Lab 2 - Determining Quality of Road Networks

This week's lab continued in the theme of spatial accuracy and data quality.  Using the National Standard for Spatial Accuracy (NSSDA) statistics we compared the accuracy of two street datasets in Albuquerque, New Mexico.

Street test point locations in Albuquerque, New Mexico.

The first data set consisted of streets data provided by the City of Albuquerque - this was our 'truth' layer.  The second data set was a portion of the USA Streets layer provided by ESRI.  Both data sets were compared at 55 different test point locations.  Test point locations were selected using an ArcGIS Desktop Add-In called the 'Sampling Design Tool'.  These sample locations were then moved to the nearest four- or three-way intersection on the City of Albuquerque data.  Sample locations were discarded if the closest City of Albuquerque streets intersection did not also have a corresponding ESRI USA Streets intersection (the ESRI USA Streets layer was not as complete as that provided by the City of Albuquerque).

The reference layer was then hand digitized using aerial orthophotos of the study area (outlined in blue above). All reference points were taken in what can be considered the 'centerline' of the street, as viewed in the orthophoto image.  The two data sets were then compared to this reference location using an Excel table to compute the Euclidean distance difference between the reference x and y locations and the streets layer under comparison.  After following the NSSDA worksheet (the details of which can be viewed here: https://www.fgdc.gov/standards/projects/FGDC-standards-projects/accuracy/part3/chapter3) the results were as follows:

USA Streets Positional Accuracy:  Using the National Standard for Spatial Data Accuracy, the data set tested 264.7 feet horizontal accuracy at 95% confidence level.

Albuquerque Streets Positional Accuracy: Using the National Standard for Spatial Data Accuracy, the data set tested 51.5 feet horizontal accuracy at 95% confidence level.