I don't think it works out of the box using the ExtractExamplesFromRaster task. ExtractExamplesFromRaster can only process one raster and its associated ROIs.

You may be able to combine your samples through some additional IDL code. If you want to give it a try, here is the pseudo code:

1) For each raster and its associated ROIs, use ExtractExamplesFromRaster to exact examples.

2) Get properties from all examples and merge them. The properties are EXAMPLES, CLASS_VALUES, CLASS_NAMES and ATTRIBUTE_NAMES. When merging, make sure that the CLASS_NAMES and ATTRIBUTE_NAMES from all examples are the same. If not, more code logic is required for merging.

3) Create a single new examples object using the merged values:
properties = Dictionary()
properties['EXAMPLES'] = myExamples
properties['CLASS_VALUES'] = myClassValues
properties['CLASS_NAMES'] = myClassNames
properties['ATTRIBUTE_NAMES'] = myAttributeNames
properties['DESCRIPTION'] = myDescription

4) Shuffle and split the examples

5) Define and train the classifier

Thank you for the detailed reply, but I'm still having trouble getting the code to work. First, I noticed the ExtractExamplesFromRaster variable also has a ['DESCRIPTION'] key, should this be included?

For step 2 when you say to merge the examples, you mean to concatenate the arrays right? I believe I've correctly implemented the code logic for merging arrays, but even when I try to write a dictionary to use in the classifier with a single image I cannot get the Keys correct.


returns an error in the script so it won't compile, but when used in the console: properties.keys() returns 5 lines with the "keys". How do I fix the % Keys must be valid IDL variable names error?