On 12/02/14 13:41, Nikos Alexandris wrote:
Salut GRASSers,
Moritz Lennert wrote:
[..]
With all the elements in place, especially with Pietro's recent work, it
should be quite easy to create a unifying module 'i.segment.classify'
which would take as input
- the segments coming out of i.segment
- training zones
- a choice of variables
- a choice of classifier
would then calculate the chosen variables, submit the results to the
classifier and then update the segment map attribute table with the
classification result. In other words a frontend combining v.to.db,
v.rast.stats, v.class.ml and possibly some others.
As another alternative way, so as to stay in the Raster world, what do you
think of simply using "r.statistics2" and providing an input "cover=" map
in order to derive segment-oriented statistics and use'm further, for example
in an unsupervised classification scheme?
Well, actually v.rast.stats uses r.univar with zonal stats, so it also
goes through the raster world...
The vector approach does make it easier to calculate shape-related
variables too. It also has the advantage of having just one vector map
with all variables in the form of attributes instead of as many raster
maps as you have attributes.
But as always, everyone has to see what suits them best.
Moritz
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