Makes sure that any two vertices of the vector layer are at least at distance given by the threshold value.
The algorithm moves nearby vertices to one location and adds vertices to segments that are passing around other
vertices within the threshold. It does not remove any vertices. Also, it does not modify geometries unless
needed (it does not snap coordinates to a grid).
This algorithm comes handy when doing vector overlay operations such as intersection, union or difference
to prevent possible topological errors caused by numerical errors if coordinates are very close to each other.
After running the algorithm some previously valid geometries may become invalid and therefore it may be useful
to run Fix geometries algorithm afterwards.
and reports counts of matched/unmatched features
This gives an explicit warning to users when features were not matched,
and optionally allows them to save non-matching features to a layer.
This algorithm returns the portion of a line (or curve) which falls
between the specified start and end distances (measured from the
beginning of the line).
Z and M values are linearly interpolated from existing values.
Refactor the existing "raster pixels to polygons" algorithm and
create a new "pixels to points" algorithm, which creates a point
feature at the center of every pixel. nodata pixels are skipped.
This algorithm creates copies of line features in a layer, by
creating multiple parallel versions of each feature. Each copy is offset
by a preset distance.
This algorithm creates copies of features in a layer, by
creating multiple offset versions of the feature. Each copy is displaced
by a preset amount in the x/y/z/m axis.
Adds two new algorithms, for filtering line/polygon vertices by their
M or Z values. A minimum and maximum M/Z value can be entered, and
if the vertices fall outside these ranges they will be discarded
from the output geometry.
Both min and max filter value can also be data defined, so can
vary per feature.
Adds a native k-means clustering algorithm.
Based on a port of PostGIS' ST_ClusterKMeans function, this
new algorithm adds a new cluster ID field to a set of input
features identify the feature's cluster based on the k-means
clustering approach. If non-point geometries are used as input,
the clustering is based off the centroid of the input geometries.
Converts a raster layer into a vector layer, with a polygon feature
corresponding to each pixel from the raster and a single field
containing the band value from the raster.
Sponsored by SMEC/SJ
