Corridor mapping is rapidly evolving through the integration of UAS, lidar, AI, and multi-sensor data collection platforms. Through research findings and real-world case studies, presenters will demonstrate innovative approaches that enhance asset inventory, vegetation management, infrastructure inspection, and large-scale corridor analysis while reducing field effort and improving data quality.
3:30 PM – 3:45 PM
Evaluating Oblique UAS Photogrammetry for Highway Corridor Mapping: An Experimental Framework Toward Best Practices
Presented by Yushin Ahn, California State University at Fresno
Oblique unmanned aerial system (UAS) photogrammetry has emerged as a promising complement to conventional nadir image acquisition for transportation mapping applications. By capturing side-looking imagery, oblique photogrammetry may improve the reconstruction of vertical features while potentially reducing the need for direct overflight of active roadways, making it particularly attractive for highway corridor mapping. Despite its growing interest, limited guidance exists regarding optimal flight configurations, expected mapping accuracy, and operational best practices for highway applications.
This study presents the experimental framework and methodology of an ongoing research project investigating the feasibility and best practices of oblique UAS photogrammetry for highway corridor mapping. The research evaluates multiple flight scenarios by varying key acquisition parameters, including flight altitude, camera look angle, image overlap, and flight offset from the roadway. The study also considers control and checkpoint configurations, as well as representative highway geometries commonly encountered in transportation mapping.
The presentation will introduce the overall research methodology, discuss the experimental design, and share preliminary observations from the ongoing investigation. The findings are expected to support the development of practical guidelines for transportation agencies considering the adoption of oblique UAS photogrammetry for highway corridor mapping and contribute to the broader discussion of emerging UAS mapping technologies.
3:45 PM – 4:00 PM
Helicopter Quality Mapping from a Fixed-Wing Platform: A Multi-Sensor Approach
Presented by Matt Bethel, Merrick & Company
Advances in airborne mapping have expanded the ability to collect high-quality geospatial data more efficiently and across a broader range of applications. This presentation explores the integration of multiple lidar and imaging sensors into a single fixed-wing airborne mapping platform and examines how multi-sensor acquisition strategies can improve data quality, operational efficiency, and project versatility.
Attendees will gain insight into system configuration considerations, data acquisition workflows, and the practical advantages of combining complementary sensor technologies within a unified platform. The presentation will discuss how these capabilities are enabling fixed-wing aircraft to support projects traditionally associated with helicopter-based mapping, creating new opportunities for large-scale and complex geospatial data collection.
The session will also review accuracy and precision performance using established industry standards, including ASPRS guidelines and USGS lidar base specification requirements. Real-world project examples will demonstrate how integrated multi-sensor approaches can meet diverse project objectives while maintaining high levels of quality, coverage, and efficiency.
4:00 PM – 4:15 PM
AI for Powerline Corridor Mapping: Automated Classification of Conductors and Vegetation Encroachment
Presented by Thadeu Lugarini, GeoCue Group
This presentation shares a real-world case study developed for Axia Energia in Brazil, demonstrating how AI-based classification in LP360 was used to automate the extraction of utility assets and identify vegetation encroachment along transmission line corridors. The workflow automatically classifies transmission towers, conductors, ground, and multiple vegetation classes, creating an accurate dataset for engineering analysis and vegetation management. Attendees will gain practical insights into implementing AI-powered classification workflows for utility corridors, understand the benefits and limitations of automated feature extraction, and learn how Brazilian transmission projects are using LP360 to accelerate lidar processing while improving consistency and operational efficiency.
4:15 PM – 4:30 PM
From Field Patrol to Virtual-First: Building a Multi-Sensor Lidar Workflow for Utility Vegetation Management at Corridor Scale
Presented by Daniel Perr, Pointerra
Utility corridor lidar programs are producing datasets that quickly exceed the capacity of conventional geospatial workflows. Multi-sensor collections combining mobile laser scanning, airborne lidar, and drone-based imagery generate heterogeneous point clouds that must be co-registered, classified, and analyzed across hundreds of kilometers of right-of-way, often within tight project timelines and under utility client QC requirements. This session presents a practitioner’s case study in how ArborMetrics Solutions, LLC, one of North America’s leading utility vegetation management firms, solved those data management challenges on the Fortis BC corridor program, and what the results reveal about what it takes to make lidar-derived outputs reliable enough to replace field-based inspection at scale.
ArborMetrics Solutions, LLC entered the Fortis BC program with a fragmented toolset: three separate software platforms required simultaneously to complete a single virtual inspection, with no unified environment for co-registering multi-sensor data or automating encroachment analysis. A previous remote sensing platform failed mid-project, unable to match imagery and point clouds, forcing an immediate pivot. The team needed a path from manual, multi-tool data management to a workflow where heterogeneous sensor data from MLS, ALS, and drone collections could be consolidated, classified, and queried in a single environment, with automated polygon extraction replacing manual clearance measurement for every span.
This session walks through the technical decisions behind that transition on a live corridor program: how multi-sensor datasets were co-registered and consolidated; how automated encroachment polygon generation was configured and validated against field-checked ground truth; how 2D and 3D analysis environments were unified to support both QC review and field crew work planning; and how a validation framework was established to build confidence in lidar-derived outputs to a standard acceptable for utility client deliverables. Presenters will also address the classification and filtering decisions that most directly affect output reliability, and the practical thresholds ArborMetrics Solutions, LLC has identified for when virtual inspection can replace physical site visits without a field check.
The operational results from the Fortis BC program validate the data quality approach. Virtual inspection is 4.8 times faster than equivalent field patrol on comparable sites. Physical site visits have been reduced by 62%, with crews arriving on-site with full situational awareness derived from lidar and imagery analysis rather than on-the-ground assessment. On validated low-risk sites, QC effort has been reduced by approximately 27%. These outcomes are presented not as marketing metrics but as a function of specific data pipeline decisions, and the session will be explicit about where the validation work is still ongoing and what the path to broader deployment looks like as the validated dataset continues to grow.
