Unlocking the Characteristics of Bathymetric LiDAR Sensors

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It’s always tricky making detailed comparisons between different LiDAR sensors and technologies. Technical specifications often list different parameters, and even when they are the same, life is made more difficult by the use of different units.

For the first time we have a comparison table (see Table 1) listing the key specifications of the new bathymetric LiDAR sensors. The table goes some way to providing an insight into the nuances of each sensor, including previously unlisted specifications, such as laser energy per pulse.

The table divides the sensors up into the traditional bathymetric LiDAR sensors, and topo-bathy sensors. The new topo-bathy LiDAR sensors bridge the divide between topographic and bathymetric LiDAR. The early EAARL sensor was the first of these beginning operations in 2001. Since then new sensors have been developed to efficiently measure both topographic and shallow bathymetric elevations.

It should be noted that all the LiDAR systems listed can measure both topographic data and bathymetry. The topographic data gathered from a traditional bathymetric LiDAR system tends to be of a lower density compared to that provided by a topo-bathy LiDAR sensor. The topo-bathy LiDAR sensors have a lower laser power, narrower beam, more frequent measurements and a smaller receiver field-of-view (FOV) (Dewberry 2012, Wright and Brock 2002). The HawkEye III system tends to cover both bases by having multiple lasers.

One characteristic of interest are the scan patterns which are shown diagrammatically in the table. Some of the scanners are able to look forward and backward, increasing the number of times an area is sampled; although, this pattern does oversample the edges whilst under sampling the central part of the scan. This is demonstrated in Figure 1 by the AHAB Chiroptera and HawkEye III sensors.

Figure 2 demonstrates an example where multiple looks are created by two bathymetric LiDAR systems installed in an aircraft. In this example Fugro LADS are able to fly the LADS Mk3 and Riegl VQ-820-G sensors in the same aircraft. The Riegl sensor is directed forward in this setup; however, it can also be configured to look backward.

Another interesting characteristic in the table is the laser energy per pulse. Although there are other factors involved, such as the receiver telescope area and FOV, the laser power combined with the pulse duration can be correlated to the depth penetration. The downside of higher laser energy per pulse is that the measurement frequency is generally lower than those systems with less energy per pulse. The main factor causing this is the limited energy per density dictated by the eye safety standard. The lower energy systems, like the Riegl VQ-820-G, have a much higher measurement frequency.

It is the measurement frequency which sets the topo-bathy LiDAR sensors apart from the traditional bathymetric LiDAR sensors. The high measurement frequency of topo-bathy sensors results in a closer point spacing, however, in order to obtain the high measurement frequency the depth penetration is sacrificed. It should be noted that higher measurement frequencies becomes more superfluous as the depth increases. This is due to the unknown beam refraction. Therefore, the horizontal location and shape of each footprint is much less certain as a function of depth.

The maximum water depths listed by each manufacturer only tend to be reached in ideal conditions. The typical maximum water depths achieved in Australia and the Pacific tend to be reduced, mainly dependent upon the turbidity and seafloor bottom type. A general comparison in the table is provided against the Secchi depth; the Secchi depth being a simple groundbased measurement of water clarity.

One characteristic which is difficult to measure is the LiDAR footprint diameter due to the laser beam lacking a sharp edge. The 1/e2 width is used in this instance to define the nominal LiDAR footprint diameter. This measurement is the distance across the footprint between points which have an intensity equal to 13.5% of the maximum intensity within the footprint (Paschotta 2013). The sensors with higher laser energy per pulse tend to have a larger footprint.

In summary, it would be perilous to rate the various LiDAR sensors as better or worse, as each is unique in terms of bathymetry quality and cost. It is important to realise that all the sensors have unique capabilities, including those characteristics not listed in the table, such as receiver aperture area, and their individual capabilities i.e. HawkEye’s ability to divide its receiver into multiple sections effectively reduces its footprint size; CZMIL’s ability to divide it’s backscatter into seven small FOV segments and one large for deep water; and EAARL-B transmitting three beams and receiving them in three small FOV beams and one large one for deeper water.

It is the complete sensor package which provides the advantages and disadvantages. A decision of which sensor to use will be dependent upon the survey area, environment, project requirements and sensor availability. The most common aspects which tend to affect the choice of sensor relate to the maximum and minimum depths that need to be achieved, the level of detail inside the survey, and the products to be derived from the LiDAR data.

It is hoped that by providing an overview of the main characteristics of each LiDAR sensor, you will be in a more informed position at the start of your next bathymetry project.

The author wishes to thank Hugh Parker and Mark Penley Fugro LADS, David Collison and Joong Yong Park Optech Inc, Swante Welander Airborne Hydrography (AHAB), Martin Pfennigbauer Riegl, and John Brock and Charles W Wright the U.S. Geological Survey (USGS) for their contribution and providing the specifications of their LiDAR sensors.

Dr Nathan Quadros completed his Ph.D. in 2008 investigating issues with airborne LiDAR in the coastal zone. He is currently delivering bathymetric and topographic LiDAR to Tonga, PNG, Vanuatu and Samoa, along with the training and capacity building for these country governments to use the data.

A 935Kb PDF of this article as it appeared in the magazine complete with images is available by clicking HERE