I am trying to run a supervised classification in SNAP. Every time I run the random forest classifier with vector trainning sites it classifies evrything as one class. I perform my classification as follows:
- atmospheric correction using Sen2cor stand alone processor
- load corrected image into snap and resample everything to 10m (using resampling tool under raster)
- I create a spatial subset to minimise the extent of the image
- I load trainning vectors and study site vector
- create a land/sea mask to isolate just my study site
- run a random forest supervised classifiction
After running the random forest supervised classification, I then changed the confidence>=0. It then shows that one class has a frequency of 100%. I have tried multiple times and each time it generates an output with a different class contaning a frequency of 100%. I have 7 classes each with varrying numbers of training vector shapefiles in it. I have seen people saying that you should reproject your sentinel 2 image however the projections on the image and the shapfiles is the same and when i do try to reproject the sentinel image, it does not work it just displays a grey screen with the odd pink/red, green or blue pixel.
Please could somone help me out here.