Hi, Here's the process I plan to do for my image classification
1. Create an unsupervised classification from TCAP images to get clusters of pure pixel values. 2. Convert to vector. 3. Create a random location of vector points. 4. From the converted vector layer, select random polygons (approximately 60 polys for each class). 5. Label training polygons for the desired classification classes 6. Run smap classification I will be running this method for a series of LANDSAT images (one tile at a time). My problem is by converting the whole image from raster to vector areas, the v.to.rast module reports "Killed" and could not complete the conversion. This maybe due to the whole image being large. Type of Map: raster Number of Categories: 47 | | Data Type: CELL | | Rows: 7518 | | Columns: 8504 | | Total Cells: 63933072 | | Projection: UTM (zone 51) | | N: 746814 S: 532551 Res: 28.5 | | E: 857451 W: 615087 Res: 28.5 | | Range of data: min = 1 max = 47 I've tried r.neighbors to reduce number of areas with less than 1-10 pixels, but this process outputs vectors layers with mixed pixel values, thus making it difficult to use in MLC or SMAP as training areas. What I need is to, limit raster to vector conversion to the desired randomly selected locations only. So that r.to.vect could complete the conversion. Any ideas? maning -- |---------|----------------------------------------------------------| | __.-._ |"Ohhh. Great warrior. Wars not make one great." -Yoda | | '-._"7' |"Freedom is still the most radical idea of all" -N.Branden| | /'.-c |Linux registered user #402901, http://counter.li.org/ | | | /T |http://esambale.wikispaces.com| | _)_/LI |---------|----------------------------------------------------------| _______________________________________________ grass-user mailing list grass-user@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-user