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Extracting raw data from an unsupervised classification of multiple Landsat scenes

Question asked by Dan_White on Apr 9, 2015
Latest reply on Apr 10, 2015 by Dan_White

Hi All, I'm trying to extract the raw data values for the 5 spectral bands of a Landsat scene that I have conducted an unsupervised iso-cluster unsupervised classification on.

 

I am looking into the variability of sea-ice using Landsat images.  One of the fundamental steps I need to do in order to achieve this is to classify the snow/ice/water based on its reflectance.  So far, I have run an unsupervised iso-cluster unsupervised classification based on 5 rasters, being the spectral bands 1,2,3,4 and 6, and have opted for 10 classes. What I need to achieve is a classification with enough classes that are statistically distinct from one another, which I can then use to classify the medium on all my other images.

 

As an example, I have a composite raster with 10 classes, each a product of the 5 bands as mentioned.  Class 1 has a count of 464285, but I would like to know for that class, what is the raw data value for each band within the composite image?'

 

Any advice greatly welcomed thanks!

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