3.4.4.2. Classification¶
This tab allows for the classification of the Band set using the spectral signatures checked in ROI & Signature list. Several classification options are set in this tab which affect the classification process also during the Classification preview.
This tool allows for the use of the following algorithms: Minimum Distance, Maximum Likelihood, Spectral Angle Mapping.
Random Forest
is available in the Random Forest tab.
3.4.4.2.1. Classification¶
- Select input band set
: select the input Band set to be classified;
- Use
MC ID
C ID
: if MC ID is checked, the classification is performed using the Macroclass ID (code MC ID of the signature); if C ID is checked, the classification is performed using the Class ID (code C ID of the signature);
: open the Algorithm band weight for the definition of band weights;
3.4.4.2.2. Algorithm¶
This tool allows for the selection of the classification algorithm and the optiona definition of thresholds.
: available Classification Algorithms are:
- Threshold
: it allows for the definition of a classification threshold (applied to all the spectral signatures); if Threshold is equal to 0, then thresholds Signature threshold are evaluated; in particular:
- for Minimum Distance, pixels are unclassified if distance is greater than threshold value;
- for Maximum Likelihood, pixels are unclassified if probability is less than threshold value (max 100);
- for Spectral Angle Mapping, pixels are unclassified if spectral angle distance is greater than threshold value (max 90);
- Threshold
: open the Signature threshold for the definition of signature thresholds;
3.4.4.2.3. Land Cover Signature Classification¶
Land Cover Signature Classification is a classification that can be used as alternative or in combination with the Algorithm (see LCS threshold). Pixels belonging to two or more different classes (or macroclasses) are classified as Class overlap with raster value = -1000.
- Use
LCS
Algorithm
only overlap: if LCS is checked, the Land Cover Signature Classification is used; if Algorithm is checked, the selected Algorithm is used for unclassified pixels of the Land Cover Signature Classification; if only overlap is checked, the selected Algorithm is used only for class overlapping pixels of the Land Cover Signature Classification; unclassified pixels of the Land Cover Signature Classification are left unclassified;
: open the LCS threshold;
3.4.4.2.4. Classification output¶
Classification output allows for the classification of the Band set according to the parameters defined in Algorithm.
In addition, a previously saved classification style (QGIS .qml file) can be loaded and used for classification style.
Classification raster is a file .tif
(a QGIS style file .qml
is saved along with the classification); also other outputs can be optionally calculated.
Outputs are loaded in QGIS after the calculation.
- Load qml
: select a .qml file overriding the colors defined for C ID or MC ID;
: reset style to default (i.e. use the colors defined for C ID or MC ID);
Apply mask
: if checked, a shapefile can be selected for masking the classification output (i.e. the area outside the shapefile is not classified);
: reset the mask shapefile;
Create vector
: if checked, in addition to the classification raster, a classification shapefile is saved in the same directory and with the same name as the Classification output; conversion to vector can also be performed at a later time (see Classification to vector);
Classification report
: if checked, a report about the land cover classification is calculated and saved as a .csv file in the same directory and with the same name (with the suffix
_report
) as the Classification output; report can also be performed at a later time (see Classification report);Save algorithm files
: if checked, the Algorithm raster is saved, in addition to the classification raster, in the same directory as the Classification output; a raster for each spectral signature used as input (with the suffix
_sig_MC ID_C ID
) and a general algorithm raster (with the suffix_alg_raster
) are created;- BATCH
: add this function to the Batch;
- RUN
: choose the output destination and start the image classification;