## 3 Methods
### Test Field and Reference Data  
Test field was established in the Evo study area located in southern Finland (61\({}^{\circ}\)19\({}^{\prime}\) N, 25\({}^{\circ}\)11\({}^{\prime}\) E). The area lies within the southern boreal forest zone and comprises approximately 2000 ha of mainly managed boreal forest. Scots pine and Norway spruce are the dominant tree species and the average stand size in the area is slightly less than one hectare. The elevation of the area varies from 125 to 185 m above sea level. In the first phase, an ATV route 800 m in length was laid out to cross four forest stands. Then 224 trees were marked on either side of the route (Figure 2). The locations of the trees were measured to the center of the stem at breast height (1.3 m above ground level) using a Trimble 5602 DR200\({}^{+}\) total station. The total-station orientations were determined using ground-control points measured in open areas around  
Figure 1: An ATV with global satellite navigation systems (GNSS) antennas and receivers, inertial measurement unit (IMU) and laser scanner equipment mounted on it for the purposes of the study. the test site using a VRS-GPS device. The measured trees comprised the reference object network. The location accuracy of the reference targets was estimated to be better than 10 cm in 2D (East-North). The route was driven two times to acquire data with different satellite geometry (Table 1). The average driving speed of the ATV was about 4 km/h. The reference trajectory and laser scanning were collected using a MLS system ROAMER R2 of the Finnish Geospatial Research Institute, FGI. The ROAMER R2 consists of a NovAtel SPAN navigation system, which includes a GNSS receiver and an IMU, and an ultra-high speed phase-shift laser scanner. All sensors are mounted on a rigid platform. Tables 2 and 3 list the technical specifications of the navigation system and the laser scanner. The reference trajectory was computed using the Waypoint Inertial Explorer software. The reference GNSS data were downloaded from the Trimnet GNSS service to a virtual reference station close to the test site. The collected laser point cloud was georeferenced to local coordinate system by combining the laser scanner data with the trajectory and synchronization data using FGI software developed in-house. \begin{table}
\begin{tabular}{c c c} \hline  & _Trajectory 1_ & _Trajectory 2_ \\ \hline Date & 30 October 2014 & 30 October 2014 \\ Start and end time (UTC+3) & 12:01:32 p.m.–12:15:14 p.m. & 2:26:04 p.m.–2:37:33 p.m. \\ No. of satellites, cut-off angle 15\({}^{\circ}\) a & 13 (6 GPS + 7 GLO) & 18 (10 GPS + 9 GLO) \\ GDOP, cut-off angle 15\({}^{\circ}\) a & 2.8 & 1.9 \\ Ionosphere Total Electron Content a & 30 (low) & 35 (low) \\ Average speed & 3.5 km/h & 4.2 km/h \\ \hline \end{tabular}  
*: Trimble Navigation Ltd., Sunnyvale, CA, USA, [[http://www.trimble.com](http://www.trimble.com)]([http://www.trimble.com](http://www.trimble.com)).  
\end{table} 
Table 1: Reference trajectory acquisition. Figure 2: The reference trajectory (red) and the reference trees (green). Background orthoimage: National Land Survey Finland 2012. The reference positions of the trees were measured in the field at breast height, which was determined as 1.3 m above average ground level around the tree. Accordingly, the point cloud was classified for points on the ground and for points at 1.3 m above the ground. The ground-based points were classified using the ground classification algorithm in the TerraScan software (Terrasolid Ltd., Helsinki, Finland). This algorithm is based on the triangulated irregular network (TIN) approach using local low points as the initial points and then starts to grow a network of triangles according to the given parameters (for more details, see [37]). In this study, the parameters were optimized to produce a surface model that is sufficiently dense and follows also the smaller terrain variations, and yet excludes extreme noise.