TRIP develops indicators that describe how the transportation network subdivides the Nation's landscape, and how this subdivision and traffic on the network influence natural resources. Examples of TRIP products are a model of remoteness (estimated access time) of a back-country-landscape, a national dataset of distance to the nearest road, and a video portraying deflation of open space along Colorado's Front Range.

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 Euclidean distance, in units of meters, to the nearest road. The NORM ED value at any point estimates the largest radius of a circle, centered at that point, that contains no roads. Accuracy of the estimate is limited by the accuracy of the source data, 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 uniform detail or reliability in all areas.

The full-resolution dataset provides distance-to-road (DTR) values on a 30-meter image, 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 therefore be used to calculate comparable average DTR values for counties, states, watersheds, ecoregions, or any other area of interest.