. 

To adhere to the NSSDA standards, here is my formal NSSDA accuracy statement:

Using the National Standard for Spatial Data Accuracy, the ABQ data set tested at 24.16 ft or 7.36 meters horizontal accuracy at 95% confidence level.

Using the National Standard for Spatial Data Accuracy, the USA data set tested at 201.52 ft or 61.42 meters horizontal accuracy at 95% confidence level.

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