Accurate positioning is the foundation of modern surveying, mapping, utility management, and infrastructure operations, yet GNSS performance is increasingly challenged by obstruction, interference, and demanding field conditions. This session explores innovative approaches to maintaining reliable geospatial accuracy through sensor fusion, high-precision field workflows, GNSS quality assurance, and alternative positioning methods for GNSS-denied environments, highlighting real-world applications from utility mapping and regulatory compliance to airborne lidar operations.
12:00 PM – 12:15 PM
When Centimeters Fail in the Field: Catching GNSS Errors Before They Corrupt the Deliverable
Presented by Michael Leppitsch, Point One Navigation
Every survey deliverable, as-built, and utility map is only as trustworthy as the positions behind it. But GNSS alone breaks down where the work actually happens: beside buildings and steel structures, under tree canopy, in trenches and rights-of-way, and in the multipath-heavy conditions of a live jobsite. This session examines what goes wrong when crews move from open-sky testing to production positioning across surveying, utility locating and damage prevention, and construction layout. It covers the sensor-fusion and correction-network strategies (GNSS, INS, and wheel odometry) that catch and correct these errors before they propagate into control, as-builts, and mapped features. Attendees leave with a practical framework for diagnosing positioning drift, evaluating RTK network density and coverage, and building field workflows that hold centimeter accuracy where the sky is obstructed, not just where it’s open.
12:15 PM – 12:30 PM
From GIS to GNSS: High-Accuracy Meter Collection for Lead and Copper Rule Compliance
Presented by Robert Eisenrich, McKim & Creed
In support of compliance with the EPA’s revised Lead and Copper Rule (LCR), PWC (Fayetteville Public Works Commission) undertook a project to collect high-accuracy GNSS locations for water meters across its service area. Accurate meter locations—particularly when linked to parcel boundaries—are a critical foundation for identifying potential lead service lines, prioritizing replacement efforts, and supporting defensible lead classification workflows.
Rather than surveying every location manually, PWC adopted a GIS-first approach to streamline planning and execution. Using existing meter records and service grids, we identified gaps in spatial accuracy and mapped concentrations of meters without verified GNSS data. This enabled us to generate a priority collection order based on data quality and meter density, maximizing efficiency in the field.
Field teams used ArcGIS Field Maps integrated with Trimble R12 receivers to capture sub-inch meter locations. Each collected point automatically inherited key non-spatial attributes—such as meter ID and service address—minimizing manual entry and preserving data integrity. By maintaining attribute continuity and capturing precise GNSS locations, the dataset now supports both utility operations and lead service line inventory management at the parcel level.
To provide real-time transparency, we deployed ArcGIS Dashboards that tracked collection rates and symbolized progress across the network. These visualizations enabled dynamic decision-making and gave stakeholders daily insight into field performance. We also incorporated QA/QC tools to flag low-accuracy points and inaccessible locations, ensuring continuous data quality control and facilitating follow-up coordination.
This project highlights how the thoughtful integration of GIS, high-precision GNSS, and smart field applications can meet evolving regulatory needs—like the Lead and Copper Rule—while dramatically improving operational efficiency. The result is a spatially authoritative meter inventory that strengthens PWC’s ability to assess lead exposure risk, prioritize remediation, and support customer outreach with confidence.
12:30 PM – 12:45 PM
When a Few Centimeters Matter: Transforming Field Operations with High-Accuracy GNSS
A few centimeters may seem insignificant—until they determine the location of critical underground infrastructure.
As utilities, municipalities, and infrastructure owners modernize their field operations, the demand for accurate, repeatable geospatial data continues to grow. High-accuracy GNSS is no longer reserved for traditional surveying—it is becoming an essential tool for improving field productivity, standardizing data collection, and creating more reliable infrastructure records.
This presentation explores how organizations are using high-accuracy GNSS to transform everyday field workflows. Rather than focusing on hardware specifications, the session examines how repeatable, centimeter-level positioning improves productivity, reduces rework, strengthens collaboration between field and office teams, and increases confidence in infrastructure data.
Attendees will leave with practical insights into where high-accuracy GNSS delivers the greatest operational value, key considerations for successful implementation, and proven strategies for modernizing field operations through more accurate and reliable positioning.
12:45 PM – 1:00 PM
Airborne Laser Scanning in GNSS-Denied Areas
Presented by Peter Rieger, RIEGL
Jamming and spoofing of GNSS signals have become common practice in war zones and areas of political tension. The unavailability of reliable GNSS signals has a major impact on mapping services in general and airborne laser scanning (ALS) in particular. We present a concept for ALS surveys without using GNSS. We also present the results of demonstration projects.
Conventional ALS is based on joint processing of synchronised observations of GNSS receivers, an inertial measurement unit (IMU), and a scanning laser ranging device. The prime role of GNSS is to determine the aircraft’s location in a georeferenced coordinate system. GNSS observations are combined with IMU measurements of accelerations and angular velocities in a Kalman filter to estimate the aircraft’s position and attitude as a function of time. With GNSS being unavailable, an alternative method is required to determine the aircraft’s position. We propose using bundle adjustment of images which are simultaneously acquired with IMU and laser ranging measurements. Several hybrid sensor systems with aerial cameras and a laser scanner have been introduced in recent years. The bundle adjustment will provide projection centre coordinates, which can be combined with the IMU measurements to estimate the flight trajectory. It is assumed that the dependencies of photogrammetry on GNSS can be eliminated, e.g. by using the laser ranging clock for synchronisation and by establishing tie points and tie surfaces to previously collected and already georeferenced imagery and point clouds.
We examine the feasibility of the concept and the quality of the resulting point cloud by using data of a project in which images were taken simultaneously with a traditional ALS survey. For purposes of lidar georeferencing the GNSS positions are replaced with camera positions, inertial measurements, and observations derived from laser scanning data. Compared to a conventional Kalman filter, this is an adjustment-based approach which tightly couples the IMU and lidar. This is especially beneficial here, where images and laser data are acquired only within the flight lines, and thus redundancy of a pure position and inertial data fusion is limited to periods with low dynamics.
This workflow differs from conventional processing by using a bundle block adjustment to determine camera projection centers instead of GNSS processing. The step of obtaining an initial trajectory for the nonlinear least-squares (NLS) adjustment is often realized with filter or sliding-window optimization, which is not directly possible as these methods may diverge during the long periods in-between flight lines without position aiding. Here, an artificially degraded single-positioning single-frequency GNSS solution is used purely for initialization. The point cloud of the traditional ALS survey serves as reference for analysing the quality of the GNSS-less point cloud based on internal consistency (strip differences compared to those of the reference point cloud) and absolute accuracy (block difference to reference point cloud).
