I have a labelled classified data of the Sentinal -1 image after the maximum likelihood classification. I saved it in tif format as well. However, when I try to load this Data in ARCGIS, i don’t see the labelled information.
I want to do the accuray prediction of the classifier.
the labelling of the classes is something in the metadata of SNAP. This information is lost when you convert the data to GeoTiff. The raster only consists of integer numbers
It is not necessary to convert to GeoTiff: Please have a look at this related question: unsupervised classification
Thanks @ABraun for your reply. The image has been loaded with min as -1 and max as 3 value. I have 4 classes in my SNAP classifications ranging from 0-3. It is showing -1 as well .
I have taken the ROI using the sentinal 2 image and classified the images using maximum likehood algorithm in SNAP.
One image is the orignal sentinal 1 image terrain corrected.
The other image is the pre-processed sentinal 1 image with pre-processing( orbit file, calibration,speckle filtering lee filter,terrain correction)
Accuracy of orignal image= 67.2%
Accuracy of pre-processed image= 68.23%
There is not a huge difference in the results? I am wondering why is that happening?
Accuracy is almost same so why do we need to pre-process the image with so many steps.
Most of the preprocessing measures improve the quality of the image (geolocation, reduction of speckle) which are not directly visible in one single accuracy measure. The accuracy does not say much about speckle in the image, yet it makes sense to remove it before classifying. Similar for the calibration. Although you do not see the difference, it is good to reduce the impact of the incidence angle in your images so that similar pixels in near and far range are classified the same.