Tool Cluster Analysis for Point Clouds
Cluster analysis for point clouds.
This tool is a port of the 'Cluster Analysis for Grids' tool from the 'Imagery - Classification' tool library.
References
- Forgy, E. (1965): Cluster Analysis of multivariate data: efficiency vs. interpretability of classifications. Biometrics 21:768.
- Rubin, J. (1967): Optimal Classification into Groups: An Approach for Solving the Taxonomy Problem. J. Theoretical Biology, 15:103-144.
- Author: Volker Wichmann (c) 2010, LASERDATA GmbH
- Menu: Shapes|Point Clouds|Classification
Parameters
| | Name | Type | Identifier | Description | Constraints |
|---|
| Input | Point Cloud | Point Cloud, input | PC_IN | Input | - |
| Output | Result (*) | Point Cloud, output, optional | PC_OUT | Output | - |
| Statistics | Table, output | STATISTICS | - | - |
| Options | Attributes | Table fields | FIELDS | The attribute fields to cluster | - |
| Method | Choice | METHOD | - | Available Choices:
[0] Iterative Minimum Distance (Forgy 1965)
[1] Hill-Climbing (Rubin 1967)
[2] Combined Minimum Distance / Hillclimbing
Default: 1 |
| Clusters | Integer | NCLUSTER | Number of clusters | Minimum: 2
Default: 10 |
| Normalise | Boolean | NORMALISE | Automatically normalise attributes by standard deviation before clustering. | Default: 1 |
| (*) optional |
Command-line
Usage: saga_cmd pointcloud_tools 11 [-PC_IN <str>] [-FIELDS <str>] [-PC_OUT <str>] [-STATISTICS <str>] [-METHOD <str>] [-NCLUSTER <num>] [-NORMALISE <str>]
-PC_IN:<str> Point Cloud
Point Cloud, input
-FIELDS:<str> Attributes
Table fields
-PC_OUT:<str> Result
Point Cloud, output, optional
-STATISTICS:<str> Statistics
Table, output
-METHOD:<str> Method
Choice
Available Choices:
[0] Iterative Minimum Distance (Forgy 1965)
[1] Hill-Climbing (Rubin 1967)
[2] Combined Minimum Distance / Hillclimbing
Default: 1
-NCLUSTER:<num> Clusters
Integer
Minimum: 2
Default: 10
-NORMALISE:<str> Normalise
Boolean
Default: 1