Evaluating geospatial accuracy for equity analyses: A case study of the U.S. National Bridge Inventory

Abstract

This short communication seeks to develop and evaluate a generalizable methodological approach for geospatially matching infrastructure assets to socioeconomic data to better facilitate equity-informed transportation decisions. This study focuses specifically on providing insight into the spatial accuracy of the U.S. Department of Transportation (DOT)'s National Bridge Inventory (NBI) dataset at a national level via a method that is less computationally or manually intensive than past approaches. Phase 1 focuses on assessing the quality of existing NBI locational data using a geospatially-driven method. We find that 98.8% and 95.4% of the NBI records matched the reported state and county tag respectively, according to their reported latitude and longitude. Phase 2 focuses on potential ways to correct locational mismatches. We find that a 30.5 m (100 ft) buffer and Thiessen polygons provide the greatest improvements in matching accuracy in the NBI record over point coordinates. Phase 3 assesses the feasibility of enhancing location granularity through a hand-checked case study. We find that for coarser geospatial levels (state and county), equity-based analyses may be possible, but for more granular geospatial levels (place and census tract), which is where equity-based analyses are often conducted, the data may need greater buffering and hand checks to ensure accuracy. To use more automated processes at these high spatial resolutions, governments and other policy-making entities will likely need to require quality control checks of longitude and latitude infrastructure data. This work provides the first systematic analysis of the robustness of the NBI data for equity-based analyses, as well as possible policies to improve its usage for equity analyses.