Feasibility of mobile laser scanning for mapping and monitoring a riverine environment

The detailed geometry of ground topography is needed for various environmental studies, including river dynamic studies (erosion/deposition), hydraulic modeling, interpreting fluvial geomorphology and habitat modeling. In recent years, mobile laser scanning (MLS) has provided an efficient and versatile method for collecting three-dimensional data for built and natural environments. MLS is a surveying technique that uses a laser beam for distance observations, global navigation satellite systems (GNSS) for determining the position and an accurate inertial measurement unit (IMU) for measuring the 3D orientation. The MLS system can be flexibility mounted on different vehicles for different purposes. Advances in technology in recent years have introduced lighter sensors, which have also made it possible to develop personal laser scanning (PLS) systems by mounting the sensors on a backpack. While ground topography mapping using MLS has mainly been discussed in the context of road modeling, the performance and usability of MLS have been lacking in geomorphological surveys and fluvial studies. In particular, a multitemporal MLS data collection yields a remarkable and highly detailed data source for analysing different natural processes. The multitemporal MLS surveys provide possible new applications for e.g. flood risk management, monitoring the health and the quality of city trees, conducting environmental impact assessments, updating the city maps and updating interior models. In this PhD thesis, the feasibility of MLS for mapping and monitoring a riverine environment was analysed. The MLS data were measured by mounting the sensors on a boat (BoMMS), cart and backpack. The assessment of digital terrain model (DTM) accuracy and the geometric quality of MLS point clouds and performance of BoMMS data for monitoring multitemporal topography and vegetation changes were likewise investigated. Automatic data processing methods were tested and presented for generating terrain and vegetation points from the BoMMS data. Moreover, the study demonstrated the integrated use of MLS and panoramic images for interpreting an MLS-based change detection model. The results indicate that MLS is an efficient method for improving the spatial and temporal coverage of high-resolution 3D environmental models. In particular, MLS provide a unique measuring perspective for complex environments. While the number of applications can be unlimited, it should be noted that high-performance MLS measurements require good satellite visibility, proper system calibration and reference control measurements.