[GRASS-user] detecting olive trees from satellite imagery

Moritz Lennert mlennert at club.worldonline.be
Wed Oct 29 08:51:31 PDT 2014

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 ?

[2] http://lists.osgeo.org/pipermail/grass-user/2013-October/069189.html

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