Chapter Overview
HALE UAS (high altitude,
2.6 TLS data acquisition and initial processing
2.6.1 Background
Surveys conducted using a terrestrial laser scanner (TLS) were conducted at Coledale Beck, for comparison with the results of the UAS-SfM approach for quantifying topography (Chapter 3) and substrate size (Chapter 4). This work formed part of a collaboration with colleagues from Bath Spa University (BSU).
Data acquisition and initial processing of the TLS data, including merging scans, georeferencing, clipping data to the area of interest and removal of data spikes, were undertaken by colleagues from BSU (see Appendix A for division of work). The output of this process was a dense point cloud, on which the main analyses were then conducted. The TLS used is a Leica ScanStation C10 (Figure 2.19), a green wavelength (532nm) scanner with a 300m range, 360o by 270o field of view and scan speed of up to 50,000 points per second.
Figure 2.19. Leica ScanStation C10 terrestrial laser scanner (left) and Leica reflective targets (right), in use at Coledale Beck, July 2013.
Chapter 2 – Methods 65 2.6.2 Field set-up
Prior to data collection, a site assessment was undertaken to establish the optimal locations for scan stations and scan targets to ensure sufficient coverage of the c.120m reach at Coledale Beck. Elevated scan station locations were chosen to ensure higher angles of incidence and to reduce shadowing. Six reflective Leica targets were positioned at visible locations within the area of interest (Figure 2.20) and care was taken to ensure they covered the range of elevations present at the site. Each of these targets is mounted on a tripod (Figure 2.19) which was centred and levelled using an optical plummet. The targets positions were marked with a wooden stake and survey marker (Figure 2.21), and later recorded using a Leica GPS1200 dGPS and post-processed using RINEX data.
2.6.3 Data acquisition
Prior to the scanning process, the tripod-mounted Leica ScanStation C10 laser scanner (Figure 2.19) was centred and levelled at each scan position using a laser plummet, spirit level and dual access compensator. As for the targets, each scan position was marked with a wooden stake and survey marker (Figure 2.21), and later recorded using a Leica GPS1200 dGPS and post-processed using RINEX data. The reflective targets were tilted and rotated relative to the scanner position and their positions recorded by focussed, high resolution scans which were stored in the scanner memory and later used to assist accurate co-registration of the main point clouds. The scanner was then used to acquire high resolution laser scans (defined as 5cm resolution at 100m range) from eight different scan station positions. Each scan took approximately 45 minutes to acquire, with c.10-15 minutes set-up time between scans. In total, the TLS data acquisition took approximately nine hours.
2.6.4 Initial data processing
Initial processing of the dense TLS point cloud was undertaken entirely within the Cyclone software (Leica Geosystems HDS, LLC). This comprised co-registering of the eight separate scans using the known locations of each of the six reflective targets. During this process, those targets producing the greatest errors in the applied registration were removed (T4 and T6 – see TLS error diagnostics in Appendix A). The known positions of the remaining targets and scan stations acquired using dGPS were then used to georeference the merged scan to British National Grid co-ordinates. The full error diagnostics for this registration are provided in
Chapter 2 – Methods 66 Appendix A. The resulting overall mean absolute error was 0.009m, and average error in the vertical dimension was 0.026m.
Figure 2.20. Location of TLS targets and scan station positions at Coledale Beck, July 2013.
Figure 2.21. Example of a marker established at Coledale Beck and used as TLS reflective target position markers and TLS scan station position markers.
Chapter 2 – Methods 67 Manual editing of the TLS point cloud was undertaken to remove clearly erroneous data spikes (due to sensor saturation by sunlight) and then to clip the dataset to match the approximate extent of the UAS survey. The resulting point cloud was exported from Cyclone as a PTS file comprising c. 165 million points with a file size of c. 9GB.
The point cloud was rasterised using code written in-house (R. Austrums 2014). The resulting TLS DEM had a spatial resolution of 0.013m. This pixel size was selected as a compromise between achieving the highest spatial resolution and minimising holes in the DEM in areas of sparser point density. This procedure also included a small amount of interpolation conducted using an iterative gap filling process. This process aims to fill some of the gaps (i.e. empty cells) in the DEM by interpolating the elevation data from those cells which surround the gaps and do contain data. This process is conducted in stages, or ‘iterations’. For each iteration (of a total of ten), empty cells were given a value of the mean of all neighbouring cells, where the number of neighbouring cells totalled four or more. Whilst in theory this could result in interpolation over distances of up to 0.13m, in reality this interpolation rarely extended further than 0.05m and was not found to adversely affect subsequent analyses carried out on the TLS DEM. Chapters 3 and 4 describe the subsequent use of the TLS DEM and point cloud for quantifying fluvial topography and substrate size.
2.7 References
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Chapter 3 – Topography 69