There are opensource tools that can extract features from hires imagery, an example is GRASS, see this sample process (ignore the subjectline :))
http://lists.osgeo.org/pipermail/grass-user/2007-August/040808.html But this requires, that you have direct access to the imagery (which isn't legally allowed with Bing) Another option for small areas is to try balloon/kite mapping: http://grassrootsmapping.org/ In my experience, the most effective way is by manually tracing in JOSM (no computer algorithm can do what a human can see, at least not yet) and of course ground validation. On Fri, Feb 8, 2013 at 1:51 PM, Ryan Sommerville <[email protected]> wrote: > Hi all, > We're working on digitizing all building footprints in the Kathmandy > Valley. The current Bing imagery makes this a challenge in some areas, > especially densely packed neighborhoods. > > If possible, we'll utilize an automatic extraction of footprints and are > working on this now along with specific validation of that extraction. This > will still leave many buildings untraced (especially in dense neighborhoods) > so we'll also need to manually trace many buildings. The imagery sometimes > shows a clear building boundary but often it is unclear. > > Does anyone know of a methodology to accurately trace footprints using low > resolution imagery through a combination of mapping technique and > validation? > > Is it possible to add to the Buildings_Tools plugin to tag traces which will > require field verification? > > Any advice or suggestions is much appreciated! > > Thanks, > Ryan > > _______________________________________________ > HOT mailing list > [email protected] > http://lists.openstreetmap.org/listinfo/hot > -- cheers, maning ------------------------------------------------------ "Freedom is still the most radical idea of all" -N.Branden wiki: http://esambale.wikispaces.com/ blog: http://epsg4253.wordpress.com/ ------------------------------------------------------ _______________________________________________ HOT mailing list [email protected] http://lists.openstreetmap.org/listinfo/hot
