Charting depths from above with airborne bathymetric Lidar

The mapping of underwater terrain and the monitoring of coastal and inland waters have been transformed by airborne bathymetric Lidar. The precision of laser-based remote sensing, combined with the ability to penetrate water surfaces, is utilized by this technology to provide critical data for environmental management, infrastructure planning and disaster preparedness. The principles, applications and advancements in airborne bathymetric Lidar are explored in this article, highlighting its potential to revolutionize the hydrographic surveying landscape.

Airborne bathymetric Lidar uses a pulsed green laser, usually at a wavelength of 532nm, to penetrate water surfaces and gather data from underwater landscapes. This wavelength is ideal because it penetrates water effectively, experiencing minimal absorption and scattering in clear water, which allows for accurate measurements of submerged features. The technology works on the time of flight (ToF) principle, calculating distances by measuring the time it takes for a laser pulse to travel to an object and back, such as the seafloor or riverbed. To ensure precise depth measurements, advanced refraction correction techniques based on Snell’s law are used to account for the bending of the laser beam at the air-water interface.

The sensor systems are complex, multi-component setups that include the following key elements:

1. Laser scanner: At the heart of the system is the laser scanner, which generates and directs laser pulses in scanning patterns over the survey area. While some scanners use only the green wavelength for measuring both bathymetry and topography in one go, others also incorporate infrared lasers to more precisely capture data from water surfaces. Dual-wavelength systems are particularly useful for mapping complex environments where water and land meet.
2. Global navigation satellite system (GNSS): The GNSS ensures that the sensor platform is precisely georeferenced. High-accuracy differential GNSS setups, often used with ground-based base stations, provide real-time or post-processed corrections to achieve positional accuracy to within a few centimetres. This capability is crucial for creating detailed maps and aligning datasets across multiple survey missions.

3. Inertial measurement unit (IMU): The IMU continuously monitors the aircraft’s attitude, including roll, pitch and yaw, to compensate for movements caused by turbulence or manoeuvring. This data, combined with GNSS outputs, allows for precise orientation of the laser pulses and accurate georeferencing of the collected points in three-dimensional space.

Together, these components create a tightly integrated system that produces high-resolution, geospatially accurate datasets. This allows for detailed analysis of submerged topography, aquatic vegetation and underwater structures.

Key performance metrics of airborne bathymetric Lidar

1. Penetration depth

The depth that bathymetric Lidar can penetrate is influenced by the water’s clarity, the laser’s energy output and the receiver’s sensitivity. In ideal conditions, such as clear water with low turbidity, it can reach depths up to three times the Secchi depth. For example, in clear coastal or inland waters, this could mean depths of over 30 metres. However, suspended sediments, algae or other particles can scatter and absorb the laser, reducing its effective depth. Advanced laser systems with higher pulse energy and optimized wavelengths are designed to overcome these challenges, providing more consistent depth measurements in various aquatic environments.

2. Accuracy

Bathymetric Lidar provides impressive accuracy for both topographic and bathymetric data points, achieving vertical precision to within 10cm. This high level of accuracy is due to the precise time synchronization of the Lidar system’s components, including the laser scanner, GNSS and IMU. Additionally, advanced processing techniques such as full waveform analysis and refraction corrections further enhance measurement precision by accounting for factors that include water surface dynamics and signal attenuation within the water column.

3. Point density

High-density Lidar systems can achieve point densities of over 50 points per square metre, which is crucial for creating detailed digital terrain models (DTMs) and bathymetric maps. This dense data coverage allows for the capture of fine-scale features, such as small geomorphological structures, submerged vegetation and artificial underwater objects. Achieving this density depends on factors such as flying altitude, laser pulse repetition rate and scanning geometry. High point densities are especially valuable for applications such as habitat modelling, floodplain analysis and infrastructure monitoring. However, for the sake of eye safety, green lasers are not as collimated as IR lasers used for topographic mapping and show a laser footprint diameter on the surface of over 10–50cm when operated from drones or crewed aircraft, respectively.

These metrics highlight the versatility of airborne bathymetric Lidar in capturing detailed and accurate data across a wide range of aquatic and terrestrial environments.

