Design and evaluation of a full-wave surface and bottom-detection algorithm for LiDAR bathymetry of very shallow waters

Abstract

Airborne Laser Bathymetry (ALB) is an attractive technology for the measurement of shallow water bodies because of the high acquisition rate and high point densities that can be achieved. Of special interest is the application of ALB in non-navigable areas where the only alternatives are conventional terrestrial surveying by wading with a pole, multi-media photogrammetry, or spectrally based depth retrieval. The challenge for laser based approaches in such very shallow waters (< 2 m) is the difficulty of discriminating between echoes from the surface and the bottom. This work presents an algorithm for the detection of surface, volume, and bottom (SVB) designed to meet this challenge while requiring only a single wavelength (532 nm) sensor. The accuracy of the algorithm is cross validated against reference measurements obtained from terrestrial survey with a total station and shows negligible bias and virtually no depth dependence for the experimental dataset.

Concept and Performance Evaluation of a Novel UAV-Borne Topo-Bathymetric LiDAR Sensor

“…Beyond the pure sensor settings, an additional increase of depth performance is expected via sophisticated waveform processing. [81] reported an increased areal coverage when employing a surface-volume-bottom based exponential decomposition approach, in both very shallow and deeper water areas. [5,82] use waveform stacking, i.e., averaging of neighboring waveforms, to enhance ALB depth performance reporting an increase of 30%.…”

DepthLearn: Learning to Correct the Refraction on Point Clouds Derived from Aerial Imagery for Accurate Dense Shallow Water Bathymetry Based on SVMs-Fusion with LiDAR Point Clouds

“…However, nowadays, this color information seems to be very important for achieving reliable results from many machine learning and deep learning classification approaches. Moreover, LiDAR data in the very shallow nearshore zone (<2 m depth) suffer from the difficulty of extraction of the surface and bottom positions, which are typically mixed in the green LiDAR signal [15]; however, recent approaches [16] show promise toward meeting this challenge. On the contrary, although image-based point clouds, generated through SfM-MVS processes, have color information, they suffer from the refraction effect described in 1.1.…”

Nearshore Sandbar Classification of Sabaudia (Italy) with LiDAR Data: The FHyL Approach

“…In this context the airborne LiDAR (light detection and ranging) technology is considered a very powerful tool for beach monitoring and investigation, since it allows collecting data over a short time frame, providing a full overview at a larger scale with good spatial and vertical accuracy [15,16]. The LiDAR technology is a respectable support tool for the morphological characterization in shallow water (less than 1 m depth; [17][18][19]). LiDAR system is a scanner that deflects a laser beam across the flight line and detects its reflection, so that a swath of ground along the flight line is sampled point wise.…”

“…LiDAR system is a scanner that deflects a laser beam across the flight line and detects its reflection, so that a swath of ground along the flight line is sampled point wise. The production of a DSM (digital surface model) and DTM (digital terrain model) on a wide scale range, regardless of the site characteristics, shows that laser altimetry technology is spreading through the use of LiDAR bathymetric airborne [16][17][18][19].…”