LiDAR drones are gaining popularity in the land surveying market. These systems are a particularly good choice for creating surveys over closed tree canopies.
The laser pulses from a lidar unit hit not only the topcover vegetation of an area, but also the underlying ground or structures. By measuring travel time of the laser pulse bare-earth elevations under tree canopies can be brought to light. This is impossible with only a photogrammetric drone system.
This article explains how these point clouds can be loaded and converted in Virtual Surveyor.
Virtual Surveyor converts the point cloud to an elevation terrain and/or a image terrain. This is a good approach for digital earth works applications and when you want to create a topographic surface at bare-earth level. Virtual Surveyor is not a point cloud engine, so it is not recommended for mobile mapping and terrestrial scanning.
- Supported point cloud file formats are:
- The user sets a coordinate system or units because .las/.laz don’t carry a coordinate system like GeoTIFF files do.
- The user choose to generate an elevation terrain (DSM) and/or an image terrain (orthophoto). It is only possible to generate an image terrain when the point cloud contains color information.
- The user decides to favor high points (top of canopy) or low points (bare-earth). Or he can select the available classes (if available) before starting the conversion.
Add a point cloud file
- Create a new (empty) project first.
- Drag & drop the point cloud file or files in the project view.
- Click on Input Required button to set the point cloud conversion options.
- Define the coordinates system. You can enter the coordinates system name or EPSG code to easily find it in the list. Check "I don't know" and select the units if you prefer to work in a local coordinate system.
- Choose the Point cloud settings.
- Decide whether you want to convert the point cloud to an elevation terrain, an image terrain or both.
- Choose the conversion option. Favor high points is good to model top of canopy. Favor low point gives priority to bare-earth points. You can also decide which classes to import if the point cloud has previously been classified.
- Click Run to start the conversion.
- Only the points selected according to the conversion option will be used.
- Holes will be interpolated.
- When the conversion ends, Insert the terrain in the view port.
- The image terrain is draped over the elevation terrain.
- The hill shade lens is automatically enabled if no image terrain has been generated from the point cloud
Favor High VS favor low
A lidar unit can create multiple points at the same horizontal location in a point cloud. Indeed, the beam can either hit the vegetation or go through an interstice and measure a lower point thanks to multiple drone positions and angles. The user can force the points to favor during the conversion of the point cloud to an elevation terrain.
Favor high points is good to model top of canopy. It can be used when you want to analysis tree heights or other vegetation features.
Favor low points gives priority to bare-earth points. The resulting elevation terrain is not a perfect bare-earth surface and still contains some spikes. But this process reveals areas under the vegetation where the lidar beam was able to go through canopy cracks and hit the ground.
Add multiple point cloud files
When you add multiple point cloud files, Virtual Surveyor will test if they overlap or touch. When so, the multiple point cloud files will be merged into one large terrain file.
Tips & Tricks
- Use a low pass point grid after lidar point cloud import with favor low points option to generate a bare-earth surface.
- You can use the other terrain lenses to emphasize your terrain. Explore all the terrain lenses here.
- It also works for bathymetry data.
- Virtual Surveyor is not a point cloud engine, and generally is not designed to work with terrestrial and mobile mapping data sources.
- Point clouds from photogrammetry data? You can use them but in this case it is better to use the orthophoto and DSM from the photogrammetry process.