University of North Carolina Wilmington (UNCW) has uniquely positioned itself as a leader in the unmanned aerial systems (UAS hereafter) field over the last several years, in large part thanks to a research contract awarded by the NCDOT in August 2019, slated to end Dec. 31st 2021. Through prior UAS work led by PI Pricope and the work completed under RP2020-04 (Fusing multi-source UAS-derived data to improve project planning and the NCDOT Wetlands Prediction Model), we have gained invaluable experience working with UAS-collected topographic LiDAR (Light Detection And Ranging) data and this uniquely positions us to continue to lead the development of frontier applied data collection, processing and implementation for NCDOT’s next generation topo-bathymetric LiDAR integration. Previous work has enabled my research lab to develop: 1) field data collection, sampling, calibration and validation protocols for effective UAS data collection and processing using both fixed-wing passive, as well as rotocopter-mounted active (LiDAR) sensors; 2) implement effective, replicable and transparent processing workflows to create validated, ortho-photogrammetrically and planimetrically correct UAS-derived products, following ASPRS technical standards for imagery and LiDAR data horizontal and vertical positioning accuracy; and 3) develop and apply geospatial analytical data classification (including machine learning) workflows and UAS to satellite imagery fusion techniques. Work conducted at multiple coastal wetland sites throughout the southeastern NC showed that the capabilities of topographic LiDAR data collection are severely limited in water-covered, partially-inundated, or tidally-influenced zones, where LiDAR returns are null. In this proposal, building on the extensive field, lab, data processing and machine learning classification approaches developed under RP2020-04, we make the case for extending NCDOT’s LiDAR capabilities by adding the capabilities of a topo-bathymetric LiDAR instrument to the array of UAS-borne sensors in NCDOT’s inventory. We propose to conduct highly applied research across a spectrum of clear, tannic and turbid waters of varying depths to fill gaps and improve data quality and collection capabilities for activities that include planning, monitoring and inspections. Examples of applications and data products include but are not limited to planning guidance for bridge, drainage, ferry, mitigation and abatement projects, modeling and mapping flooding and stormwater management approaches, aquatic habitats, hydrography, substrate and sediment transport, underwater archeology, and tidally-influence zones, and monitoring debris accumulation (dams, bridges), scouring, shoaling, channelization and sedimentation in ferry or shipping corridors. We plan to accomplish five distinctive tasks: 1) conduct thorough literature and technical review of the state-of-the-art in the UAS-based topo-bathy space both from an academic and industry perspective, including outreach and a review of other state DOTs similar capabilities and approaches; 2) create a replicable and easy to implement project design and sampling strategy that spells out pre- and mission criteria and considerations to ensure safe and successful project execution; 3) design and execute field data collections across a gradient of use cases and conditions and conduct outreach to public schools in the region during this process; 4) implement end-to-end data pre- and processing workflows for the site data collected and construct an implementation practicality envelope that clearly spells out what is and is not feasible and accomplishable with the request technology from an applied perspective by area of application (planning, modeling and mapping, and monitoring); and 5) conduct sustained outreach throughout the duration of the project to K-12 and university students from a range of socioeconomic backgrounds, conduct a 2-day NCDOT training/webinar series and create clear and usable final deliverables, including but not limited to technical instructions manuals for all stages of planning, collection, preprocessing, processing and visualizations, data dictionaries and metadata for all datasets created during the project, and final copies of all data collected. This project will result in time and cost savings through increased inspection capabilities, improved mapping and models of water areas, and more robust measurements of drainage system capacities.