Applications of airborne bathymetric Lidar

1. Coastal and riverine mapping. Airborne bathymetric Lidar is widely used for mapping submerged and intertidal topographies, providing high-resolution datasets essential for coastal zone management, floodplain analysis and navigation safety. The technology helps to identify underwater hazards, sandbanks and erosion-prone areas, supporting maritime activities and infrastructure planning.
   Example: The RIEGL VQ-840-G has been successfully deployed in Austria to map submerged riverbeds with exceptional detail, enabling precise modelling of river morphology and aiding hydrological assessments​ (Mandlburger et al., 2023).
2. Hydrodynamic and erosion studies. Accurate DTMs generated from bathymetric Lidar are crucial for studying hydrodynamic processes and sediment transport. By capturing detailed information about channel morphologies and patterns of sediment deposition or erosion, this technology is invaluable for understanding river systems and managing waterway stability. Morphodynamic studies can also use this data to document and predict changes caused by floods or infrastructure projects.

Example: Post-flood erosion analyses in fluvial environments highlight the ability of Lidar to track sediment displacement and quantify volumetric changes over time​​ (Mandlburger et al., 2015).

3. Environmental monitoring. Bathymetric Lidar plays a crucial role in environmental management by providing insights into aquatic vegetation distribution, habitat structures and ecosystem health. Its ability to capture water surface and column attributes also supports water quality assessments. Additionally, the technology helps detect submerged debris or pollutants, aiding in conservation and restoration efforts.
   Example: Detailed submerged topography data from green laser systems has been employed to monitor vegetation habitats in coastal and riverine ecosystems (Islam et al., 2022; Janowski et al., 2022).
4. Disaster management. In disaster scenarios, bathymetric Lidar is a crucial tool for modelling and mitigation. High-resolution elevation data supports simulations of storm surges, tsunamis and riverine floods, enabling predictive models to assess risks and plan evacuations. After disasters, Lidar can be used to quantify damage, such as erosion from storm surges or changes in channel morphology after flooding.
   Example: Coastal flood simulation models enriched with Lidar-derived DTMs help forecast the impact of rising sea levels and storm events​​ (Awadallah et al., 2022; Choné et al., 2021).

These applications demonstrate the versatility of bathymetric Lidar in addressing critical challenges in environmental and infrastructure management as well as disaster risk reduction.

Technological advancements in bathymetric Lidar

The evolution of bathymetric Lidar technology has been marked by substantial innovations in sensor design, data processing and operational platforms. These advancements have enhanced the technology’s accuracy, versatility and affordability, expanding its application potential across various fields. Key technological strides include:

1. Full waveform analysis. Full waveform analysis is a significant advancement in Lidar data processing (Schwarz et al., 2019). Instead of capturing just discrete points, this technique records the entire reflected laser signal, allowing for detailed modelling of water columns, submerged features and even turbidity levels. By analysing attributes such as pulse amplitude, echo width and waveform shape, full waveform analysis can distinguish between vegetation, sediment and solid surfaces, enriching datasets for ecological studies and sedimentology (Ji et al., 2022). Additionally, this approach enhances depth penetration by optimizing signal processing for attenuated returns in turbid waters.
2. Dual-wavelength systems. Combining green and infrared lasers, dual-wavelength systems address the challenges of surveying complex environments (Gangelhoff et al., 2023). The green laser excels in penetrating water surfaces and mapping submerged features, while the infrared laser provides water surface information and topographic data of land surfaces and vegetation. This dual capability enables seamless integration of bathymetric and topographic mapping in a single flight, making the technology ideal for areas such as coastal zones and riverbanks where land and water intertwine.
3. Integration with UAVs. The miniaturization of Lidar systems has enabled their integration with uncrewed aerial vehicles (UAVs; Wang et al., 2022). Lightweight, compact systems such as the RIEGL VQ-840-G and the YellowScan Navigator are designed for UAV deployment, significantly reducing operational costs and allowing surveys in remote or hard-to-reach locations. UAV-based Lidar can fly at lower altitudes, improving spatial resolution and point density, making it ideal for localized studies such as habitat mapping or infrastructure inspections (Mandlburger et al., 2020). These systems also allow for more frequent data collection, supporting applications that require temporal analysis.

These advancements showcase the increasing sophistication of bathymetric Lidar technology, allowing for more accurate and comprehensive data collection while extending its use to new and challenging applications. Future innovations, such as AI-driven data processing and improved sensor designs, are expected to further enhance the capabilities of this transformative technology.

