GIS5935 Lab 2: Determining Quality of Road Networks

This lab was a test for the horizontal accuracy of two network datasets for the city of Albuquerque, New Mexico. The first one is a StreetMap USA network, compiled from TIGER 2000 data. The second one, ABQ_Streets is centerline data provided by the City of Albuquerque Planning Department. The independent dataset used was a digitized shapefile for all of the test points (27 intersections), that was created using digital orthophotos from 2006. First, 27 well-defined locations were determined that were intersections in both datasets. Then the "true" intersection was determined using the orthophotos. Then the X and Y coordinates for all three datasets (independent, StreetmapUSA, and ABQ_Streets) were added and and the NSSDA statistics were determined. Sampling locations can be seen below:

Horizontal Positional Accuracy:

Using the national standard for spatial data accuracy, the ABQ_Streets dataset tested 22.908 feet horizontal accuracy at 95% confidence level.

the StreetMap_USA dataset tested 147.857 feet horizontal accuracy at 95% confidence level.

GIS5935: Completeness of Road Networks

This assessment was meant to determine and compare the completeness of two road networks for the same county.
First, the total length of each road network was determined. From there, a grid polygon was used to determine the completeness on a more specific level. This was carried out by using a combination of spatial analysis tools found in ArcGIS including Intersect, Dissolve, and Spatial Join tools. Once the completeness for both networks in each polygon was determined, the differences in length between each network were found for every polygon, and can be seen in the choropleth map below.

GIS5935 Lab 1: Accuracy & Precision

This lab dealt with measuring horizontal accuracy and precision. To measure horizontal precision, an "average" location has to be determined from the given data. After that, distances from the observations to that average must be measured, in order to find what distance corresponds to a specified percentage of the observations or given data. To measure horizontal accuracy, the "true" location must be determined or given, and then the distance to the average needs to be measured.

An example of precision estimates:

In this case, horizontal and vertical precision are at 4.4 and 5.7 meters, respectively, while the horizontal and vertical accuracy have 3.25 and 5.96 meter discrepancies, respectively.