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v.distance - Finds the nearest element in vector map ’to’ for elements in vector map ’from’.
vector, distance, database, attribute table
v.distance v.distance --help v.distance [-pa] from=name [from_layer=string] [from_type=string[,string,...]] to=name [to_layer=string] [to_type=string[,string,...]] [output=name] [dmax=float] [dmin=float] [upload=string[,string,...]] [column=name[,name,...]] [to_column=name] [table=name] [separator=character] [--overwrite] [--help] [--verbose] [--quiet] [--ui] Flags: -p Print output to stdout, don’t update attribute table First column is always category of ’from’ feature called from_cat -a Calculate distances to all features within the threshold Output may be written to stdout using the ’-p’ flag or uploaded to a new table created by the ’table’ option; multiple ’upload’ options may be used. --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 Parameters: from=name [required] Name of existing vector map (from) Or data source for direct OGR access from_layer=string Layer number or name (from) 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_type=string[,string,...] Feature type (from) Input feature type Options: point, line, boundary, centroid, area Default: point,line,area to=name [required] Name of existing vector map (to) Or data source for direct OGR access to_layer=string Layer number or name (to) 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 to_type=string[,string,...] Feature type (to) Input feature type Options: point, line, boundary, centroid, area Default: point,line,area output=name Name for output vector map containing lines connecting nearest elements dmax=float Maximum distance or -1 for no limit Map units, meters for ll Default: -1 dmin=float Minimum distance or -1 for no limit Map units, meters for ll Default: -1 upload=string[,string,...] Values describing the relation between two nearest features Options: cat, dist, to_x, to_y, to_along, to_angle, to_attr cat: category of the nearest feature dist: minimum distance to nearest feature to_x: x coordinate of the nearest point on the ’to’ feature to_y: y coordinate of the nearest point on the ’to’ feature to_along: distance to the nearest point on the ’to’ feature along that linear feature to_angle: angle along the nearest linear feature in the ’to’ map, measured CCW from the +x axis, in radians, between -Pi and Pi inclusive to_attr: attribute of nearest feature given by to_column option column=name[,name,...] Column name(s) where values specified by ’upload’ option will be uploaded to_column=name Column name of nearest feature (used with upload=to_attr) table=name Name for new attribute table separator=character Field separator for printing output to stdout Special characters: pipe, comma, space, tab, newline Default: pipe
v.distance finds the nearest element in vector map (to) for elements in vector map (from). Various information about the vectors’ relationships (distance, category, etc.) may be uploaded to the attribute table attached to the first vector map, or printed to ’stdout’. A new vector map may be created where lines connecting nearest points on features are written. dmin and/or dmax can be used to limit the search radius (in lat-long locations to be given in meters since they are calculated as geodesic distances on a sphere). For lines to lines, say line A to line B, v.distance calculates the shortest distance of each vertex in A with each segment (not vertex) in B. The module then calculates the shortest distance of each vertex in B to each segment in A. The overall shortest distance of A points to B segments and B points to A segments is used. Additionally, v.distance checks for intersections. In case of intersections, the first intersection found is used and the distance set to zero. For lines to areas, the distance is set to zero if a line is (partially) inside an area. The first point of the line that is inside the area is used as common point. The distance is also set to zero if the line intersects with the outer ring or any of the inner rings (isles), in which case the fist intersection is used as common point. For areas to areas, the module checks first for overlap or if one area is (partially) inside the other area. This is computationally quite intensive. If the outer rings of the two areas do not overlap, the distance is calculated as above for lines to lines, treating the outer rings as two lines. Again, the first point encountered falling into an area is used as common point, or the first intersection point. For anything else than points to lines, there can be several common locations with zero distance, and the common location would then be the result of an overlay consisting of several points, lines, or areas. v.distance selects in these cases a single point, and does not create an overlay like v.overlay. In this implementation, any shared point is as good as any other. Calculating an intersection is costlier than to check if a vertex is inside a polygon. For example, if a vertex of the boundary of the ’to’ area is inside the ’from’ area, it is a common location. For speed reasons, the distance is then set to zero and no further tests are done.
If a nearest feature does not have a category, the attribute column is updated to NULL. The upload column(s) must already exist. Create one with v.db.addcolumn. In lat-long locations v.distance gives distances (dist, from_along, and to_along) not in degrees but in meters calculated as geodesic distances on a sphere. If one or both of the input vector maps are 3D, the user is notified accordingly.
