Traditional aerial LIDAR, mobile laser scanning, tripod mounted terrestrial scanners, and our True View line of 3DIS (3D imaging systems) are all tools that have been added to the surveyor and mappers toolbox. In the end the need is quite often the same, to turn the rich, dense point cloud into vectors and gridded point representations akin to traditional surveying drawings that can be ingested into CAD for the engineer to analyze and design around. Thankfully, for the True View user, True View EVO, the point cloud processing engine included with every system purchase, is built on our LP360 point cloud exploitation software, providing the True View user with a wide array of tools for creating products from the dense point cloud and imagery. Many of these have been in use for years and some are more recent introductions or modifications to existing features to help streamline the processing.
Need breakline vector elements in CAD?
EVO contains an extensive suite of Feature Edit and Feature Analyst tools. The former for digitizing various breakline features as desired and conflating elevation values from the point cloud with the feature elements as you digitize or edit features, or vertices all while synchronized with the views for visually referencing the point cloud for quality control and validation. The Feature Analyst tools provide not only the means for viewing and editing feature attributes and schema, but powerful tools for navigation and analysis of those features.
Figure 1 Feature Analyst For Efficiently Locating And Navigating To Problematic Vertices Once compiled, conversion to AutoDesk’s AutoCAD DXF (Drawing Interchange Format or Drawing Exchange Format) is as simple as a right-click on your feature layer in the Table of Contents (TOC) and selecting Export as DXF.
Figure 2 Export Features To DXF
Need a Digital Elevation Model as a Raster?
Figure 3 Exporting A DEM Raster
Do your workflows or CAD software require that you ingest a gridded ASCII dataset instead?
After exporting the raster model at your desired grid spacing, use the “DEM to LAS” tab of the Add Files dialog to convert the raster back into a point cloud. Then, use the Export Wizard to export the points to a delimited ASCII XYZ, or even go directly to DXF.
Figure 4 DEM To LAS To Create A Gridded Dataset From The Raster
Figure 5 Export Gridded Points To ASCII XYZ
Contours can be generated from a TIN surface at specified intervals. The contours can be saved to one of the three following file formats: shapefiles, DXF, or DGN, though we recommend using shapefiles, then converting to DXF by right-clicking on the feature layer as explained above. You have a choice to save polylines as 3D or 2D when exporting to shapefiles, where the elevation is always stored as an attribute for each contour. Each index and intermediate contour is assigned a user-specified type code. The codes are stored as attributes for shapefiles.
Figure 6 Breakline Enforced Contours
Processed your point cloud in a known spatial reference system, but now need the final products in a local coordinate system?
The LAS Affine Transform Point Cloud Task (PCT) is the flexible tool for applying common types of transformations to take a point cloud dataset from grid-to-ground. That can even be the raster that you’ve brought back into EVO using the DEM to LAS, as discussed above. For example, one of the most common grid-to-ground transformations is when you know the horizontal scale to be applied from an origin point. Configure the LAS Affine Transform PCT with the scale and translate values – we provide a cheat sheet on our searchable support knowledge base to help you out. The result of running the point cloud task is a new dataset in the ground, aka local coordinate system. Then, create your desired products from the local coordinate system dataset.
Figure 7 Applying A Horizontal Scale About An Origin Point Using The LAS Affine Transform PCT
Not seeing what you need or the workflow on how to achieve the products you need?
Reach out to us and we’ll help you to turn your acquired point cloud into the dataset you need.