[GRASS-user] Workflow of a classification project with orthophotos
nikos.alexandris at felis.uni-freiburg.de
Wed Jul 16 10:50:56 EDT 2008
I would like to have a confirmation that my feet are on the ground when
I try to realise the following work-flow with G-FOSS. I want to classify
forest gaps out of orthophotos (...actually it's not my job but I want
to help somebody who intented to do all by hand or accept what "others"
say that this task cannot be done unless one utilises commercial
I have more than 300 tiles of a mosaic composed by on aerial imagery.
Unfortunately it is a mixture of different acquisitions (date) and has
significant contrast differences in some regions.
My class-scheme would be gaps, shadows of tree-stands withing the gaps
water, vegetation, urban surfaces.
I can not perform any normalisation the way I know it for some number of
pictures (e.g. for 3,4 satelliteimagery). First of all there are no
overlapping areas and I am not aware (practically) of any other method
to perform a colour balance.
Anyone struggling with normalisation, colour balancing issues without
having the meta-data (date of acquisition) nor the raw data?
1. Stretch colour orthophotos (8-bit R,G and B bands) from 0 to 255
values (weither with GDAL or import in GRASS' database and stretch
inside the DB)
2. Visually identify the different "groups" of images taken more or less
at the same time
I have some vector of interest areas which correspond to biger
admnistrative areas (images are from West-Central Germany, groups are
something like koblenz, trier, simmern and more).
3. Split the mosaic in the groups that include photos that present less
5. Segmentation with i.smap
6. Use r.texture as I think it will boost the accuracy of the
8. Some handwork to improve sampling
9. Re-Run segmentation, classification
10. Handwork to correct obvious errors
11. Voila the power of GFOSS ;-)
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