Tool NameSupervised Majority Choice Image Classification
Tool IDclassify_majority
Library IDimagery_classification
Version1.0
Author(s)O. Conrad (c) 2023

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 Artificial Neural Network have been excluded from default, because using them might be a bit more time consuming.

Parameters

NameTypeIdentifierDescriptionConstraints
Input
Featuresgrid list, inputFEATURES
Training Areasshapes, inputTRAIN_AREAS
Training Samplestable, inputTRAIN_SAMPLES
Output
Majority Choicegrid, outputCLASSES
Majority Countgrid, output, optionalMAJORITY_COUNT
Classes Countgrid, output, optionalNUNIQUES
Options
NormalizebooleanNORMALIZEDefault: 0
TrainingchoiceMODEL_TRAINAvailable 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
UnambiguousbooleanUNAMBIGUOUSDo not classify a pixel if more than one class reaches the same majority count for it.Default: 0
Parallel EpipedbooleanCLASSIFY_BOXDefault: 1
Minimum DistancebooleanCLASSIFY_MINDISTDefault: 1
Mahalonobis DistancebooleanCLASSIFY_MAHALONOBISDefault: 1
Maximum LikelihoodbooleanCLASSIFY_MAXLIKEDefault: 1
Spectral Angle MappingbooleanCLASSIFY_SAMDefault: 1
Normal BayesbooleanCLASSIFY_BAYESDefault: 1
Decision TreebooleanCLASSIFY_DTDefault: 1
Random ForestbooleanCLASSIFY_RFDefault: 0
Support Vector MachinebooleanCLASSIFY_SVMDefault: 1
K-Nearest NeighboursbooleanCLASSIFY_KNNDefault: 0
Artificial Neural NetworkbooleanCLASSIFY_ANNDefault: 0