28.1.13. Point Cloud Data Management

28.1.13.1. Assign projection 

Assigns a Coordinate Reference System to a point cloud layer, if it is missing or wrong. A new layer is created.

See also

Reproject

Parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to assign a CRS to

Desired CRS

CRS

[crs]

The CRS to apply to the layer

Output layer

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the point cloud file to use as output. One of:

Save to a Temporary File
Save to File…

Outputs

Label	Name	Type	Description
Converted	`OUTPUT`	[point cloud]	Output point cloud layer with a new CRS. Currently supported formats are `.LAS`, `.LAZ`, `.COPC.LAZ` and `.VPC`.

Python code

Algorithm ID: pdal:assignprojection

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.2. Build virtual point cloud (VPC)

Creates a virtual point cloud (VPC) from input point cloud data.

If you leave the optional parameters unchecked, the VPC file will be built very quickly as the algorithm will only read metadata of input files. With any of the optional parameters set, the algorithm will read all points which can take some time.

../../../../_images/point_cloud_buildvpc.png — Fig. 28.13 Generating Virtual Point Cloud with overview from a set of point cloud tiles

See also

Merge

Parameters

Label	Name	Type	Description
Input layers	`LAYERS`	[point cloud] [list]	Input point cloud layers to combine inside a virtual point cloud layer
Calculate boundary polygon	`BOUNDARY`	[boolean] Default: False	Set to True to show the exact boundaries of data (rather than just rectangular extent)
Calculate statistics	`STATISTICS`	[boolean] Default: False	Set to True to understand ranges of values of the various attributes
Build overview point cloud	`OVERVIEW`	[boolean] Default: False	Generates a single “thinned” point cloud of all the input data (using only every 1000th point from original data). The overview point cloud will be created next to the VPC file - for example, for `mydata.vpc`, the overview point cloud would be named `mydata-overview.copc.laz`.
Virtual point cloud	`OUTPUT`	[point cloud] Default: `[Save to temporary file]`	Specify the point cloud file to build the data into. One of: Save to a Temporary File Save to File…

Outputs

Label	Name	Type	Description
Virtual point cloud	`OUTPUT`	[raster]	Output point cloud layer combining all the input data, as a virtual file.

Python code

Algorithm ID: pdal:virtualpointcloud

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.3. Clip 

Clips a point cloud layer by a polygon layer so that the resulting point cloud contains only points within the polygons.

../../../../_images/point_cloud_clip.png — Fig. 28.14 Clipping an input point cloud layer with a polygon coverage

Parameters

Basic parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to clip

Clipping polygons

OVERLAY

[vector: polygon]

Polygon vector layer to use as coverage for clipping the points

Clipped

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the point cloud file to export the clipped points to. One of:

Save to a Temporary File
Save to File…

Advanced parameters

Label

Name

Type

Description

Filter expression

Optional

FILTER_EXPRESSION

[expression]

A PDAL expression for selecting a subset of features in the point cloud data

Cropping extent

Optional

FILTER_EXTENT

[extent]

A map extent for selecting a subset of features in the point cloud data

Available methods are:

Calculate from layer…: uses extent of a layer loaded in the current project
Calculate from layout map…: uses extent of a layout map item in the active project
Calculate from bookmark…: uses extent of a saved bookmark
Use map canvas extent
Draw on canvas: click and drag a rectangle delimiting the area to take into account
Enter the coordinates as xmin, xmax, ymin, ymax

Outputs

Label	Name	Type	Description
Clipped	`OUTPUT`	[raster]	Output point cloud whose features are the points within the coverage polygon layer.

Python code

Algorithm ID: pdal:clip

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.4. Create COPC 

Creates the index for all the input point cloud files in a batch mode.

Parameters

Label

Name

Type

Description

Input layers

LAYERS

[point cloud] [list]

Input point cloud layers to create an index for

Output directory

Optional

OUTPUT

[folder]

Default: [Skip output]

Specify the folder to create the new files in. One of:

Skip Output
Save to a Temporary Directory
Save to Directory

Outputs

Label	Name	Type	Description
Output directory	`OUTPUT`	[folder]	Output folder containing point cloud layers with accompanying COPC index files.

Python code

Algorithm ID: pdal:createcopc

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.5. Information 

Outputs basic metadata from an input point cloud file.

Example of output information:

LAS           1.4
point format  6
count         56736130
scale         0.001 0.001 0.001
offset        431749.999 5440919.999 968.898
extent        431250 5440420 424.266
              432249.999 5441419.999 1513.531
crs           ETRS89 / UTM zone 34N (N-E) (EPSG:3046)  (vertical CRS missing!)
units         horizontal=metre  vertical=unknown

Attributes:
- X floating 8
- Y floating 8
- Z floating 8
- Intensity unsigned 2
- ReturnNumber unsigned 1
- NumberOfReturns unsigned 1
- ScanDirectionFlag unsigned 1
- EdgeOfFlightLine unsigned 1
- Classification unsigned 1
- ScanAngleRank floating 4
- UserData unsigned 1
- PointSourceId unsigned 2
- GpsTime floating 8
- ScanChannel unsigned 1
- ClassFlags unsigned 1

Parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to extract metadata information from

Layer information

OUTPUT

[file]

Default: [Save to temporary file]

Specify the file to store the metadata information. One of:

Save to a Temporary File
Save to File…

Outputs

Label	Name	Type	Description
Layer information	`OUTPUT`	[vector]	`HTML` file to store the metadata information.

Python code

Algorithm ID: pdal:info

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.6. Merge 

Merges multiple point cloud files into a single one.

