Technology Forum - LiDAR

Martin Pfennigbauer
Director - Research &
Intellectual Property
RIEGL Laser Measurement
Systems, Austria

Martin Pfennigbauer holds a Dipl.-Ing. Degree and a PhD from Vienna University of Technology. From 2000 to 2005 he was working as assistant professor at the Institute of Communications and Radio-Frequency Engineering, focusing on free-space optical intersatellite communication and quantum communication. Since 2005 he is with RIEGL Laser Measurement Systems, presently as Director, Research & Intellectual Property.

High-resolution hydrographic laser scanning with online waveform processing
Besides the established bathymetric airborne laser scanners with high penetration but low resolution there is a new class of airborne laser scanners dedicated for joint topographic and bathymetric surveying. With the RIEGL VQ-820-G we introduced an instrument of this class with exceptional high measurement rate of 200 kHz and high spatial resolution due to a narrow beam and short laser pulse duration. As a novelty in this field the VQ-820-G not only records the full waveform of the echo data for subsequent analysis but also performs online waveform processing delivering highly accurate spatial information in real time. The laser scanner features a slim design with a total weight of about 20 kg, operating at a single wavelength and capturing the data on a laptop computer or directly to a USB drive.We give insights into the instrument online waveform processing technique and present results from various field tests in different areas.

Dr. Rinaldo Wurglitsch
Manager Software Develoment
IQSOFT Gesellschaft für

Dr. Rinaldo Wurglitsch is the leader for the software development at IQSOFT. His main focus are on research projects together with industrial partner and research partners in the area of Geo Business Applications, specially for improvement LIDAR data storage and performance.Study in Vienna University of Economics and Business Administration.He published different papers and wrote the book “Time Related Informations†about data storage and rational and object rational databases.

Streamline your process from LIDAR to GIS Subtitle: The evolution of LIDAR data from file system to very large database
The presentation demonstrates a new and easy approach to increase efficiency and transparency of LIDAR delivery, storage, analysis, visualization and object recognition. The solution is in action on customer site with currently more than 10TB of data (8 billion points). Airborne Laser Scanning (ALS) produces vast amounts of data, which must be efficiently stored, processed and retrieved “ accompanied by the data lifecycle management including metadata. Conventional methods mostly use file systems for storage resulting in a lack of data management and performance bottlenecks.The main focus of this presentation is on ease of management, performance, provisioning, quality assurance and data security associated with spatial data. The core of the solution is technically based on the “Oracle® Spatial” database product, which is used to store and retrieve spatial data.The data resulting from ALS missions and their descriptive ISO compliant metadata are accumulated in a XML capable database and published by Catalogue Service (CSW) for disposal to processing.Processing the ALS data files leads to structured, geo-referenced and classified point clouds. Aerial images are also stored in database as georaster objects. Serve as base for extracting color information to enrich the point cloud data.Our solution facilitates a random access to point clouds and aerial images to serve 3D-visualizations, spatial analysis and object recognition processes. This can be controlled and monitored comfortably by an interactive graphical interface.

Martin Isenburg
Owner and Scientist

Dr. Isenburg received his MSc in 1999 from the University of British Columbia in Vancouver, Canada and his PhD in 2004 from the University of North Carolina at Chapel Hill, USA “ both in Computer Science.Dr. Isenburg provides a popular suite of LiDAR processing software called LAStools. He is involved in shaping the LAS exchange standard, in promoting the free, open-source LASzip compressor, and in designing the upcoming PulseWaves specification.

PulseWaves - A first glimpse at the open data exchange format for full waveform LiDAR data
Currently researchers and scientists that are working on cutting edge LiDAR research by trying to make use of the full laser waveform data that modern scanners digitize are experiencing severe difficulties as there is no established standard format for storing and exchanging full waveform LiDAR data. Hence researchers not only spend a lot of time converting between proprietary vendor formats and verbose ASCII representations, but they can also not easily share their data or their software with others to reproduce and utilize the scientific results. With the upcoming PulseWaves format we hope to change this.The PulseWaves standard is an open, community-created, vendor-neutral data exchange format for geo-referenced full waveforms LiDAR data. The PulseWaves format is to essentially fullfill the same role for full waveform LiDAR that the ASPRS LAS format fulfills for discrete return LiDAR.The format was developed over the course of 2012 in an open discussion involving hardware vendors, researchers, and various agencies. The format is LAS compatible but instead of storing discrete returns, it stores geo-referenced laser pulses and their associated waveforms. It is meant to cater both topographic and bathymetric LiDAR.Especially emerging applications in climate change and carbon research will find useful applications of full waveform data for biomass calculations and forest inventories.In my talk I will give an overview about the most recent specification, the available open source API, the state of support by vendors, and the available software for processing the full waveform data in PulseWaves format.

Dr. Tim Tutenel
Delft University of Technology
The Netherlands

Interactive Visual Analysis of Flood Scenarios Using Large-Scale LiDAR Point Clouds
The visualisation of large-scale geospatial data is a demanding challenge that find applications in many fields, including climatology and hydrology. In this work, we are focusing on the visual analysis of flooding scenarios. We propose a novel solution that is able to visualise coloured LiDAR data of several hundred square kilometres including high-resolution flood simulation results.One key contribution is a level-of-detail rendering algorithm that enables us to handle Terabytes of data interactively. Furthermore, we present a novel algorithm to annotate (colour entire regions or highlight routes), or modify (i.e. clip, cut, raise/lower) the unordered LiDAR point set on-the-fly with flexible 2D geographic metadata (i.e., polygons, paths and landmarks). The principles of our technique are to make use of hierarchical structures on the metadata and a new quadtree-based GPU traversal algorithm. We examined three test cases and show that combining the flood simulation with different topographic shading techniques facilitates drawing conclusions about water flow, security measures, and evacuation planning.
Dr Thomas Bahr
Senior Consultant
Exelis Visual Information Solutions

Automatic Extraction of 3D Information from LiDAR Data
Professionals across industries use LiDAR data to cover the increasing demands in urban planning and management sectors. Although, LiDAR systems provide detailed valuable geometric information, they still require extensive interpretation of their data for object recognition and extraction to harness it for geospatial analysis projects. Examples are studies for urban development, solar and wind power plants, right-of-way analyses, and forest inventories. In this paper we show a new workflow to transform point cloud data and extract essential information for city management applications without expert knowledge. The most commonly used data formats such as LAS, GeoTIFF and SHP are supported, to rapidly access and ingest the LiDAR data. Feature identification can be performed on an entire point cloud scene, a user defined subset of a scene, or multiple LAS files simultaneously, providing accurate information in a fraction of time. Multithreading technology is used to quickly find features of interest such as building footprints, trees, power lines, and power poles, through either an automated feature identification tool or by manually identifying features in a photorealistic 3D visualization. The resulting products can be imported as raster or vector layers, useful for performing additional geospatial analysis, sharing with colleagues for verification studies, or inclusion in GIS for mapping applications.