Hi, I am a new SNAP user trying to do a Random Forest Classification.
For that, I preprocessed the image I want to classify and I created a shapefile with the ROI in QGIS.
I am trying the train on vectors classification. For that, I have found the following problems or doubts:
What do I need to put in -vector training , training vectors-? (which file and its format)
I thought I should put my ROI shapefile or something like this, but, I cannot open any shapefile with the program. (please let me know how to open them)
2- What do i need to put in -feature selection, feature bands-? (again file and format).
To avoid the "javax.imageio.IIOException: 16-bit samples are not supported for Horizontal differencing Predictor " error I introduced all the individual bands I want to do the classification to (it is a total of 29 bands); then I imported my AOI (polygon shapefiles) while selecting one of those bands, then I finally was able to run the classification.
Everything seemed to work well except for the results; I ended up with 2 bands: LabeledClasses and Confidence. When I export this file into a tiff, I obtain a black image without data. The same happens in SNAP.
For the classification i am using 29 raster bands, belonging to 6 different rasters: NDVI, NDBI, NDWI percentil 50 and 90, sentinel 1 and sentinel 2 images and tasseled components images aswel.
The AOI are shapefile polygons created with QGIS and I am importing them into my first raster band
I’ve been using SNAP to compare the results of Random Forest classifications of Landsat’s 8 and 9. Both images have different number of pixels, so I can’t band math them. How can I solve it?
Also, is there a way to turn these LabeledClasses images to a shapefile or vector data?