Dear GRASSers, 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 tools... !)
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? My workflow 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 colour differences 4. Sampling 5. Segmentation with i.smap 6. Use r.texture as I think it will boost the accuracy of the classification 7. Classify 8. Some handwork to improve sampling 9. Re-Run segmentation, classification 10. Handwork to correct obvious errors 11. Voila the power of GFOSS ;-) Cheers, Nikos _______________________________________________ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user