See also

Build virtual point cloud (VPC)

Parameters

Basic parameters

Label

Name

Type

Description

Input layers

LAYERS

[point cloud] [list]

Input point cloud layers to merge into a single one

Merged

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the output point cloud merging input files. One of:

Save to a Temporary File
Save to File…

Advanced parameters

Label

Name

Type

Description

Filter expression

Optional

FILTER_EXPRESSION

[expression]

A PDAL expression for selecting a subset of features in the point cloud data

Cropping extent

Optional

FILTER_EXTENT

[extent]

A map extent for selecting a subset of features in the point cloud data

Available methods are:

Calculate from layer…: uses extent of a layer loaded in the current project
Calculate from layout map…: uses extent of a layout map item in the active project
Calculate from bookmark…: uses extent of a saved bookmark
Use map canvas extent
Draw on canvas: click and drag a rectangle delimiting the area to take into account
Enter the coordinates as xmin, xmax, ymin, ymax

Outputs

Label	Name	Type	Description
Merged	`OUTPUT`	[point cloud]	Output point cloud layer merging all the input files.

Python code

Algorithm ID: pdal:merge

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.7. Reproject 

Reprojects a point cloud to a different Coordinate Reference System (CRS).

See also

Assign projection

Parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to reproject to a different CRS

Target CRS

CRS

[crs]

The CRS to apply to the layer

Reprojected

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the reprojected point cloud file. One of:

Save to a Temporary File
Save to File…

Advanced parameters

Label

Name

Type

Description

Coordinate operation

Optional

OPERATION

[datum]

The datum transformation to use to reproject the data between the origin and target systems.

Outputs

Label	Name	Type	Description
REPROJECTED	`OUTPUT`	[point cloud]	Output point cloud layer in the target CRS.

Python code

Algorithm ID: pdal:reproject

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.8. Thin (by sampling radius)

Creates a thinned version of the point cloud by performing sampling by distance point (reduces the number of points within a certain radius).

../../../../_images/point_cloud_thin.gif — Fig. 28.15 Thining point cloud (by sampling radius)

See also

Thin (by skipping points)

Parameters

Basic parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to create a thinned version from

Sampling radius (in map units)

SAMPLING_RADIUS

[number]

Default: 1.0

Distance within which points are sampled to a unique point

Thinned (by radius)

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the output point cloud with reduced points. One of:

Save to a Temporary File
Save to File…

Advanced parameters

Label

Name

Type

Description

Filter expression

Optional

FILTER_EXPRESSION

[expression]

A PDAL expression for selecting a subset of features in the point cloud data

Cropping extent

Optional

FILTER_EXTENT

[extent]

A map extent for selecting a subset of features in the point cloud data

Available methods are:

Calculate from layer…: uses extent of a layer loaded in the current project
Calculate from layout map…: uses extent of a layout map item in the active project
Calculate from bookmark…: uses extent of a saved bookmark
Use map canvas extent
Draw on canvas: click and drag a rectangle delimiting the area to take into account
Enter the coordinates as xmin, xmax, ymin, ymax

Outputs

Label	Name	Type	Description
Thinned (by radius)	`OUTPUT`	[point cloud]	Output point cloud layer with reduced points.

Python code

Algorithm ID: pdal:thinbyradius

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.9. Thin (by skipping points)

Creates a thinned version of the point cloud by keeping only every N-th point (reduces the number of points by skipping nearby points).

See also

Thin (by sampling radius)

Parameters

Basic parameters

Label

Name

Type

Description

Input layer

INPUT

[point cloud]

Input point cloud layer to create a thinned version from

Number of points to skip

POINTS_NUMBER

[number]

Default: 1

Keep only every N-th point in the input layer

Thinned (by decimation)

OUTPUT

[point cloud]

Default: [Save to temporary file]

Specify the output point cloud with reduced points. One of:

Save to a Temporary File
Save to File…

Advanced parameters

Label

Name

Type

Description

Filter expression

Optional

FILTER_EXPRESSION

[expression]

A PDAL expression for selecting a subset of features in the point cloud data

Cropping extent

Optional

FILTER_EXTENT

[extent]

A map extent for selecting a subset of features in the point cloud data

Available methods are:

Calculate from layer…: uses extent of a layer loaded in the current project
Calculate from layout map…: uses extent of a layout map item in the active project
Calculate from bookmark…: uses extent of a saved bookmark
Use map canvas extent
Draw on canvas: click and drag a rectangle delimiting the area to take into account
Enter the coordinates as xmin, xmax, ymin, ymax

Outputs

Label	Name	Type	Description
Thinned (by decimation)	`OUTPUT`	[point cloud]	Output point cloud layer with reduced points.

Python code

Algorithm ID: pdal:thinbydecimate

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.

28.1.13.10. Tile 

Creates tiles from input point cloud files, recommended for best performance (in display or analysis) with such datasets in QGIS.

Parameters

Basic parameters

Label

Name

Type

Description

Input layers

LAYERS

[point cloud] [list]

Input point cloud layers to create tiles from

Tile length

LENGTH

[number]

Default: 1000.0

Size of the edge of each generated tile

Output directory

OUTPUT

[folder]

Default: [Save to temporary folder]

Specify the folder to store the generated tiles. One of:

Save to a Temporary Directory
Save to Directory

Advanced parameters

Label

Name

Type

Description

Assign CRS

Optional

CRS

[crs]

The CRS to apply to the layer

Outputs

Label	Name	Type	Description
Output directory	`OUTPUT`	[folder]	Output folder containing the tiles generated from input files.

Python code

Algorithm ID: pdal:tile

import processing
processing.run("algorithm_id", {parameter_dictionary})

The algorithm id is displayed when you hover over the algorithm in the Processing Toolbox. The parameter dictionary provides the parameter NAMEs and values. See Using processing algorithms from the console for details on how to run processing algorithms from the Python console.