Convert LAS to SHP

Simplify Features

A dense point cloud can be thinned for more efficient processing and then filtered based on the standard ASPRS classification or other LAS components. A series of transformers can be used to process each feature of interest such as distinct building footprints as polygons or approximated tree locations as points. A few transformers that can be useful in this process include:

• PointCloudThinner: Using dense point clouds in a workflow can often be time consuming and inefficient especially when creating shapefiles. To overcome this issue, the PointCloudThinner can be used to simplify the input data by removing points without jeopardizing the quality of the output features.
• PointCloudFilter: LiDAR data has a variety of components for each point collected. The PointCloudFilter transformer is a great option for distinguishing points based on components like intensity or classification for further, component-specific processing such as creating shapefiles.
• PointCloudSplitter: The PointCloudSplitter is similar to the PointCloudFilter in its ability to distinguish certain points of interest from a point cloud based on components. This transformer will output multiple point cloud features immediately after use for further processing or to be saved as their own individual .LAS files.

Before: An .LAS point cloud of a city

After: Three .SHP files of points and polygons representing buildings, the ground and trees

Tutorial: Point Clouds for Profiling and Slicing