# Fast and High Precise Spatial Documentation of Traffic Accident Site Using Only Low-Cost RPAS
## 2 Materials and Methods
### Proposed RPAS Method
\begin{table}
\begin{tabular}{c c} \hline
**Flight Parameters:** & **Camera Parameters:** \\ \hline Flight height: 10 m & Camera maker: Hasselblad \\ Size of area: 20 \(\times\) 25 m & Camera model: L1D-20c \\ Forward/side overlaps: 70/80\% & Camera angle: 90\({}^{\circ}\) (perpendicular to the ground) \\ Type of scan: Single grid & Still Image size: 5472 \(\times\) 3648 pixels \\ GSD: approx. 0.002 m & Resolution: 72 dpi \\ Speed: approx. 1 m\(\cdot\)s\({}^{-1}\) & F-stop: f/3.2 \\ Flight time (take-off and landing included): approx. 2 min & Exposure time: 1/200 s \\ Flight mode: manual & ISO: 100 \\ Number of acquired images: 27 & Camera trigger speed: approx. 3.5 s \\ \hline \end{tabular}
\end{table} 
Table 1: Flight and camera parameters (third flight). we used objects and points. To assess the accuracy inside and around the arranged traffic accident, we dislocated reference objects and points. We did subsequent processing completely with Agisoft Photoscan Professional (64-bit) version 1.4.4 [13]. To create a 3D model from sequences of 2D images, we used the structure from motion (SfM) method. Original images, without any transformation or correction, entered processing, as recommended by the software producer. The images' coordinates were acquired from an onboard GNSS receiver (GPS + GLONASS) and written into the images' exchangeable image file format (EXIF). These coordinates were further used for automatic georeferencing. After uploading the images, we followed four main steps. Camera calibration should precede all steps. The first step included images of aligning. We found key and tie points over all the images. The second step involved building a dense point cloud. During the third step, we created a meshed model from the dense point cloud. The fourth step included textured model building. After these steps, the model was ready for traffic accident site inspection and measurement. We tested several various settings. The following settings, shown in Table 2, gave the most appropriate results. Point cloud, 3D model, digital surface model (DSM), orthomosaic etc. could be exported and used in selected GIS software. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**1. Step** & **2. Step** & **3. Step** & **4. Step** \\ (Aligning Photos) & **(Building Dense Cloud)** & **(Building Mesh)** & **(Building Texture)** \\ \hline Accuracy—High & Quality—High & Surface type—Height field (2.5D) & Mapping mode—Generic \\ Key point limit—10,000 & Depth filtering—Mild & Source data—Dense cloud & Blending mode—Mosaic \\ Tie point limit—4000 & Calculate point & Face count—High & Hole filling—Enabled \\  & vertex—Enabled & & \\ x & x & Interpolation—Enabled & Ghosting filter—Enabled \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Agisoft Photoscan Professional (64-bit) version 1.4.4 settings. Figure 2: Overview of arranged traffic accident site with reference objects. A, B, C—vehicles; 1, 2, 3, 4, 8—reference objects with known dimensions; and 5, 6, 7—reference points for measurements. Green line represents third flight’s trajectory. The computational time was 14 min. The model was computed on a device with the following parameters: CPU--Intel Core i7-8750H, 2.20 GHz, 6 Cores, 12 Logical Processors; RAM--16 GB; GPU--nVidia GeForce GTX 1060 with Max-Q Design, 6 GB.