PointCloudCombiner

Combines features into a single point cloud. Point cloud and non-point cloud geometries are supported.

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Typical Uses

  • Combining multiple point clouds into a single feature
  • Converting non-point cloud features to a point cloud in order to process them against point cloud features
  • Converting non-point cloud geometry to a point cloud to take advantage of processing efficiency gains

How does it work?

The PointCloudCombiner receives one or more features and combines them into a single point cloud output feature, converting geometry to point clouds if necessary.

When combining multiple input features, all features must be in the same coordinate system, regardless of geometry type.

Attributes and measures may optionally be preserved as point cloud components.

The various input geometry types are each handled differently.

Point Clouds

Input point cloud features are simply combined with no further modifications. They may be combined with additional point clouds and/or any other input geometry type.

Vectors

Vectors are converted as follows:

  • Point and curve features are converted vertex for vertex - that is, each vertex in the vector geometry will produce a point in the point cloud.
  • Polygonal, donut, surface and solid features are converted into a grid of points lying inside the area on the 3D plane represented by the area’s calculated normal. The density of the grid may be adjusted with the Point Interval parameter.

Rasters

Rasters are converted as follows:

  • The x and y components are created from the cell ground coordinates, or columns and rows if the raster has no coordinate system.
  • The first selected numeric band will become the z component.
  • The first selected bands with red/green/blue/gray interpretations will become the color_red/color_green/color_blue components.
  • Additional selected bands will also be preserved. If the band has a name, the component name will be the band name. If the band has no name, the component name will be bandN, where N is the band index.
  • Nodata may optionally be extracted.

Examples

Usage Notes

  • When combining multiple input features (regardless of format), they must be in the same coordinate system. The CoordinateSystemSetter and Reprojector transformers may be useful.

Choosing a Point Cloud Transformer

FME has a selection of transformers for working specifically with point cloud data.

For information on point cloud geometry and properties, see Point Clouds (IFMEPointCloud).

Configuration

Input Ports

Output Ports

Parameters

Editing Transformer Parameters

Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.

Defining Values

There are several ways to define a value for use in a Transformer. The simplest is to simply type in a value or string, which can include functions of various types such as attribute references, math and string functions, and workspace parameters. There are a number of tools and shortcuts that can assist in constructing values, generally available from the drop-down context menu adjacent to the value field.

Dialog Options - Tables

Transformers with table-style parameters have additional tools for populating and manipulating values.

Reference

Processing Behavior

Group-Based

Feature Holding

Yes

Dependencies None
Aliases  
History  

FME Community

The FME Community is the place for demos, how-tos, articles, FAQs, and more. Get answers to your questions, learn from other users, and suggest, vote, and comment on new features.

Search for all results about the PointCloudCombiner on the FME Community.

 

Examples may contain information licensed under the Open Government Licence – Vancouver and/or the Open Government Licence – Canada.

Keywords: point "point cloud" cloud PointCloud LiDAR sonar