Abstract
Highway networks are represented by linear spatial objects (road segments). Having accurate length information of road centerlines is critical in transportation. This paper presents a geographic information system (GIS)-based approach that overlays planimetric road centerlines and elevation data to model road centerlines in a 3D space and estimate their lengths. Elevation sources included light detection and ranging (lidar) and the National Elevation Dataset (NED). The estimated distances were compared to distance measurement instrument (DMI)-measured distances to evaluate the accuracy. The effects of elevation datasets with varying vertical accuracies were assessed. The relationship between road geometric properties and the accuracy of distance estimates was examined. We found that (a) the proposed 3D approach is efficient in estimating 3D road centerline distances, (b) using lidar point data improves the accuracy by 28 percent over the use of NED, and (c) certain road geometric properties have direct relationship with the accuracy of distance estimates.
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