I’ve been reading the topics about synergic use of S1 and S2 data for land use and land cover analysis. Futhermore, I read the new tutorial by Sir. Andreas Braun, for combination of S1 data (http://step.esa.int/docs/tutorials/S1TBX Synergetic use of S1 (SAR) and S2 (optical) data Tutorial.pdf).
I intend to performe a fusion of S1 and S2 dataset for forest degradation/LULC mapping in amazon region in my final paper for Radar discipline. I’m master’s student.
The point is, can I perform a reverse PCA on SNAP for literaly fusion and not just combine the images in a stack or collocation? I intend to use a supervised classifier and assess the accurcy of fusioned and combined data, just like in this paper http://dx.doi.org/10.1080/15481603.2013.805589
I just know the tool for perform the PCA on stack data and obtain the components. Is it correct to apply the classifier on PCA bands?
Aditional information: I’ll use a SLC image and pre-processing it (apply orbit file, radiometric calibration, thermal noise removal, multilooking, terrain correction and linear to dB) and apply a atmospheric correction and resampling on S2 image.
Thank you for your attention guys!