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Exercise 2: Lava Detection using Supervised Classification - continued
 
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Training fields

  • Choose an RGB band combination (e.g. 4-5-3) and stretch the image so that you can visually distinguish between different classes.
  • Multivariate Analysis >Supervised Classification > Select Training Fields or press on the red TF icon. A new bar will open.
  • Press the open icon in TF bar
  • Open the file TF_2001_6cl.sav
  • Inspect some of the training fields and look at the classes.
 
 
Training fields for Landsat 2001 (FCC 4-5-3), 6 classes
 
To learn how to work with the GIS module, please refer to the tutorial on p. 92.

To draw some more training fields:

  • Digitise an area.
  • Finish the polygon with a right click on the mouse.
  • In the training fields window name the polygon according to the class and then press enter.
  • Save the result (the icon is in the TF bar).


 
 
Running the classification, assigning colours to classes

  • Open the un-stretched (original) Landsat 2001 bands number 1, 2, 3, 4, 5, and 7 separately as greyscale images.
  • Mark the FCC where you have opened the training fields before.
  • Go to Multivariate Analysis >Supervised Classification > Maximum Likelihood.
  • Pressing the shift button, mark the un-stretched band number 1, 2, 3, 4, 5, and 7 of Landsat 2001.
  • Set the threshold to 0 (zero) so that all pixels get classified
  • Press OK
  • The process will now run for several seconds to one minute, depending on the image size, the number of bands, and your computer.

 
 
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Nyiragongo and Nyamuragira
Introduction
Change detection and hazard assessment
Worksheet introductionExercise 1: Exploring and learning about the volcanoExercise 2: Lava Detection using Supervised ClassificationExercise 3: Multitemporal Change Detection and Monitoring
Eduspace - Download
Nyiragongo_Landsat.zip
Eduspace - Software
LEOWorks 3LEOWorks 3 Tutorial
 
 
 
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