Beyond Standard Workflows: Accessing additional water body information from full-waveform LiDAR bathymetry data

This tutorial focuses on novel approaches to analyze full-waveform LiDAR bathymetry data. Standard methods often reach their limits, especially with regard to the evaluable water depth and the derived information content. The tutorial provides an introduction to novel processing methods that address these challenges and provide additional water body information.
In the theoretical part of the tutorial, full-waveform stacking approaches based on the analysis of adjacent waveforms will be introduced. These methods enable the identification of water bottom points in areas where conventional workflows encounter limitations. Additionally, a technique for deriving information on water turbidity will be presented. Participants will gain a comprehensive understanding of the underlying concepts and their potential applications.
In the practical part, a data set of an alpine mountain lake will be used to test the presented methods hands-on. The participants will:

• analyze individual full-waveforms from different areas of the water body to understand the challenges in full-waveform processing,
• process adjacent full-waveforms using the full-waveform stacking methods and investigate the impact of neighborhood choice on te detection of water bottom points,
• derive turbidity parameters from the stacked full-waveforms both manually and
  automatically.

This interactive tutorial offers participants the opportunity to directly apply the presented methods and to develop a better understanding of the potentials and challenges of full-waveform analysis in bathymetry. The tutorial is aimed at scientists, engineers and practitioners who deal with the analysis of LiDAR bathymetry data and want to expand their knowledge of innovative evaluation methods.

 

Terabytes on the Lap: Visual Analysis of Massively Large LIDAR Raw Data and Interactive Editing of Derived Big Point Clouds with HydroVish

The presentation outlines an end-to-end workflow for processing bathymetric LiDAR data using HydroVish, a custom software that handles all processing steps within a single environment. It emphasizes waveform processing techniques like Gaussian and Richardson-Lucy deconvolution, and highlights the use of MTA (Multiple Time Around) to handle complex signal returns. Classification of point clouds is achieved using a Random Forest model with multiple handcrafted features, trained on distinct datasets for sea, river, and mixed environments. Strip adjustment is rigorously optimized using ICP and the Ceres solver, correcting global and local trajectory parameters. Refraction of the water surface is also considered, as well as reliable surface mesh creation, and a dedicated quality management process is integrated, evaluating results through statistical analysis and meaningful TIFF images.

 

Through-water photogrammetry: Water depth ad river bottom topography from UAV images – The Pielach River research dataset, opens an external URL in a new window

In this tutorial, we demonstrate the fundamentals of through-water photogrammetry for obtaining water depth and river bottom topography from UAV images. Based on the “Pielach River research dataset October 2024 - Mapping shallow inland running waters with UAV-borne photo and laser bathymetry“ (Mandlburger et al., DOI: 10.48436/5xwsn-7qb10), we demonstrate the full processing pipeline from image orientation, geo-referencing, dense point cloud derivation, water surface level estimation, refraction correction, DTM generation, and water depth derivation based on photogrammetric standard software (Pix4Dmapper) and the scientific laser scanning and point cloud software OPALS (Orientation and Processing of Airborne Laser Scanning data).

This tutorial addresses scientists and practioners alike, and combines theory and (hands-on) examples, opens an external URL in a new window.

 

Laser derived water depths - From georeferenced point clouds to watercourse DTM with OPALS

With about a decade of experience in airborne data acquisition from UAVs, helicopters and fixed-wing aircraft, Skyability has collected a great variety of bathymetric LiDAR data. The aim of the tutorial is to demonstrate the entire laser bathymetry processing pipeline using LAStools and the scientific laser scanning software OPALS, developed at TU Wien. Starting with the georeferenced but otherwise raw point cloud, the individual processing steps include filtering of sporadic noise points, the derivation of a water surface model, runtime- and refraction correction of the underwater points, classification into ground and off-terrain points, interpolation of a Digital Terrain Model of the watercourse consisting of all ground points from the dry and submerged area, and finally the calculation of water depth maps. The tutorial introduces the entire workflow in comprehensive hands-on examples.

 

A deepdive into the World of RIEGL Lidar Bathymetry Systems and Software

With over 40 years of experience researching, developing, and producing laser rangefinders, distance meters, and scanners, RIEGL is a proven innovator in 3D technology.

Since 2011, RIEGL has also provided topo-bathymetric system models for integration with crewed fixed-wing aircraft and helicopters. The well-known strengths of RIEGL devices — high-resolution topographic measurement with high efficiency — are extended to enable seamless coverage of land and underwater areas.

This presentation will provide insight into latest sensor technology and software tools for bathymetric applications. We will examine the entire workflow, from project planning to the specifics of parameterizing RIEGL’s bathymetric sensors and the challenges of bathymetric laser scanning. Regarding post-processing, we will examine the ALB (Airborne Lidar Bathymetry) software suite, RiHYDRO, which supports data classification and the generation of water surface models and applies water refraction correction according to refraction indices. Additionally, we will provide background information on full waveform processing and waveform averaging, which can be applied to maximize depth penetration success.

 

Learning and teaching the underwater photogrammetry challenges with the POSER 3D simulation framework

POSER (an oPen sOurce Simulation platform for tEaching and tRaining underwater photogrammetry) is a 3D simulation framework developed within the ISPRS Educational and Capacity Building Initiative. It is built upon the open-source platform Blender and integrates realistic modelling of underwater physics, including light refraction, scattering, and absorption, to simulate faithful survey conditions. Although it is primarily designed to support the teaching and learning of underwater imaging principles, POSER has great potential also for research and experimentation. In this tutorial, participants will be introduced to the POSER framework to practice with crucial aspects of underwater photogrammetry and independent methods for the assessment of its accuracy potential. Ready-to-use application scenarios will be show-cased ranging different application fields, from marine ecology to archaeology and subsea metrology.