On 29/10/14 15:05, Margherita Di Leo wrote:
Dear All,
I have to develop a classifier to detect olive tree canopies using
Geoeye-1 images. I had thought of segmentation and indeed the
segmentation is capable of separating and detecting canopies. However I
need now a classifier that retains only the segments that represent
olive trees. The range of values assigned to canopies is quite high and
doesn't follow a particular order, hence i haven't found an obvious
mapcalc rule so far. However, I have been reasoning about the particular
pattern that characterise olive orchards: olive trees are obviously
round, disposed on regular grids, at constant distance to each other,
and the canopies, although having different sizes (within a certain
range), are almost always well separated from each other. I am now
looking to a way to translate this concept into operational rule. I'm
sure that this is nothing new, so I was wondering if you could point me
relevant literature and existing tools to put this in practice.
Thank you in advance for any hints
Have you tried integrating variables concerning shape and size (cf some
of the v.to.db variables), texture (r.texture - unfortunately GRASS does
not propose texture measures for arbitrary polygons, but only for
fixed-size windows around pixels, but you can use average texture
measures within your segmentation polygons).
You should probably check Pietro's v.class.ml in addons [1]. You can
also look at the sample script I sent to the grass-users list a while
ago [2].
Just brainstorming here: maybe the r.li.* modules can be (ab)used for
such as task ?
[1]
https://trac.osgeo.org/grass/browser/grass-addons/grass7/vector/v.class.ml
[2] http://lists.osgeo.org/pipermail/grass-user/2013-October/069189.html
_______________________________________________
grass-user mailing list
[email protected]
http://lists.osgeo.org/mailman/listinfo/grass-user
