These data are intended for geographic display at national levels and for large regional areas. The data should be displayed at scales appropriate for 1:100,000-scale data. No responsibility is assumed by the U.S. Geological Survey in the use of these data.
The National Overview Road Metric-Euclidean Distance (NORM-ED) dataset was developed to describe the extent and configuration of the spaces between roads in the United States. The metric of NORM-ED is straight-line (Euclidean) distance, in units of meters, to the nearest road. The value of NORM-ED for any point estimates the largest radius of a circle, centered at that point, that contains no roads. The accuracy of the estimate is limited by the accuracy of the source data (see Source data below, p. 4), both in terms of roads depicted and their positions.
NORM-ED considers all roads to be equal, regardless of road surface, width, and traffic volume. The dataset from which NORM-ED was built contains features ranging from interstate highways to jeep tracks, although not necessarily with equal detail or reliability in all areas.
The full-resolution dataset provides distance-to-road (DTR) values on a 30-meter grid, using an equal-area projection. NORM-ED values can be aggregated statistically-by averaging, for example-over areas of the user's choice, and results are mathematically valid. NORM-ED can be used, therefore, to calculate comparable average DTR values for counties, states, watersheds, ecoregions, or any other area of interest.
Alaska had to be subdivided into sectors for processing owing to size limitations for numeric grids.
Sectors were processed individually, while attaching portions of adjoining sectors. Neighboring areas are included because they are not roadless. Without their inclusion, DTR values near core-area edges would be in error wherever roads just beyond the core-area boundary are closer than roads inside the core area.