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!
Hi Daniel,
Class Probability should be a useful tool for what you are trying to accomplish. You might also take a look at the Zonal Statistics or Zonal Statistics as Table tools in the Spatial Analyst Zonal toolset. You can get at a variety of descriptive stats for each class by using your classes as the input zones. I think the two tools only work on single band rasters so you would need to run each Landsat band individually.