Lab 2: Standards

 This lab presented the various standards for spatial data accuracy. The one used in the lab is National Stand for Spatial Data Accuracy (NSSDA) which requires a minimum sample of twenty locations with 20% in each quadrant and greater than 10% the diameter of the study area.

The steps used to evaluate the accuracy of two road center line datasets,

1. Verify that the line feature in the road centerline datasets are split at each intersection.
2. Create a point feature using the Intersection tool;
3. Simplify the intersection point feature with the Multipart to Singlepart tool and delete duplicates using the features shape (geometry). This step may be in either order but the out come is a single point feature at each intersection
4. Use the Subdivide Polygon tool to divide the study area feature into four equal parts. This is used to ensure that no more than 20% of the sample are found within a quadrant.
   
5. Use the measure tool to record 10% of the study area's radius. This may be saved in a field for each of the four quadrants or written down for future reference.
6. Use the spatial select tool to select all intersection point feature which intersects the study area.
7. From that selection use the Create Random Points constrained to the one of the intersection points, enter the desired number of points, at least 20, and minimum distance. The minimum distance is the value from step 5.
   
8. Evaluate the random points to ensure that they are at good intersection. If not repeat step 7 or select an intersection in close proximity of the random sample intersection. It might be useful to use the select by attribute to limit the intersection to avoid ramps and limited access highways. 
9. Edit the random samples points moving them to the center of the intersection using the provided high resolution imagery. It is best to turn off all the other layers while establishing this control. 
   
10. Use the Add XYCoordinate tool to add the x, y-coordinates to the random sample points.
    
11. Use the Near analysis tool or spatial joins to associate the sample feature with the target intersection point. If using the Near analysis tool be sure to map the fields and select the location so the needed information for both intersections are added.
    
12. Export the feature to use in Excel and calculate the root square mean erorr (RSME) per the NASSDA guidelines. 

 

Shown below is a screenshot of the random sample location and road centerline; Based on these random samples the datasets have the expected accuracy:

The City of Albuquerque tested 12.78 feet horizontal accuracy at 95% confidence level.

The StreetMap USA road centerline tested 96.92 feet horizontal accuracy at 95% confidence level.