Our first step in post processing is to ensure our classified ground points are representative of the actual surface we flew. This involves both automatic and manual cleaning. Running our raw point cloud through the TerraScan drone wizard classifies our data (ground, low/medium/high vegetation, building, noise, etc.) and from there we can pan through the data for any anomalies. These are often points classified as ground that do not represent the real-world ground, such as at the bottom of drainage inlets or running up the edge of a building wall. These points will be manually classified out of the ground. The example below demonstrates an inlet in a parking lot where the bottom of the inlet was classified as ground. In the shaded surface, we can see the indentation in the surface while the cross-section view identifies erroneous ground points.
Classify these points as low points, to be deleted from the point cloud later, and we have a clean surface.
One of the most common deliverables our clients ask for is a LandXML surface model. Generating a surface model requires DTM extraction in the form of breaklines. These are features that are on the ground and hold elevations for the area. Common features included in our DTM extraction are top and toe of slopes, edges of paved surfaces, road crown lines, gutters/top of curb, and edge of water. We will also include model keypoints or grid points to sub-sample the lidar ground points. For our simplified surfaces, we often use 50-foot grid points with a closest Z value sampling. These points are exported as an XYZ text file through TerraScan. Unneeded grid points (within 10 feet of breaklines, on roads or buildings) will be deleted. This lends itself to a better-looking (smoother) surface model in comparison to using model keypoints. These options are dependent on the level of accuracy required. Alternatively, planimetric features are not included in the surface model as they are only 2D and do not hold an elevation value. These features include anything else we can see in the project area – commonly tree lines, street signs, buildings, powerlines. Most of our planimetrics are extracted off the orthomosaic while the lidar can provide confirmation on location. Since these are representative 2D features, their elevation is set to 0 prior to delivery. Of course, this is client based and may differ from project to project. A following topic will key on this differentiation as well.
Providing this brief look into our feature extraction processes, we hope you can gather some insights and extend the limits of your own practices. Reach out with any tips or tricks you would like us to dive deeper on or share any of your experiences.
Be on the lookout for our next installment!
Again, feel free to reach out with any questions or inquiries. Our team continues to evolve and innovate relating to our workflows and we would be happy to collaborate with you.
