Spatial Data Quality Standards

 This week we learned about the various data quality standards, specifically NMAS and NSSDA. In our exercise, we applied the NSSDA methodology to test the accuracy of two maps in Albuquerque, NM. The two maps are from the city of Albuquerque and StreetMaps USA. I used Minnesota Planning's Positional Accuracy Handbook as a reference(1999). 

After downloading the provided data and before starting the analysis, I first created my excel spreadsheet based on the worksheet provided by the Positional Accuracy Handbook (Minnesota Planning, 1999). Next, I created a point feature class and selected my 20 sampling points, referenced in Figure 1. I made sure the points were properly distributed, with each quadrant having less than 20% of the points. They are all located at intersections. 

Figure 1. 20 sampling points on the city of Albuquerque's map.

I then created two more feature classes for the StreetMaps USA map and the reference points. I made sure that I went in the same order as I added each point so they matched properly in the spreadsheet. Once I placed all of my test and reference points, I used the add geometry attributes tool to add each point's x and y coordinates. From there, I used the export to excel tool to move each of three coordinate tables outside of ArcGIS Pro. I then set up my horizontal accuracy worksheet with all of the coordinates and did my calculations. These are my final results:

City of Albuquerque's map:

Tested 18.70 feet horizontal accuracy at 95% confidence interval.

StreetMaps USA map:
Tested 400.6 feet horizontal accuracy at 95% confidence interval.

References:

Minnesota Planning. (1999). Positional Accuracy Handbook: Using the National Standard for Spatial Data Accuracy to measure and report geographic data quality.