# Point Cloud Modeling ## **Point Cloud Modeling** ### **Add Mobile Laser Scanning** Get3D Mapper supports the addition of laser point cloud and track line data collected by mobile laser equipment. The software supports laser point cloud modeling alone and laser point cloud fusion modeling with photos. Support vehicle-mounted, airborne, backpack, and handheld laser point clouds. Laser point cloud supported formats: \*.las, \*.ptx, \*.pts, \*.e57. Trajectory line supported formats: \*.txt, \*csv. **1) Open the Add Mobile Laser Scanning interface**

**2) Setting up the laser point cloud spatial reference**

**3) Add Point Cloud Data**

**4) Add Trajectory Files**

**5) Define the trajectory** Set the spatial reference of the track line, the separator, and the actual meaning corresponding to each column ("GPS time, longitude, latitude, elevation" or "GPS time, east coordinate, north coordinate, elevation").

**6) Enquiry** Whether you need to check for data matching.

**7) Check the matching results** Laser point cloud check contains laser point position and track line position matching; laser point cloud time and track line time matching. And display the matching status.

**8) Apply point cloud** After importing point cloud, click **Apply** to generate a new block.

### **Add Terrestrial Laser Scanning** Get3D Mapper supports adding laser point cloud and center data collected by a stationary laser equipment. The software can support laser point cloud modeling alone and laser point cloud and photo fusion modeling. The following formats are supported: \*.las, \*.ptx, \*.pts, and \*.e57. The station center supports manual input or import of \*.txt format files.

Add Terrestrial Laser Scanning Interface

**1) Select the point cloud coordinate system**

**2) Add Point Cloud**

**3) Add station Center** There are two ways to add station center coordinates: One is to manually add station center coordinates on the right side of the point cloud list. The other is to click **Add Station Center**, import the center of the station coordinates file. File samples such as the figure below, including the point cloud name, x, y, z arrangement, separated by a space in the middle:

If there is no station center coordinates, the software can automatically calculate, uncheck the Define station center. **4) Apply point cloud** After importing point cloud, click **OK** to generate a new block.

### Process Point Cloud In the point cloud block, navigate to the **Point Cloud** panel and click **Process** to cut the point cloud.

After processing, you can view and check the point cloud in the 3D view. If point cloud checked, then continue create a new 3D reconstruction according to the workflow. ## Point Cloud-Image Fusion Modeling Get3D Mapper supports importing laser point cloud data and fusing it with image data for modeling. Multi-source data fusion modeling can solve the texture distortion, feature voids and other defects in the 3D modeling process. Image data is first imported for aerial triangulation (Relative Orientation). For data containing control points, Absolute Orientation should be completed before importing the laser data for fusion modeling. After AT, open the Point Cloud panel, select the point cloud type, and add the data (e.g., mobile LiDAR).

Imports laser data: The laser data consists of .las point cloud files, and .txt point cloud trajectory line files. Click **Add Mobile Point Cloud**, select the correct coordinate system, import the point cloud file in ".las" format, and the trajectory line file in ".txt" format.

**Note: The correct coordinate system should be selected for both files.** Where the trajectory line file needs to correspond to: Time, X, Y, Z

Click **OK** and the software automatically matches the point cloud data with the track line. The two correspond to each other and the submission is successful.

Click **Process** in Point Cloud Process to slice the tiles. Once you have finished slicing the tiles, you can view both the point cloud trace lines and the image photo shelf in the 3D view.

Right click to submit Reconstruction for multi-source data fusion modeling.

Tutorial video: