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NAME
v.net.distance - Computes shortest distance via the network between the given sets of features.
Finds the shortest paths from a feature 'to' to every feature 'from' and various information about this realtion are uploaded to the attribute table.
KEYWORDS
vector, network, shortest path
SYNOPSIS
v.net.distance
v.net.distance help
v.net.distance [-g] input=name output=name [from_layer=integer] [from_cats=range] [from_where=sql_query] [to_layer=integer] [to_cats=range] [to_where=sql_query] [to_type=string[,string,...]] afcolumn=name [abcolumn=name] [--overwrite] [--verbose] [--quiet]
Flags:
- -g
- Use geodesic calculation for longitude-latitude locations
- --overwrite
- Allow output files to overwrite existing files
- --verbose
- Verbose module output
- --quiet
- Quiet module output
Parameters:
- input=name
- Name of input vector map
- output=name
- Name for output vector map
- from_layer=integer
- From layer number or name
- A single vector map can be connected to multiple database tables. This number determines which table to use.
- 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 inhab >= 10000
- to_layer=integer
- Layer number
- To layer number or name
- Default: 1
- 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 inhab >= 10000
- to_type=string[,string,...]
- To feature type
- Options: point,line,boundary
- Default: point
- afcolumn=name
- Arc forward/both direction(s) cost column
- abcolumn=name
- Arc backward direction cost column
DESCRIPTION
v.net.distance finds the nearest element in set to
for every point in set from.
NOTES
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, output map
contains the shorest path between each cat, tcat
pair. Each path consist of several lines. If a line is on the
shorest 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.
The costs of arcs in forward and backward direction are specified by
afcolumn and abcolumn columns respectively. If
abcolumn 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.
EXAMPLES
Find shortest path and distance from every school to the nearest
hospital and show path from school number one.
v.net.distance input=city output=nearest from_where="type=school" \
to_where="type=hospital" afcolumn=SHAPE_LEN
d.vect nearest cats=1
SEE ALSO
v.net.path,
v.net.allpairs,
v.net.distance,
v.net.alloc
AUTHORS
Daniel Bundala, Google Summer of Code 2009, Student
Wolf Bergenheim, Mentor
Last changed: $Date: 2013-05-23 13:01:55 -0700 (Thu, 23 May 2013) $
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