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.
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.
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