ORIENTATION ANDPROCESSING OF AIRBORNE LASER SCANNING DATA (OPALS)- CONCEPT AND FIRST RESULTS OF A COMPREHENSIVE ALS SOFTWARE Gottfried Mandlburger a , Johannes Otepka ab , Wilfried Karel ab , Wolfgang Wagner ab and Norbert Pfeifer a a Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, b Christian Doppler Laboratory “Spatial Data from Laser Scanning and Remote Sensing” Gusshausstrasse 27-29/E122, 1040, Vienna, Austria, gm{jo,wk,ww,np}@ipf.tuwien.ac.at Commission III/2 KEY WORDS: LIDAR, ALS processing software, automatic workflow, data administration ABSTRACT: Since the mid-1990s, the Institute of Photogrammetry and Remote Sensing (I.P.F.) is engaged in Airborne Laser Scanning (ALS) in research and development. Scientific contributions have been made in a wide field of related topics like full waveform signal analysis, georeferencing and filtering of ALS point clouds, automatic breakline modelling, DTM generation, quality control, etc. Apart from that, converting research ideas into software solutions is an enduring tradition at the I.P.F. for which the DTM program SCOP++ is an example. Partial solutions of ALS-related issues have been implemented in SCOP++, but a complete processing chain is missing, as the development cycles for this highly interactive program are long. Thus, the objectives of the new OPALS program system are to provide a complete processing chain for large ALS projects and to shorten development cycles significantly. OPALS is designed as a collection of small well-defined modules which can be accessed in three different ways: (i) from DOS/Unix shells as executables, (ii) from Python shells as full-featured, platform-independent Python modules or (iii) from custom C++ programs by dynamic linkage (DLL) for fastest module calls. Sophisticated custom processing chains can be established by freely combining the OPALS modules using shell or Python scripts. To reduce development times, a lightweight framework is introduced. It allows non-expert programmers to implement their own modules, concentrating on the implementation of their latest research outcomes, whereas the framework deals with general issues like validation of user inputs, error handling, logging, etc. In this way, new research outcomes get available more rapidly for the scientific community. OPALS does not only target researchers, but also ALS service providers dealing with large ALS projects. Efficient data handling is a precondition for this purpose. Thus, the OPALS data manager (ODM) is one of the core units, allowing administration of data volumes in the order of 10 9 points. The ODM acts as spatial cache and provides high-performance spatial queries. Currently, a quality control package (opalsQC) is in progress and first results (point density maps, strip difference maps, 3D-strip shifts) are presented in the paper. 1 INTRODUCTION Airborne laser scanning (ALS) has been a main research topic at the Institute of Photogrammetry and Remote Sensing (I.P.F.) for more than a decade. Scientific contributions have been made in a wide field of ALS-related topics like filtering of point clouds (Kraus and Pfeifer, 1998), derivation of digital terrain models (Kraus and Pfeifer, 2001), (Pfeifer et al., 2001), georeferencing of flight strips (Kager, 2004), quality control of ALS data (Ressl et al., 2008), automatic modelling of breaklines (Briese, 2004), and many fields of application like building modelling (Rotten- steiner and Briese, 2002), (Dorninger and Pfeifer, 2008), hy- draulic modelling (Mandlburger et al., 2008), forestry (Hollaus et al., 2007) and geomorphology (Sz´ ekely et al., 2008). Currently, the research activities also focus on full waveform laser scanning (Wagner et al., 2004) comprising the decomposition and calibra- tion of the laser echoes (Wagner et al., 2006), as well as the im- provement of digital terrain models (DTM) using additional full waveform echo attributes (Doneus and Briese, 2006), (Mandl- burger et al., 2007). ALS is a highly automated data capturing technique. Today, the sensor observations from global navigation satellite systems (GN- SS), from inertial measurement units (IMU) and laser scanners are processed online and are simultaneously stored on hard disc arrays even during the flight mission. Thus, a first inspection of the raw point cloud can be done while still airborne. However, more sophisticated data processing is typically done in postpro- cessing back in the office. The processing chain comprises anal- ysis of the full waveform signal, direct georeferencing, strip-wise checking of relative and absolute accuracy of the point cloud, im- provement of the georeferencing if necessary, data organisation and administration, and finally, filtering of the point cloud, and derivation of digital terrain or other models. In this paper we present a comprehensive framework for these steps. While rely- ing on the algorithms for data processing mentioned above, espe- cially data administration in suitable structures is a challenging task. Another question is at which stages quality control shall be incorporated into the process. The article is structured as follows. Section 2 describes a best practice workflow for processing ALS projects representing the basis for our new OPALS software. In section 3, the general concepts of OPALS are highlighted, and section 4 describes an example module in more detail. The current status is presented in section 5, and the article concludes with the major findings and addresses future work in the final section 6. 2 ALS DATA PROCESSING Fig. 1 shows the proposed processing chain based on full wave- form ALS data. The first section deals with the derivation of the 3D point cloud starting with the raw observations. On the one hand, the flight path is determined combining the observations of In: Bretar F, Pierrot-Deseilligny M, Vosselman G (Eds) Laser scanning 2009, IAPRS, Vol. XXXVIII, Part 3/W8 – Paris, France, September 1-2, 2009 Contents Keyword index Author index 55