Supervised classification (Tutorial)

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Classification with Orfeo Toolbox

Image statistics

  1. Add the LandSat-8 imagery Subset_S2A_MSIL2A_20170619T_B12_BOA.tif into a QGIS project.
  2. Calculate mean and standard error for each band of the Sentinel-2 imagery.
    1. Open Orfeo Toolbox --> Compute images second order statistics (see figure A).
    2. Set Subset_S2A_MSIL2A_20170619T_B12_BOA.tif as Input images.
    3. Save the Output XML file as Subset_S2A_MSIL2A_20170619T_B12_BOA.tif.xml.

Train image classifier

  1. Add the training areas lab_9_training_input.shp into QGIS. It should be available in the course data.
  2. Open Orfeo Toolbox --> TrainImageClassifier (libsvm) to use the Support Vector Machine SVM algorithm (see figure B).
  3. Set Subset_S2A_MSIL2A_20170619T_B12_BOA.tif as Input image list.
  4. Set training_manual_poly.shp as Input vector list.
  5. Set Subset_S2A_MSIL2A_20170619T_B12_BOA.tif.xml as Input XML image statistics file.
  6. Set Name of discrimination field to C_ID (C_ID refers to the column that contain the LUC classes code).
  7. Save the Output confusion matrix as ConfusionMatrixSVM.csv.
  8. Save the Output model as SVM.model.
  9. Calculation of accuracies :
    Open ConfusionMatrixSVM.csv in LibreOffice or MS Excel and calculate overall, producer and consumer accuracies.


  1. Add the cloud mask cloud_shadow_mask.tif into QGIS. It should be available in the course data.
  2. Open Orfeo Toolbox --> Image Classification (see figure C).
  3. Set Subset_S2A_MSIL2A_20170619T_B12_BOA.tif as Input image.
  4. Set cloud_shadow_mask.tif as Input mask.
  5. Set SVM.model as Model file.
  6. Set SUB_LC81950242013188LGN00_MUL.tif.xml as Statistical file.
  7. Save the Output image as su_svm.tif.
  8. Evaluate classification results.
    1. Add the classification result su_svm.tif to QGIS.
    2. Right click su_svm.tif in the TOC and select Properties --> Style --> Style --> Load Style.
    3. Load classifcation.qml, which should be available in the course data.
    4. Open the Google Maps Layer under Web --> ObenLayers plugin --> Add Google Satellite layer and look for misclassification.

Compute a confusion matrix with independent reference data

  1. Open Orfeo Toolbox --> ComputeConfusionMatrix (Vector) (see figure D).
  2. Set su_svm.tif as Input image.
  3. Set train_systematic_seg.shp as Input reference vector data.
  4. Set Field name to C_ID.


Figure A: Dialogues of the Compute images second order statistics
Figure B: Dialogues of the TrainImageClassifier (libsvm)
Figure C: Dialogues of the Image Classification
Figure D: Dialogues of the ComputeConfusionMatrix (Vector)
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