Due to a large number of available Airborne Lidar Bathymetry (ALB) survey datasets and scheduled future surveys,
there is a growing need from coastal mapping communities to estimate the accuracy of ALB as a function of the survey
system and environmental conditions. Knowledge of ALB accuracy can also be used to evaluate the quality of products
derived from ALB surveying. This paper presents theoretical and experimental results focused on the relationship
between sea surface conditions and the accuracy of ALB measurements. The simulated environmental conditions were
defined according to the typical conditions under which successful ALB surveys can be conducted. The theoretical part
of the research included simulations, where the ray-path geometry of the laser beam was monitored below the water
surface. Wave-tank experiments were conducted to support the simulations. A cross section of the laser beam was
monitored underwater using a green laser with and without wind-driven waves. The results of the study show that
capillary waves and small gravity waves distort the laser footprint. Because sea-state condition is related to wind at a
first-order approximation, it is possible to suggest wind speed thresholds for different ALB survey projects that vary in
accuracy requirements. If wind or wave information were collected during an ALB survey, then it is possible to evaluate
the change in accuracy of ALB survey due to different sea surface conditions.
In addition to the well-developed bathymetric LiDAR (Light Detecting and Ranging) remote sensing technique,
Airborne Hydrography AB (AHAB) has presented a new bathymetric LiDAR reflectance processing technique which
provides new applications of producing seafloor reflectance image, seafloor identification and classification. In the past
decade, HawkEye II bathymetric LiDAR systems produced by AHAB collected and processed over 100,000 square
kilometer LiDAR reflectance data in more than ten countries in Europe, America, Oceania, Indian Ocean and Asia. In
this paper, we introduce the background of bathymetry LiDAR, the algorithm and methods used in the bathymetric
LiDAR reflectance processing, the reflectance image and seafloor classification applications.
Today airborne LiDAR (Light Detection And Ranging) systems has gained acceptance as a powerful tool to rapidly
collect invaluable information to assess the impact from either natural disasters, such as hurricanes, earthquakes and
flooding, or human inflicted disasters such as terrorist/enemy activities.
Where satellite based imagery provides an excellent tool to remotely detect changes in the environment, the LiDAR
systems, being active remote sensors, provide an unsurpassed method to quantify these changes. The strength of the
active laser based systems is especially evident in areas covered by occluding vegetation or in the shallow coastal zone
as the laser can penetrate the vegetation or water body to unveil what is below.
The purpose of this paper is to address the task to survey complex areas with help of the state-of-the-art airborne LiDAR
systems and also discuss scenarios where the method is used today and where it may be used tomorrow.
Regardless if it is a post-hurricane survey or a preparation stage for a landing operation in unchartered waters, it is today
possible to collect, process and present a dense 3D model of the area of interest within just a few hours from deployment.
By utilizing the advancement in processing power and wireless network capabilities real-time presentation would be
Airborne depth sounding lidar has proven to be a valuable sensor for rapid and accurate sounding of shallow areas. The
received lidar pulse echo contains information of the sea floor depth, but also other data can be extracted. We currently
perform work on bottom classification and water turbidity estimation based on lidar data. In this paper we present the
theoretical background and experimental results on bottom classification. The algorithms are developed from simulations
and then tested on experimental data from the operational airborne lidar system Hawk Eye II. We compare the results to
field data taken from underwater video recordings. Our results indicate that bottom classification from airborne lidar data
can be made with high accuracy.