v.net.distance - Computes shortest distance via the network
between the given sets of features.
Finds the shortest paths from each ’from’ point to the nearest
’to’ feature and various information about this relation are
uploaded to the attribute table.
vector, network, shortest path
v.net.distance
v.net.distance --help
v.net.distance [-
gl]
input=
name
output=
name [
arc_layer=
string]
[
arc_type=
string[,
string,...]]
[
node_layer=
string] [
from_layer=
string]
[
from_cats=
range] [
from_where=
sql_query]
[
to_layer=
string]
[
to_type=
string[,
string,...]] [
to_cats=
range] [
to_where=
sql_query]
[
arc_column=
name] [
arc_backward_column=
name]
[
node_column=
name] [--
overwrite] [--
help]
[--
verbose] [--
quiet] [--
ui]
- -g
-
Use geodesic calculation for longitude-latitude locations
- -l
-
Write each output path as one line, not as original input segments.
- --overwrite
-
Allow output files to overwrite existing files
- --help
-
Print usage summary
- --verbose
-
Verbose module output
- --quiet
-
Quiet module output
- --ui
-
Force launching GUI dialog
- input=name [required]
-
Name of input vector map
Or data source for direct OGR access
- output=name [required]
-
Name for output vector map
- arc_layer=string
-
Arc layer
Vector features can have category values in different layers. This number
determines which layer to use. When used with direct OGR access this is
the layer name.
Default: 1
- arc_type=string[,string,...]
-
Arc type
Input feature type
Options: line, boundary
Default: line,boundary
- node_layer=string
-
Node layer
Vector features can have category values in different layers. This number
determines which layer to use. When used with direct OGR access this is
the layer name.
Default: 2
- from_layer=string
-
From layer number or name
Vector features can have category values in different layers. This number
determines which layer to use. When used with direct OGR access this is
the layer name.
Default: 1
- from_cats=range
-
From category values
Example: 1,3,7-9,13
- from_where=sql_query
-
From WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000
- to_layer=string
-
Layer number or name
To layer number or name
Default: 1
- to_type=string[,string,...]
-
To feature type
Options: point, line, boundary
Default: point
- to_cats=range
-
To category values
Example: 1,3,7-9,13
- to_where=sql_query
-
To WHERE conditions of SQL statement without ’where’ keyword
Example: income < 1000 and population >= 10000
- arc_column=name
-
Arc forward/both direction(s) cost column (number)
- arc_backward_column=name
-
Arc backward direction cost column (number)
- node_column=name
-
Node cost column (number)
v.net.distance finds the nearest element in set
to for every point
in set
from.
These two sets are given by the respective
layer,
where and
cats parameters. The type of
to features is specified by
to_type parameter. All
from features are
points. A table
is linked to
output map containing various information about the
relation. More specifically, the table has three columns:
cat,
tcat and
dist storing category of each
from feature,
category of the nearest
to feature and the distance between them
respectively.
Furthemore, the
output map contains the shortest path between each
cat,
tcat pair. Each path consists of several lines. If a line
is on the shortest path from a point then the category of this point is
assigned to the line. Note that every line may contain more than one category
value since a single line may be on the shortest path for more than one
from feature. And so the shortest paths can be easily obtained by
querying lines with corresponding category number. Alternatively, unique paths
can be created with the
-l flag where each path will be a separate
single line in the output.
The costs of arcs in forward and backward direction are specified by
arc_column and
arc_backward_column columns respectively. If
arc_backward_column is not given, the same cost is used in both
directions.
v.net.distance will not work if you are trying to find the nearest
neighbors within a group of nodes, i.e. where
to and
from are
the same set of nodes, as the closest node will be the node itself and the
result will be zero-length paths. In order to find nearest neighbors within a
group of nodes, you can either loop through each node as
to and all
other nodes as
from or create a complete distance matrix with
v.net.allpairs and select the lowest non-zero distance for each node.
Find shortest path and distance from every school to the nearest hospital and
show all paths.
Streets are grey lines, schools are green circles, hospitals are red crosses,
shortest paths are blue lines:
# connect schools to streets as layer 2
v.net input=streets_wake points=schools_wake output=streets_net1 \
operation=connect thresh=400 arc_layer=1 node_layer=2
# connect hospitals to streets as layer 3
v.net input=streets_net1 points=hospitals output=streets_net2 \
operation=connect thresh=400 arc_layer=1 node_layer=3
# inspect the result
v.category in=streets_net2 op=report
# shortest paths from schools (points in layer 2) to nearest hospitals (points in layer 3)
v.net.distance in=streets_net2 out=schools_to_hospitals flayer=2 to_layer=3
# visualization
g.region vector=streets_wake
d.mon wx0
d.vect streets_wake color=220:220:220
d.vect schools_wake color=green size=10
d.vect map=hospitals icon=basic/cross3 size=15 color=black fcolor=red
d.vect schools_to_hospitals
Example with streams of the NC sample data set.
# add coordinates of pollution point source of pollution as vector
pollution.txt:
634731.563206905|216390.501834892
v.in.ascii input=pollution.txt output=pollution
# add table to vector
v.db.addtable map=pollution
# add coordinates of sample points as vector
samples.txt:
634813.332814905|216333.590706166
634893.462007813|216273.763350851
634918.660011082|216254.949609689
v.in.ascii input=samples.txt output=samples
# add table to vector
v.db.addtable map=samples
# connect samples and pollution to streams
v.net -c input=streams points=samples output=streams_samples \
operation=connect node_layer=3 threshold=10 \
v.net -c input=streams_samples points=pollution
output=streams_samples_pollution operation=connect \
node_layer=4 threshold=10
# check vector layers
v.category input=streams_samples_pollution option=report
Layer/table: 1/streams_samples_pollution
type count min max
point 0 0 0
line 8562 40102 101351
boundary 0 0 0
centroid 0 0 0
area 0 0 0
face 0 0 0
kernel 0 0 0
all 8562 40102 101351
Layer: 3
type count min max
point 3 1 3
line 0 0 0
boundary 0 0 0
centroid 0 0 0
area 0 0 0
face 0 0 0
kernel 0 0 0
all 3 1 3
Layer: 4
type count min max
point 1 1 1
line 0 0 0
boundary 0 0 0
centroid 0 0 0
area 0 0 0
face 0 0 0
kernel 0 0 0
all 1 1 1
# calculate distance between sample points and pollution point source
v.net.distance input=streams_samples_pollution \
output=distance_samples_to_pollution from_layer=3 to_layer=4
# check results
v.report map=distance_samples_to_pollution@vnettest option=length
cat|tcat|dist|length
1|1|100.0|100.0
2|1|200.0|200.0
3|1|231.446|231.446
v.net.path, v.net.allpairs, v.net.distance,
v.net.alloc
Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor
Markus Metz
Last changed: $Date: 2017-01-15 16:02:25 +0100 (Sun, 15 Jan 2017) $
Available at: v.net.distance source code (history)
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