Challenges and limitations of bathymetric Lidar

While bathymetric Lidar provides remarkable capabilities for underwater mapping, the technology also has limitations. These challenges can affect its operational efficiency and data accuracy:

1. Water turbidity. The effectiveness of bathymetric Lidar heavily depends on water clarity (Saputra et al., 2021). In environments with high sediment loads, algae blooms or other particulate matter, the laser signal is significantly attenuated due to scattering and absorption. This reduces the penetration depth and limits the ability to accurately capture submerged features (Richter et al., 2017). Strategies such as full waveform analysis and laser pulse energy optimization help mitigate this, but the challenge remains significant in highly turbid waters (Maas et al., 2019).
2. Environmental conditions. External environmental factors, such as weather and surface dynamics, can greatly affect data quality (Tysiac, 2020). For example, cloud cover can block GNSS signals needed for precise georeferencing. Similarly, water surface conditions such as waves or sun reflections (glint effects) can disrupt the laser’s ability to penetrate uniformly, causing data inconsistencies. To minimize these impacts, it is essential to conduct surveys in calm conditions and at carefully chosen times.
3. High costs. Advanced bathymetric Lidar systems come with significant costs, not just for the hardware but also for maintenance, calibration and operation (Pricope & Bashit, 2023). Platforms such as manned aircraft or UAVs equipped with specialized sensors such as the Teledyne Optech CZMIL Supernova or the RIEGL VQ-880-GII require substantial investment. These costs can be prohibitive for smaller-scale projects or organizations. However, ongoing innovations in sensor miniaturization and UAV deployment are helping to reduce these expenses over time.

Despite these challenges, bathymetric Lidar is continually evolving. Ongoing research and technological developments are working to address these limitations and expand its usability across a wider range of environments.

Future prospects of bathymetric Lidar

The future of bathymetric Lidar looks bright, with ongoing advancements in both hardware and software technologies. These developments aim to overcome current limitations and open up new opportunities:

1. Integration of artificial intelligence (AI). AI-powered data processing is set to revolutionize the analysis of bathymetric Lidar datasets. Machine learning algorithms can enhance feature recognition, automate data classification and improve accuracy in complex environments. For example, AI can help detect submerged vegetation, sediment layers or underwater structures, significantly reducing the time and effort needed for manual post-processing. Additionally, predictive AI models can simulate environmental changes such as erosion or habitat shifts based on historical Lidar data (Kogut & Slowik, 2021).
2. Miniaturization of sensors. The trend towards compact and lightweight Lidar sensors is creating new deployment possibilities. Miniaturized sensors are increasingly being integrated with UAVs and small autonomous platforms, enabling surveys in hard-to-reach or sensitive areas such as shallow rivers, coral reefs or disaster zones. These systems not only reduce costs but also make frequent, localized surveys feasible, supporting applications such as dynamic habitat monitoring or real-time infrastructure assessment (Szafarczyk & Tos, 2022).
3. Enhanced sensor technologies. Upcoming sensors promise higher precision, greater depth penetration and multispectral capabilities (Guo et al., 2022). For example, advancements in single-photon and full waveform Lidar are expanding the limits of underwater resolution and penetration, allowing for detailed studies even in turbid waters. Dual-channel systems that combine topographic and bathymetric capabilities will further streamline operations in mixed environments.
4. Affordability and accessibility. As production costs decrease due to technological advances and market competition, bathymetric Lidar is becoming more accessible to a broader range of users (Igbinenikaro et al., 2024). This democratization will encourage its adoption in emerging markets and smaller-scale applications such as community-based coastal monitoring or environmental restoration projects.
5. Global applications. Expanding applications in climate change mitigation, disaster resilience and sustainable resource management are likely to further drive adoption. For example, bathymetric Lidar will play a critical role in modelling sea-level rise, designing resilient coastal infrastructure and managing aquatic ecosystems.

These advancements collectively point to a future where bathymetric Lidar becomes a standard tool in both scientific research and practical applications, offering unparalleled insights into the underwater world.

Conclusion

Airborne bathymetric Lidar is at the cutting edge of modern geospatial technology, representing a significant leap in our ability to map and analyse underwater environments. By combining precision, efficiency and versatility, this technology has become essential for applications in hydrology, environmental science, infrastructure development and urban planning. Its ability to capture high-resolution data from both submerged and terrestrial surfaces supports crucial initiatives such as coastal management, disaster preparedness and habitat conservation. Despite challenges that include water turbidity and operational costs, ongoing innovations in sensor technology, data processing and platform integration continue to enhance its capabilities and accessibility.

As we face increasing environmental challenges and technological advancements, the role of bathymetric Lidar in supporting sustainable development and disaster resilience will become even more crucial. By enabling informed decision-making and fostering a deeper understanding of aquatic and coastal systems, this technology is paving the way for a more resilient and sustainable interaction with our planet’s water resources.

References

Awadallah, M. O. M., Juárez, A., & Alfredsen, K. (2022). Comparison between topographic and bathymetric Lidar terrain models in flood inundation estimations. Remote Sensing, 14(1), 227.