Find nearest lines Find nearest lines in vector map "ln" for points from vector map "pnt" within the given threshold and write related line categories to column "linecat" in an attribute table attached to vector map "pnt": v.distance from=pnt to=ln upload=cat column=linecat Find nearest area For each point from vector map "pnt", find the nearest area from map "ar" within the given threshold and write the related area categories to column "areacat" in an attribute table attached to vector map "pnt" (in the case that a point falls into an area, the distance is zero): v.distance from=pnt to=ar upload=cat column=areacat Create a new vector map Create a new vector map which contains lines connecting nearest features of maps "pnt" and map "ln". The resulting vector map can be used for example to connect points to a network as needed for network analysis: v.distance from=pnt to=ln out=connections upload=dist column=dist Create a new vector map with from and to categories in the attribute table Create a new vector map that contains lines connecting nearest features of maps "pnt" and map "ln", and a new attribute table that contains distances, from and to categories from the input maps: v.distance from=pnt to=ln out=connections upload=cat,dist column=to_cat,dist table=connections Query information Query information from selected point(s). v.distance takes points from a vector map as input instead of stdin. A new vector map with query points has to be created before the map can be analysed. Create query map (if not present): echo "123456|654321|1" | v.in.ascii output=pnt Find nearest features: v.distance -p from=pnt to=map_to_query upload=cat Point-in-polygon The option dmax=0 is here important because otherwise for points not falling into any area, the category of the nearest area is recorded. For each point from vector map "pnt", find the area from vector map "ar" in which the individual point falls, and write the related area categories to column "areacat" into the attribute table attached to vector map "pnt": v.distance from=pnt to=ar dmax=0 upload=cat column=areacat Univariate statistics on results Create a vector map containing connecting lines and investigate mean distance to targets. An alternative solution is to use the v.distance upload=dist option to upload distances into the bugs vector directly, then run v.univar on that. Also note you can upload two columns at a time, e.g. v.distance upload=cat,dist column=nearest_id,dist_to_nr. # create working copy g.copy vect=bugsites,bugs # add new attribute column to hold nearest archsite category number v.db.addcolumn map=bugs column="nrst_arch INTEGER" v.distance from=bugs to=archsites to_type=point upload=to_attr \ to_column=cat column=nrst_arch out=vdistance_vectors_raw # we need to give the lines category numbers, create a table, and create # a column in that table to hold the distance data. v.category vdistance_vectors_raw out=vdistance_vectors type=line op=add g.remove -f type=vector name=vdistance_vectors_raw v.db.addtable map=vdistance_vectors column="length DOUBLE" v.to.db map=vdistance_vectors option=length column=length # calculcate statistics. Use v.univar.sh for extended statistics. v.univar vdistance_vectors column=length Print distance between points Example for a Latitude-longitude location (EPSG 4326): # points along the equator echo "0|-61|1" | v.in.ascii output=pnt1 input=- echo "0|-58|1" | v.in.ascii output=pnt2 input=- # here, distances are in degree units v.distance -p --q from=pnt1 to=pnt2 upload=dist from_cat|distance 1|3 Print distance matrix Note: Matrix-style output is enabled only for flag -a and one given upload option. Spearfish sample data location: v.distance -pa from=archsites to=archsites upload=dist North Carolina sample data location: v.distance -pa from=hospitals to=hospitals upload=dist separator=tab from_cat to_cat dist 1 2 3 4 5 ... 1 0 7489.10 339112.17 70900.39 70406.23 ... 2 7489.10 0 345749.12 76025.46 75538.87 ... 3 339112.17 345749.12 0 274153.19 274558.98 ... 4 70900.39 76025.46 274153.19 0 501.11 ... 5 70406.23 75538.87 274558.98 501.11 0 ... ...
r.distance, v.db.addcolumn, v.what.vect
Janne Soimasuo 1994, University of Joensuu, Faculty of Forestry, Finland Cmd line coordinates support: Markus Neteler, ITC-irst, Trento, Italy Updated for 5.1: Radim Blazek, ITC-irst, Trento, Italy Matrix-like output by Martin Landa, FBK-irst, Trento, Italy Improved processing speed: Markus Metz Distance from any feature to any feature: Markus Metz New table without the -p flag: Huidae Cho Last changed: $Date: 2017-02-19 22:47:27 +0100 (Sun, 19 Feb 2017) $
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