Tomographic approaches for airborne lidar bathymetry data processing

机载激光雷达测深是一种激光扫描技术，用于测量有限浑浊浅水水域的水体底部地形。最近，由于新的传感器技术的出现，使得在水深测量数据采集方面能够有更高的空间分辨率，并且由于新的准则要求定期监测水体，这一专题变得具有相关性。激光雷达测深中的水下激光脉冲路径具有与水浊度相关的衰减特性，使数字化激光脉冲回波的信噪比恶化，从而阻碍了水体底点的探测。该提案旨在开发基于相邻数字化激光脉冲回波的层析表示的方法。在这些体素空间表示中，通过应用稳健的参数估计和三维滤波技术来提取一致的水体底部元素(而不是离散点)。因此，水体底部地形测量的精度和可靠性有望得到显著提高，从而扩大激光雷达水深测量的潜在深度范围。此外，应分析水柱中激光脉冲回波强度的衰减，目的是通过比较基于模型的衰减参数和测量的衰减参数来得出描述水浊度的参数。除了来自传统最先进的机载激光雷达测深系统的数据外，这项研究还将讨论所开发的方法对处理最近的单光子机载激光雷达系统数据的适用性。

Airborne Lidar Bathymetry is a laser scanning technique to measure waterbody bottom topography in shallow waterbodies with limited turbidity. The topic has recently gained relevance due to the advent of new sensor technologies allowing for much higher spatial resolution in bathymetry data capture and due to new guidelines demanding regular monitoring of waterbodies. The underwater laser pulse path in lidar bathymetry is characterized by a water turbidity dependent attenuation, deteriorating the signal-to-noise-ratio in the digitized laser pulse echo and thus hampering the detection of waterbody bottom points. The proposal aims at the development of methods, which are based on a tomographic representation of neighbouring digitized laser pulse echoes. In these voxel space representations, consistent waterbody bottom elements (rather than discrete points) are extracted by applying robust parameter estimation and 3D filtering techniques. As a result, a significant gain in precision and reliability of waterbody bottom topography measurement is expected, thus also increasing the potential depth range of lidar bathymetry. In addition, the decay of the laser pulse echo intensity in the water column shall be analysed with the goal of deriving parameters describing water turbidity by comparing model-based and measured decay parameters. Besides data from conventional state-of-the-art airborne lidar bathymetry systems, the research will also address the applicability of the developed methods to processing recent single photon airborne lidar system data.