UTC 2022 Funding - Cycle 2 Research Projects

Project Number: CY2-OSU-OU-02
Project Title: Coupling Remote Sensing and Machine Learning to Improve Culvert Inventories for Climate Resilient Infrastructure and Aquatic Connectivity
Performing Institutions: Oklahoma State University and University of Oklahoma
Principal Investigators: Jaime Schussler, Oklahoma State University; Thomas Neeson, University of Oklahoma
Proposed Start and End Date: 10/01/2024 to 09/30/2025
Project Description: Culverts are critical infrastructure that provide our transportation network with a safe interface with surface waters; however, only 19% of total road-stream intersections in Oklahoma have a documented hydraulic structure, such as a culvert. Additionally, culverts that are inadequately designed or aged are at risk of causing flooding or even failure during high flow events, which could significantly impact transportation connectivity and safety. The lack of a comprehensive database of the location and condition of culverts in OK severely limits strategic investment in climate-resilient transportation infrastructure and the restoration of aquatic ecosystem connectivity, particularly in lesser-resourced areas such as rural and tribal areas.

This project aims to identify and improve culvert inventory, inspection, and prioritization methods to improve the climate resilience and aquatic connectivity of culverts using remotely sensed, publicly available data. Specifically, the project will 1) apply spatial analysis to Oklahoma LiDAR and imagery data to identify culvert locations and attributes and validate with the OK Culvert Database developed in the Cycle 1 SPTC project using statistical analysis, 2) train a machine learning algorithm to characterize culverts based on input data sets (e.g., georeferenced images), 3) develop inspection protocols that incorporate remote sensing to aid in culvert prioritization and rehabilitation efforts for transportation and aquatic connectivity, and 4) apply methods to case study watersheds to evaluate their efficacy.
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