Module 1.3: TIGER Roads vs County Street Centerline Data Quality Assessment

The main goal for this module was to compare the quality of data for two similar road datasets, TIGER Roads (2000) and county Street Centerlines. Both datasets contain polyline street centerlines and attribute information for roads within Jackson County, Oregon. To provide both numerical and visual representations of the analysis, the county was divided into grid cells with equal areas, or 25 square km. In order to compare the two datasets, the length, in kilometers, was calculated for both datasets for each grid cell. The process started by clipping the Grid polygon dataset to remove streets that fall outside the boundaries of the grid cells. Then, the PAIRWISE INTERSECT tool was used, in which the input features were the clipped Street Centerline and the Grid datasets and the output type was set to Line. Then, the DISSOLVE tool was used to dissolve based on the GRIDCODE attribute with multipart features. A new length field was added (double, 1 decimal place) to calculate the new total roads lengths that fall within each individual grid cell in kilometers. This process was also repeated on the TIGER Roads polyline data. The JOIN FIELD tool was used to join the attributes with corresponding length calculations per grid cell to the Grid attribute table using the shared GRIDECODE attribute. The percent difference was also calculated using the equation: 

Percent Difference = (Total Length of Street Centerlines - Total Length of Tiger Roads)/(Total Length of Street Centerlines) x 100

The final map symbolized the calculated percent difference for each cell based on a Natural Break classification scheme with 9 classes. 

The percent difference ranged from -140% to 68%. Yellow grid cells indicated only a slight difference in data accuracy, ranging from -4.7 to 4.2. Positive percentages, ranging in color from orange to red, indicated the Street Centerlines were more accurate than the TIGER Roads at that particular grid cell. Negative percentages, ranging in color from light green to dark green, indicated that the TIGER Roads was more accurate than the Street Centerlines. The table below best summarizes the results: 

Cells	Area (km^2)	Percentage of Total Area
Empty Cells	25	0.34%
Street Centerlines more detailed than Tiger Roads	4250	57.24%
Tiger Roads more detailed than Street Centerlines	3150	42.42%
Total	7425	100%

Based on the evaluation and the assumption that higher length calculations = more accurate road data, the Street Centerlines data is more accurate. However, the areas with the higher Street Centerline accuracy seems to be located more along the main roads/highways, while the areas where the TIGER Roads were more accurate are located were it is potentially more rural. Additional analysis could compare the results to land classification datasets to identify any correlations.