In this week’s lab, we studied data quality standards and processes to check map data for accuracy. To practice this, we used provided street data for the city of Albuquerque, NM. We compared the intersections of two different street data layers. One layer was created by the City, and the other was created by StreetMaps USA. The street data created by the City of Albuquerque was much more accurate.
To analyze the accuracy of these intersections, we also created a layer of reference points by examining aerial imagery and placing points in the center of each intersection. Then, we placed points where the street lines intersected for the other two layers. It was important in this step to make sure that the order in which we placed the points matched for each layer so that we could compare the three points for the same intersection.
Once we had three sets of data, we could add XY coordinates to the attribute tables for each layer and export the table to Excel to analyze. We employed a spreadsheet with the XY coordinates to determine the positional accuracy of the City points and the StreetMap USA points (when compared to the reference points). By studying the Positional Accuracy Handbook, we could create a formal National Standard for Spatial Data Accuracy (NSSDA) statement. The positional accuracy calculation tells us how closely the coordinates for each point match the true intersection location (as identified by the reference points) (Minnesota Planning, 1999).
My findings in the form of a formal accuracy statement as per the NSSDA guidelines are below.
City Data formal accuracy statement:
Tested 19.15 meters horizontal accuracy at 95% confidence level.
StreetMaps USA formal accuracy statement:
Tested 150.78 meters horizontal accuracy at 95% confidence level.
References:
Minnesota Planning. (1999). Positional Accuracy Handbook. St. Paul, ME: Author.
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