Geostory Advances Domestically Developed Drone Bathymetric LiDAR

Geostory's domestically developed drone bathymetric LiDAR has successfully acquired stable underwater data at depths of up to 9.6 meters.

According to Geostory on July 28, this achievement demonstrates the potential of a drone-based bathymetric survey technology suitable for domestic rivers and coastal environments. It is particularly significant in that it presents to the public Geostory's capabilities in constructing 3D spatial information by linking ground and underwater data. From 2019 to 2023, through domestication research, Geostory secured the core technologies for the drone bathymetric LiDAR; currently, the company is continuing follow-up R&D to further enhance the equipment's performance and refine data processing technologies.

The drone bathymetric LiDAR system uses a dual-channel structure that utilizes Green 532nm and Near-IR 1064nm wavelengths, and it is designed to operate at a flight speed of 5 meters per second and at an altitude of 50 to 60 meters. In recent outdoor performance tests, the company compared and analyzed bathymetric detection performance by adjusting major parameters such as laser output, GAIN, and Offset. As a result, under certain conditions, the system achieved stable detection results from the low 8-meter to the low 9-meter range, and under optimal conditions, the underwater terrain was confirmed at depths of up to 9.6 meters.

Geostory's domestically developed drone bathymetric LiDAR offers high value, as it can simultaneously collect ground and underwater terrain data for rivers, reservoirs, and coastal areas, enabling the creation of continuous 3D spatial information. With a single drone flight, information on the riverbank, levee, water surface, and riverbed can be acquired collectively, reducing both time and cost compared to the existing method of combining vessel-based bathymetric surveys and ground surveys. Even in areas that are difficult to access, stable data can be obtained.

A Geostory representative stated, "We will continue to enhance detection performance and data quality, further developing this into a key technology that contributes to water resource safety management and the establishment of digital twin spatial information."

This content was produced with the assistance of AI translation services.