SAGA 9.4.2 | Tool Library Documentation

Supervised Majority Choice Image Classification


Description

The majority choice tool for supervised image classification runs the selected classification tools using standard settings and takes for each pixel of the resulting classification the class that has been identified most often by the individual classifiers. Random Forest is not selected by default because it generates randomized results with more or less strong differences each time it is run. K-Nearest Neighbours and Artifical Neural Network have been excluded from default, because using them might be a bit more time consuming.


Parameters

 NameTypeIdentifierDescriptionConstraints
InputFeaturesgrid list, inputFEATURES--
Training Areasshapes, inputTRAIN_AREAS--
Training Samplestable, inputTRAIN_SAMPLES--
OutputMajority Choicegrid, outputCLASSES--
Majority Countgrid, output, optionalMAJORITY_COUNT--
Classes Countgrid, output, optionalNUNIQUES--
OptionsNormalizebooleanNORMALIZE-Default: 0
TrainingchoiceMODEL_TRAIN-Available Choices: [0] training areas [1] training samples Default: 0
Class Identifiertable fieldTRAIN_CLASS--
Buffer Sizefloating point numberTRAIN_BUFFERFor non-polygon type training areas, creates a buffer with a diameter of specified size.Minimum: 0.000000 Default: 30.000000
Grid Systemgrid systemGRID_SYSTEM--
UnambiguousbooleanUNAMBIGUOUSDo not classify a pixel if more than one class reaches the same majority count for it.Default: 0
Parallel EpipedbooleanCLASSIFY_BOX-Default: 1
Minimum DistancebooleanCLASSIFY_MINDIST-Default: 1
Mahalonobis DistancebooleanCLASSIFY_MAHALONOBIS-Default: 1
Maximum LikelihoodbooleanCLASSIFY_MAXLIKE-Default: 1
Spectral Angle MappingbooleanCLASSIFY_SAM-Default: 1
Normal BayesbooleanCLASSIFY_BAYES-Default: 1
Decision TreebooleanCLASSIFY_DT-Default: 1
Random ForestbooleanCLASSIFY_RF-Default: 0
Support Vector MachinebooleanCLASSIFY_SVM-Default: 1
K-Nearest NeighboursbooleanCLASSIFY_KNN-Default: 0
Artificial Neural NetworkbooleanCLASSIFY_ANN-Default: 0

Command Line


Usage: saga_cmd imagery_classification classify_majority [-FEATURES ] [-NORMALIZE ] [-MODEL_TRAIN ] [-TRAIN_AREAS ] [-TRAIN_CLASS ] [-TRAIN_BUFFER ] [-TRAIN_SAMPLES ] [-CLASSES ] [-MAJORITY_COUNT ] [-NUNIQUES ] [-UNAMBIGUOUS ] [-CLASSIFY_BOX ] [-CLASSIFY_MINDIST ] [-CLASSIFY_MAHALONOBIS ] [-CLASSIFY_MAXLIKE ] [-CLASSIFY_SAM ] [-CLASSIFY_BAYES ] [-CLASSIFY_DT ] [-CLASSIFY_RF ] [-CLASSIFY_SVM ] [-CLASSIFY_KNN ] [-CLASSIFY_ANN ]
  -FEATURES:            	Features
	grid list, input
  -NORMALIZE:           	Normalize
	boolean
	Default: 0
  -MODEL_TRAIN:         	Training
	choice
	Available Choices:
	[0] training areas
	[1] training samples
	Default: 0
  -TRAIN_AREAS:         	Training Areas
	shapes, input
  -TRAIN_CLASS:         	Class Identifier
	table field
  -TRAIN_BUFFER:     	Buffer Size
	floating point number
	Minimum: 0.000000
	Default: 30.000000
  -TRAIN_SAMPLES:       	Training Samples
	table, input
  -CLASSES:             	Majority Choice
	grid, output
  -MAJORITY_COUNT:      	Majority Count
	grid, output, optional
  -NUNIQUES:            	Classes Count
	grid, output, optional
  -UNAMBIGUOUS:         	Unambiguous
	boolean
	Default: 0
  -CLASSIFY_BOX:        	Parallel Epiped
	boolean
	Default: 1
  -CLASSIFY_MINDIST:    	Minimum Distance
	boolean
	Default: 1
  -CLASSIFY_MAHALONOBIS:	Mahalonobis Distance
	boolean
	Default: 1
  -CLASSIFY_MAXLIKE:    	Maximum Likelihood
	boolean
	Default: 1
  -CLASSIFY_SAM:        	Spectral Angle Mapping
	boolean
	Default: 1
  -CLASSIFY_BAYES:      	Normal Bayes
	boolean
	Default: 1
  -CLASSIFY_DT:         	Decision Tree
	boolean
	Default: 1
  -CLASSIFY_RF:         	Random Forest
	boolean
	Default: 0
  -CLASSIFY_SVM:        	Support Vector Machine
	boolean
	Default: 1
  -CLASSIFY_KNN:        	K-Nearest Neighbours
	boolean
	Default: 0
  -CLASSIFY_ANN:        	Artificial Neural Network
	boolean
	Default: 0