Tool ISODATA Clustering for Grids
This tool executes the Isodata unsupervised classification - clustering algorithm. Isodata stands for Iterative Self-Organizing Data Analysis Techniques. This is a more sophisticated algorithm which allows the number of clusters to be automatically adjusted during the iteration by merging similar clusters and splitting clusters with large standard deviations. The tool is based on Christos Iosifidis' Isodata implementation.
References
- Author: O.Conrad (c) 2016
- Menu: Imagery|Classification|Unsupervised
Parameters
| Name | Type | Identifier | Description | Constraints |
Input | Features | Grid list, input | FEATURES | - | - |
Output | Clusters | Grid, output | CLUSTER | - | - |
Statistics | Table, output | STATISTICS | - | - |
Options | Grid System | Grid system | PARAMETERS_GRID_SYSTEM | - | - |
Normalize | Boolean | NORMALIZE | - | Default: 0 |
Maximum Number of Iterations | Integer | ITERATIONS | - | Minimum: 3 Default: 20 |
Initial Number of Clusters | Integer | CLUSTER_INI | - | Minimum: 0 Default: 5 |
Maximum Number of Clusters | Integer | CLUSTER_MAX | - | Minimum: 3 Default: 16 |
Minimum Number of Samples in a Cluster | Integer | SAMPLES_MIN | - | Minimum: 2 Default: 5 |
Update Colors from Features | Boolean, GUI | RGB_COLORS | Use the first three features in list to obtain blue, green, red components for class colour in look-up table. | Default: 0 |
Start Partition | Choice | INITIALIZE | - | Available Choices: [0] random [1] periodical [2] keep values Default: 0 |
Command-line
Usage: saga_cmd imagery_isocluster 0 [-FEATURES <str>] [-CLUSTER <str>] [-STATISTICS <str>] [-NORMALIZE <str>] [-ITERATIONS <num>] [-CLUSTER_INI <num>] [-CLUSTER_MAX <num>] [-SAMPLES_MIN <num>] [-INITIALIZE <str>]
-FEATURES:<str> Features
Grid list, input
-CLUSTER:<str> Clusters
Grid, output
-STATISTICS:<str> Statistics
Table, output
-NORMALIZE:<str> Normalize
Boolean
Default: 0
-ITERATIONS:<num> Maximum Number of Iterations
Integer
Minimum: 3
Default: 20
-CLUSTER_INI:<num> Initial Number of Clusters
Integer
Minimum: 0
Default: 5
-CLUSTER_MAX:<num> Maximum Number of Clusters
Integer
Minimum: 3
Default: 16
-SAMPLES_MIN:<num> Minimum Number of Samples in a Cluster
Integer
Minimum: 2
Default: 5
-INITIALIZE:<str> Start Partition
Choice
Available Choices:
[0] random
[1] periodical
[2] keep values
Default: 0