Data infrastructure for multitemporal airborne LiDAR point cloud analysis – Examples from physical geography in high mountain environments

• Presentation of a database as management system for multitemporal LiDAR datasets.
• Description of a 10 year series with more than 20 airborne LiDAR campaigns in an alpine environment.
• Advantages of the database management system for multitemporal analysis.

The application of multi-temporal topographic LiDAR data has become a standard for many mapping and monitoring applications in man-made and natural environments. With increasing availability of area-wide, high-resolution, multi-temporal datasets and the increasing interest in working with the original measured 3D topographic LiDAR point clouds, challenges regarding optimal data storage and management are gaining in importance. During the last decade, an unique LiDAR dataset, consisting of over 30 flight campaigns covering different areas in western Austria and northern Italy, has been acquired with the purpose to analyse surface changes in high mountain environments. The datasets from each flight campaign are stored and managed in a LiDAR specific information system (LIS, Laserdata Information System), which has a client–server architecture and a spatial relational database as a core. The system is integrated into an open source Geographical Information System, which allows a seamless integration into operational spatial data processing and analysis workflows. It enables multi-user access to 3D point cloud data and additional attributes, such as intensity, return number, global positioning system time, flight path trajectory information and fullwaveform attributes if available. In this paper we describe the available dataset, the approach to 3D point cloud storage and management and the structure of the database. The value of direct access to the stored 3D point cloud data is assessed as well as the importance of storing point cloud attributes. A further focus lies on the importance of the data management and infrastructure for the analysis of large areas and long time series of topographic LiDAR data.