Thank you for your good response
I got the solution for that but, While doing the RF classification for the GRD products getting the error like bound must me positive, sorry I don’t know what it is
and also sorry for my lack of knowledge, I have one doubt the classification which we are doing is on what based will be classify?
is it color based or backscatter based? please give me some guidance.
radar data is not measurung colours, it operates at higher wavelenghts. The signal you retrieve (and the classification is based on) represents physical characteristics of the surfaces (roughness and moisture, among others). Rice, water and built-up structures have different types of backscatter mechanisms, so they should be separable quite well. Build-up structures cause corner reflection (very high backscatter), water is mostly smooth and rice produces volume scattering once crops are developed. Especially if you are using images of different dates, its signature will change and be therefore quite unique.
By default the “number of training samples” is 5000 in any classifier in SNAP. How does it effect the results exactly and if I increase it’s value, will the accuracy improve ?
hi team,
sorry for lack of knowledge,as per my concern while we are doing the classification by any technique, we need take vector samples, then only we can classify our products.
is there any technique to classify the products by giving the back-scatter ranges (like -14 db to -19 db & -24 db to -30 db ) only based on our requirement without giving any vector samples??
if any technique is there please help me to classify the products.
and one more question is after done the classification how can we see the statistics based on area wise.
please help me to do that process.
By the way, I will create ( sigma0VH / sigma0VV ) ratio band. Should I do it before GLCM or after?
After I calculate GLCM, I will do classification with using VH, VV and VH/VV ratio bands in dB scale. So I am a little confused. Should I create VH/VV band before GLCM to have entropy, energy, contrast etc values for VH/VV band and check if it improves my classification results.
The thing you should take in your consideration, this value whatever you selected doesn’t meet the minimum of all your input raster, that’s why I think some of your input will be out, I think the better solution is to switch to vector training,
I wanna to use RF to classfy the GRD of sentinel-1 ,the images can processed in the snap software whole now?please reply me as soon as possible.thanks in advance!
just as your advices ,I had do it on snap with RF to classfy the GRD products,my steps like :GRD-calibrated- GLCM-filtering-Muitilook-Terrain correction-RF(not train the samples),is it right?I wnna to classfy the product to 3 types.if not what should i do?
please reply me ,thanks in advance!