Hello,
i would like to receive some feedback by expert users about a dense cloud classification tool on crop fields (as far as i know the worst possible scenario to apply the algorythm).
The crop field area i want to classify is 250m by 150m. The crop is 1.5m tall from ground level since it is june and it is almost ready to be cut! See "Crop field.jpg"
I used standard parameters like 8.5°, cell=100m and height = 1m in the classify ground point.
As you can see, there also some "trenches" which are supposed to help the algorythm.
After using the algorythm, i find a very strange result: trenches are classified as "vegetation", while crop is classified as ground, as you can see in the other jpg.
Question 1:How can this happen? Since ground is the lowest level, shouldnt this problem never happen?
Question 2: I have manually classified the crop field as "Low vegetation" and i have re-run the Dense Clould Classify tool. I was very careful not to select the trenches.
I thought that this "boost" would have helped the algorythm in refining the classication and maybe sort the problem. I have reapplied the classification tool and i got same results: looks like that manual intervention is ignored by algorythm. Is this confirmed? Can it be changed by any chance? It would improve a lot the results.
Thanks