Unsupervised Classfication using ER Mapper

If you haven't copied any datasets you plan to use to your Q folder, do that now because you'll be re-writing the header files. Because it is a smaller dataset, you might want to copy the small_VA_TM.ers dataset for this exercise.

Getting Ready

Open a new RGB algorithm. When it asks for the dataset, find the piece of the dataset newly copied to your own directory. Adjust the transform by clicking on the "GO with 99% clip on limits" button and then save it as an algorithm (e.g., small_Va_RGB321.alg) in your home directory.

Then you must calculate the statistics that cover the seven bands in this region (min, max, mean, variance, etc) These are used by the classification process. From the Proces Menu choose Calculate Statistics, select your small_Va.ers dataset, choose a resampling of 1 and click the "force recalculation button" on black). Click ok. When it's done, close the box by clicking cancel (you may get an error message).

Classification:

From the Process Menu, Click on "classfication" and choose "ISOCLASS Unsupervised Classfication"

You will be presented with a box in which to make 6 changes

  1. Input Dataset: Open the samll_Va_TM.ers in your directory
  2. Bands to use: It says all, but we don't want band six. Click on the folder next to the band box a list of the possible bands comes up. To get rid of band six click and drag through all seven bands to select them and then hold the control key down and click on band six to de-select it. Then click ok. The box should now read 1-5,7.
  3. Ouput Dataset: Give it a descriptive name like "sm_Va_isoclass_10.ers" (for 10 classes).
  4. Max Number of Classes: You want a maximum of 10 classes for this exercise (normally you don't want to constrain this)
  5. Minimum members in class (%): You normally don't want very narrowly defined classes, choose 1%.
  6. Desired percent unchanged: choose 90%

Click ok. Watch the process to see what's happening.

Display your classification.

  1. Open a new pseudocolor algorithm.
  2. Change the layer type to Classification Display (in the middle of the layer stack).
  3. Add your newly created dataset and click GO. NOTE ! it doesn't make any sense to use a 99% click on classified data...right? Don't use that button.
  4. From the Edit menu, select Edit Class/Region Color and Name
  5. Choose the colors that you want to have displayed for each of these regions.
  6. If you want to know where you are, display band 5 from the small_Va.ers dataset on top of the classification layer (chooose Add and put in a new Pseudocolor layer) and then find out what's underneath by showing the pixel values. Right click on the image or from the View menu choose the Cell Value option (near the bottom). You can also use the transparency change technique.

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