PointCloudPropertyExtractor

Extracts the geometry properties of a point cloud feature and exposes them as attributes, optionally checking for their existence, retrieving component properties, and finding minimum and maximum values. Extents may also be recalculated and updated.

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Typical Uses

  • Extracting basic information about a point cloud feature, such as geographic extents, number of points, and intensity ranges.
  • Calculating and updating point cloud extents after operations such as merging, clipping, or filtering that may affect their overall dimensions.
  • Accessing component information such as encoding and data type, so that further manipulation of these values can be more easily done.

How does it work?

The PointCloudPropertyExtractor receives point cloud features and extracts basic information about their geometry. The results are added as attributes, and output with the original feature.

A selection of Components is available, which may or may not exist on the point cloud. For each component included, you may check to see if it does exist (yes or no), retrieve its properties, and/or extract its minimum and maximum values. If Check Existence is used, and the chosen property does not exist on the point cloud feature, attributes will not be added for that component’s Properties or Min/Max values.

The number of points in the point cloud feature will always be included, as the attribute _num_points.

Available standard components include:

  • x
  • y
  • z
  • intensity
  • color_red
  • color_green
  • color_blue
  • classification
  • return
  • number_of_returns
  • angle
  • flight_line
  • scan_direction
  • point_source_id
  • posix_time
  • user_data
  • gps_time
  • gps_week
  • flight_line_edge
  • normal_x
  • normal_y
  • normal_z
  • classification_flags

Note: The extracted attribute values reflect the state of the point cloud at the time of extraction, and may become out of date if the point cloud properties change.

Calculate and Update Extents

A point cloud’s component values are static, and so must be explicitly updated to reflect changes.

This parameter may be used to update the extents (x, y, and z) of the point cloud feature after splitting, merging, or other operations that alter the bounding dimensions of the feature. The update is performed prior to the value extraction, and so the results will reflect updated extent values.

Examples

Usage Notes

  • To access similar information about individual points, use the PointCloudToPointCoercer to convert the point cloud feature to points.

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

Feature-Based

Feature Holding

No

Dependencies None
Aliases  
History  

FME Community

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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