Reduces the number of points in (thins) a point cloud by keeping points at a fixed interval, a maximum number of points, or a set quantity of first or last points. Remaining points are discarded.

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Typical Uses

  • Reducing the data volume of a point cloud feature to meet processing or storage requirements.
  • Creating a sample point cloud dataset for testing

How does it work?

The PointCloudThinner receives point cloud features and outputs them with fewer points than the original.

The Points to Keep are identified by a fixed interval, a maximum number of points, or by specifying a first or last number of points:

Thinning Type Amount Result

Every Nth Point (Interval)


Every 5th point of the input cloud feature will be present in the output point cloud.

Every Nth Point (Maximum Number of Points)


The output cloud will have a maximum of 100 points, evenly spaced throughout the input.

First N Points


The first 100 points from the input will be kept.

Last N Points


The last 500 points from the input will be kept.


Usage Notes

  • For finer control over how a point cloud is reduced, consider using the PointCloudSimplifier transformer. It reduces while maintaining the overall shape of the original point cloud feature, however, may take considerably more processing time.

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).


Input Ports

Output Ports


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.


Processing Behavior


Feature Holding


Dependencies None
Aliases PointCloudSampler

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 PointCloudThinner 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