## 2 Materials and Methods
### Data Processing  
#### 2.3.1 LiDAR Point-Cloud Processing  
The raw LiDAR data were pre-processed using LiGeoreference software. First, the original trajectory was segmented. Subsequently, the acquired images and GNSS base station data were added to process and solve. Lastly, the calculated point-cloud data were colored, and 36 bands were obtained.  
The LiDAR point-cloud obtained by the solution was further processed in accordance with the same processing flow (e.g., removing repeated data between flight bands, denoising, filtering, and extracting ground points). The raw data were denoised using a statistical outlier detection method that identified outliers by determining whether the distance between a point and its \(k\) neighboring points exceeded a threshold of _avg. + std_. (_avg._ and _std._ represent the average and standard deviation of distances between points and their \(k\) neighboring points, respectively) [36]. The ground points were extracted using the improved progressive TIN densification (IPTD) algorithm proposed by [PERSON], et al. [37]. Figure 3 presents the LiDAR data processing flow in the black box.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**UAV Specifications** & \multicolumn{2}{c}{**Airborne LiDAR Specifications**} & \multicolumn{2}{c}{**Camera Specifications**} \\ \hline Aircraft & M300 RTK & LiDAR system & Livox Avia & \\ Weight & 6300 g & Laser wavelength & 905 nm & Sensor & Sony A5100 \\ Max flight speed & 50 km/h (Positioning) & Laser pulse & 240 kHz & \\  & 58 km/h (Attitude) & repetition rate & & Sensor format & 23.5 \(\times\) 15.6 mm \\ Max flight time & 55 min & Maximum echo & 3 & \\ Max take-off & 5000 m & Maximum scan & 720,000 & \\ altitude & & speed & points/second & Focal length & 16 mm \\ Satellite & & Satellite & GLONASS + & \\ positioning & BeiDou + Galileo & positioning & BeiDou + Galileo & \\ GNSS positioning & 1 cm + 1 ppm & Field of view & 70.4\({}^{\circ}\)(Horizontal) & Image & \\ accuracy & (Horizontal) & & 4.5\({}^{\circ}\)(Vertical) & Image & 6000 \(\times\) 4000 \\ (RTK Fixed) & 1.5 cm + 1 ppm (Vertical) & Scan pattern & Repeat scan & resolution & \\ \hline \hline \end{tabular}
\end{table}
Table 1: The UAV flight platform, LiDAR system, and digital camera parameters.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**UAV Flight Parameters** & \multicolumn{2}{c}{**LiDAR Data**} & \multicolumn{2}{c}{**Image Data**} \\ \hline Flight altitude & 100 m & \begin{tabular}{c} Number of \\ scanning \\ routes \\ \end{tabular} & 36 & \begin{tabular}{c} Number of \\ images \\ \end{tabular} & 2240 \\ Ground Sampling & 2.34 cm/px & Mean density of points & 213.82 points/m\({}^{2}\) & \begin{tabular}{c} Image \\ forward \\ overlap \\ \end{tabular} & 90\% \\ \
\begin{tabular}{c} 35\% \\ \end{tabular} & & & \\ Camera angle & \(-90^{\circ}\) & Number of points & 3,258,544,456 &
\begin{tabular}{c} Image side \\ overlap \\ \end{tabular} & 80\% \\ Flight time & 1 h 48 min & & points & \\ \hline \hline \end{tabular}
\end{table}
Table 2: The UAV flight parameters and collected data information statistics.  
In ArcGIS 10.7, the ground point-cloud was interpolated using the inverse distance weight interpolation (IDW) [38,39] method to obtain a DEM with a resolution of 0.2 m. Furthermore, the DEM's elevation accuracy was checked. The mean elevation deviation reached 3.5 cm, the standard deviation was 4.5 cm, and the root mean square error was 4.4 cm.