Choné, G., Biron, P. M., Buffin‐Bélanger, T., Mazgareanu, I., Neal, J. C., & Sampson, C. C. (2021). An assessment of large‐scale flood modelling based on Lidar data. Hydrological Processes, 35(8), e14333.

Gangelhoff, J., Werner, C. S., & Reiterer, A. (2023). Lightweight dual-wavelength bathymetric Lidar for accurate seabed mapping. Multimodal Sensing and Artificial Intelligence: Technologies and Applications III,

Guo, K., Li, Q., Wang, C., Mao, Q., Liu, Y., Zhu, J., & Wu, A. (2022). Development of a single-wavelength airborne bathymetric Lidar: System design and data processing. ISPRS Journal of Photogrammetry and Remote Sensing, 185, 62-84.

Igbinenikaro, O. P., Adekoya, O. O., & Etukudoh, E. A. (2024). Review of modern bathymetric survey techniques and their impact on offshore energy development. Engineering Science & Technology Journal, 5(4), 1281-1302.

Islam, M. T., Yoshida, K., Nishiyama, S., Sakai, K., & Tsuda, T. (2022). Characterizing vegetated rivers using novel unmanned aerial vehicle‐borne topo‐bathymetric green lidar: Seasonal applications and challenges. River Research and Applications, 38(1), 44-58.

Janowski, L., Wroblewski, R., Rucinska, M., Kubowicz-Grajewska, A., & Tysiac, P. (2022). Automatic classification and mapping of the seabed using airborne Lidar bathymetry. Engineering Geology, 301. https://doi.org/10.1016/j.enggeo.2022.106615

Ji, X., Yang, B., Wang, Y., Tang, Q., & Xu, W. (2022). Full-waveform classification and segmentation-based signal detection of single-wavelength bathymetric Lidar. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14.

Kogut, T., & Slowik, A. (2021). Classification of airborne laser bathymetry data using artificial neural networks. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 1959-1966.

Maas, H.-G., Mader, D., Richter, K., & Westfeld, P. (2019). Improvements in lidar bathymetry data analysis. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42, 113-117.

Mandlburger, G., Hauer, C., Wieser, M., & Pfeifer, N. (2015). Topo-bathymetric Lidar for monitoring river morphodynamics and instream habitats—A case study at the Pielach River. Remote Sensing, 7(5), 6160-6195.

Mandlburger, G., Pfennigbauer, M., Schwarz, R., Flöry, S., & Nussbaumer, L. (2020). Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric Lidar Sensor. 12(6), 986. https://www.mdpi.com/2072-4292/12/6/986

Mandlburger, G., Pfennigbauer, M., Schwarz, R., & Pöppl, F. (2023). A decade of progress in topo-bathymetric laser scanning exemplified by the pielach river dataset. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-1/W1-2023, 1123-1130. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-1123-2023

Pricope, N. G., & Bashit, M. S. (2023). Emerging trends in topobathymetric Lidar technology and mapping. International Journal of Remote Sensing, 44(24), 7706-7731.

Richter, K., Maas, H.-G., Westfeld, P., & Weiß, R. (2017). An approach to determining turbidity and correcting for signal attenuation in airborne lidar bathymetry. PFG–Journal of Photogrammetry, Remote Sensing and Geoinformation Science, 85(1), 31-40.

Saputra, L., Radjawane, I., Park, H., & Gularso, H. (2021). Effect of Turbidity, Temperature and Salinity of Waters on Depth Data from Airborne Lidar Bathymetry. IOP Conference Series: Earth and Environmental Science,

Schwarz, R., Mandlburger, G., Pfennigbauer, M., & Pfeifer, N. (2019). Design and evaluation of a full-wave surface and bottom-detection algorithm for Lidar bathymetry of very shallow waters. ISPRS Journal of Photogrammetry and Remote Sensing, 150, 1-10.

Szafarczyk, A., & Tos, C. (2022). The Use of Green Laser in Lidar Bathymetry: State of the Art and Recent Advancements. Sensors (Basel), 23(1). https://doi.org/10.3390/s23010292

Tysiac, P. (2020). Bringing Bathymetry Lidar to Coastal Zone Assessment: A Case Study in the Southern Baltic. Remote Sensing, 12(22), 3740. https://doi.org/10.3390/rs12223740

Wang, D., Xing, S., He, Y., Yu, J., Xu, Q., & Li, P. (2022). Evaluation of a New Lightweight UAV-Borne Topo-Bathymetric Lidar for Shallow Water Bathymetry and Object Detection. Sensors, 22(4), 1379.