#1480: v.outlier - distinguish positive and negative outlier filtering from lidar point clouds -------------------------+-------------------------------------------------- Reporter: sbl | Owner: grass-dev@… Type: enhancement | Status: new Priority: normal | Milestone: 7.0.0 Component: Vector | Version: unspecified Keywords: review | Platform: All Cpu: All | -------------------------+-------------------------------------------------- Changes (by sbl):
* version: svn-develbranch6 => unspecified * milestone: 6.4.2 => 7.0.0 Comment: Recently we had another project where we got insufficient filtered LIDAR data, where especially returns from lower mountainous vegetation were classified as "ground return". Filtering only last return was already done in the classification process (applied by the LIDAR-operator) and therewith insufficient too. The multi-scale curvature classification (mcc) procedure developed by Evans & Hudak 2007 (PDF linked above) however helped filtering out at least some more vegetation returns. I created a GRASS 7 AddOn (python script) which applies the mcc procedure. It is not uploaded to svn yet and some more testing will be necessary in order to write a useful manual. But I could attach it as a prove of concept if that is of interest. However, it requires that the v.outlier.diff is applied. Therefore I would like to ask if the decision not to change v.outlier (because of the different concept of the module) could be reconsidered? The mcc-algorithm was really useful for us at least... -- Ticket URL: <http://trac.osgeo.org/grass/ticket/1480#comment:3> GRASS GIS <http://grass.osgeo.org> _______________________________________________ grass-dev mailing list grass-dev@lists.osgeo.org http://lists.osgeo.org/mailman/listinfo/grass-dev