Today, attendees gathered for one of Geo Week's most candid sessions: "The Ugly Truths About Bathymetric Lidar." Unlike typical conference presentations showcasing polished results or new tech, this session promised something different: an honest look at what goes wrong in bathymetric lidar acquisition and processing, and how professionals can help fix it.
Moderated by Christopher Macon of USACE, the panel brought together four industry veterans: Colin Cooper from NV5, Nicholas Johnson from USACE, Josh Novac from Dewberry, and Nick Wilson from Woolpert, Inc. Their mission: to reveal the sometimes messy reality behind bathymetric datasets.
Bathymetric lidar, the technology that uses laser pulses to map underwater topography, has become increasingly critical for coastal management, infrastructure planning, and environmental monitoring. Recent advances in the process of bathymetry have stunned many in the industry, but for organizations considering adoption or just starting out, the learning curve can be steep and expensive. This session addressed a gap rarely discussed in professional forums: what happens when data doesn't cooperate, and how experts troubleshoot their way to success.
Below, we have a few challenges that were common topics throughout the session.
Challenge 1: Unpredictable Environmental Conditions
One of bathymetric lidar's biggest challenges is environmental unpredictability. Unlike topographic lidar operating in air, bathymetric systems must penetrate water with conditions that can make or break a project. As Josh Novak from Dewberry noted, "the ugly truth is that it doesn't always work right."
Water clarity, turbidity, bottom reflectivity, and weather interact in ways difficult to predict during planning. The panel showed two flights over identical areas: poor conditions yielded almost no coverage, while improved conditions achieved complete coverage.
Weather is also a challenge. Flying on days where weather isn’t pristine risks expensive reflights, but waiting for perfect conditions may cause surveyors to miss the opportunity entirely.
Challenge 2: Water Surface Detection and Processing Complexity
Processing bathymetric lidar data is complex, particularly water surface detection. Errors in this area can affect the entire workflow. The panel showcased failures they’d witnessed: power lines misclassified as water surface, sensor issues missing detection entirely, and algorithms placing surfaces in unrealistic locations.
Classification presents unique challenges as well. One cross-section showed that the apparent bathymetric surface was actually noise, and the true bottom was two layers below. Standard topographic classification tools don't work well underwater, and emerging bathymetric algorithms still need innovation. Various noise sources require sophisticated algorithms and experienced human interpretation.
Challenge 3: Managing Client Expectations
Bathymetric lidar cannot be held to the same expectations as topographic lidar. Water absorption and scattering mean actual bottom point density will be significantly lower than shot density, and clients expecting precision may have to settle for something close enough.
Panelists agreed that early communication about potential gaps in deliverables is essential. They also strongly advocated for cross-sections and checkpoints to verify performance and processing accuracy, especially in new environments.
These three challenges were a recurring theme through the session, and can help us define the current state of bathymetric lidar. The discussion revealed that while bathymetric lidar is a powerful tool for mapping underwater, it still requires careful planning, processing, and realistic expectations.
The experts emphasized that success in bathymetric lidar depends on selecting the right system for the application, understanding environmental limitations, developing robust processing workflows, and maintaining open communication with clients about what the technology can and cannot deliver.
