The quality of hydrographic survey data is dependent on many aspects. The top-notch data requires constant alertness to the changing environment and thorough knowledge of the technology. In this article, we examine three common sources of error when doing 3D hydrographic surveys.
1 Positioning error
The survey vessel’s positioning system uses satellites to get the real-time location data, but the survey area may include GPS shadow regions, for example due to bridges, where the connection to satellites is cut off. In these areas, the inertial measurement unit (IMU) is used to estimate the location, but without the satellite connection it is more uncertain.
Some of the positioning error due to the missing satellite connection can be corrected in the post-processing phase. It is still important to plan the survey so that the route minimizes the shadows.
2 Insufficient SVP data
Sound velocity in the water is affected by the physical features of the water body. The most important feature is temperature; 1˚C change in water temperature causes 4 m/sec change in velocity. Salinity and pressure also have an effect to velocity.
Sound velocity profiling (SVP) is used to determine the sound velocity at the current time and place, allowing the correction of the sonar data accordingly. It is important to check the SVP data regularly. The right frequency depends on the environment and weather; for example, on sunny days the water column can heat up quickly, so SVP should be measured more frequently. Currents can also affect the quality of the water.
3 Vegetation, objects, bubbles
Sonar scanning uses acoustic pulses to create the point cloud of the surrounding environment. Besides the surveyed object, the water column has many kinds of error sources reflecting the sound, like floating vegetation (or fish), suspended sediment or bubbles.
Make sure you follow the survey from the screen in order to spot all the possible error sources and, if possible, take another survey line or otherwise minimize the disturbance. All of it cannot be erased, so diligent post-processing and point cloud cleaning fixes the remaining errors.
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