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Vector data processing in GRASS GIS
Vector maps in general
A "vector map" is a data layer consisting of a number of sparse features in geographic
space. These might be data points (drill sites), lines (roads), polygons (park boundary),
volumes (3D CAD structure), or some combination of all these. Typically each feature in
the map will be tied to a set of attribute layers stored in a database (road names, site
ID, geologic type, etc.). As a general rule these can exist in 2D or 3D space and are
independent of the GIS’s computation region.
Vector data import and export
The v.in.ogr module offers a common interface for many different vector formats.
Additionally, it offers options such as on-the-fly creation of new locations or extension
of the default region to match the extent of the imported vector map. For special cases,
other import modules are available, e.g. v.in.ascii for input from a text file containing
coordinate and attribute data, and v.in.db for input from a database containing coordinate
and attribute data. With v.external external maps can be virtually linked into a mapset,
only pseudo-topology is generated but the vector geometry is not imported. The v.out.*
set of commands exports to various formats. To import and export only attribute tables,
use db.in.ogr and db.out.ogr.
GRASS GIS vector map exchange between different locations (same projection) can be done in
a lossless way using the v.pack and v.unpack modules.
The naming convention for vector maps requires that map names start with a character, not
a number (map name scheme: [A-Za-z][A-Za-z0-9_]*).
Metadata
The v.info display general information such as metadata and attribute columns about a
vector map including the history how it was generated. Each map generating command stores
the command history into the metadata (query with v.info -h mapname). Metadata such as
map title, scale, organization etc. can be updated with v.support.
Vector map operations
GRASS vector map processing is always performed on the full map. If this is not desired,
the input map has to be clipped to the current region beforehand (v.in.region,
v.overlay,v.select).
Vector model and topology
GRASS is a topological GIS. This means that adjacent geographic components in a single
vector map are related. For example in a non-topological GIS if two areas shared a common
border that border would be digitized two times and also stored in duplicate. In a
topological GIS this border exists once and is shared between two areas. Topological
representation of vector data helps to produce and maintain vector maps with clean
geometry as well as enables certain analyses that can not be conducted with
non-topological or spaghetti data. In GRASS, topological data are referred to as level 2
data and spaghetti data is referred to as level 1.
Sometimes topology is not necessary and the additional memory and space requirements are
burdensome to a particular task. Therefore two modules allow for working level 1
(non-topological) data within GRASS. The v.in.ascii module allows users to input points
without building topology. This is very useful for large files where memory restrictions
may cause difficulties. The other module which works with level 1 data is v.surf.rst which
enables spatial approximation and topographic analysis from a point or isoline file.
In GRASS, the following vector object types are defined:
• point: a point;
• line: a directed sequence of connected vertices with two endpoints called nodes;
• boundary: the border line to describe an area;
• centroid: a point within a closed ring of boundaries;
• area: the topological composition of a closed ring of boundaries and a centroid;
• face: a 3D area;
• kernel: a 3D centroid in a volume (not yet implemented);
• volume: a 3D corpus, the topological composition of faces and kernel (not yet
implemented).
Lines and boundaries can be composed of multiple vertices.
Area topology also holds information about isles. These isles are located within that
area, not touching the boundaries of the outer area. Isles are holes inside the area, and
can consist of one or more areas. They are used internally to maintain correct topology
for areas.
The v.type module can be used to convert between vector types if possible. The v.build
module is used to generate topology. It optionally allows the user to extract erroneous
vector objects into a separate map. Topological errors can be corrected either manually
within wxGUI vector digitizer or, to some extent, automatically in v.clean. A dedicated
vector editing module is v.edit which supports global and local editing operations.
Adjacent polygons can be found by v.to.db (see ’sides’ option).
Many operations including extraction, queries, overlay, and export will only act on
features which have been assigned a category number. Typically a centroid will hold the
attribute data for the area with which the centroid is associated. Boundaries are not
typically given a category ID as it would be ambiguous as to which area either side of it
the attribute data would belong to. An exception might be when the boundary between two
crop-fields is the center-line of a road, and the category information is an index to the
road name. For everyday use boundaries and centroids can be treated as internal data types
and the user can work directly and more simply with the "area" type.
Vector object categories and attribute management
GRASS vectors can be linked to one or many database management systems (DBMS). The db.*
set of commands provides basic SQL support for attribute management, while the v.db.* set
of commands operates on a table linked to a vector map.
• Categories
Categories are used to categorize vector objects and link attribute(s) to each
category. Each vector object can have zero, one or several categories. Category
numbers do not have to be unique for each vector object, several vector objects
can share the same category.
Category numbers are stored both within the geometry file for each vector object
and within the (optional) attribute table(s) (usually the "cat" column). It is not
required that attribute table(s) hold an entry for each category, and attribute
table(s) can hold information about categories not present in the vector geometry
file. This means that e.g. an attribute table can be populated first and then
vector objects can be added to the geometry file with category numbers. Using
v.category, category numbers can be printed or maintained.
• Layers
Layers are a characteristic of the vector feature (geometries) file. As mentioned
above, categories allow the user to give either a unique id to each feature or to
group similar features by giving them all the same id. Layers allow several
parallel, but different groupings of features in a same map. The practical benefit
of this system is that it allows placement of thematically distinct but
topologically related objects into a single map, or for linking time series
attribute data to a series of locations that did not change over time.
For example, one can have roads with one layer containing the unique id of each
road and another layer with ids for specific routes that one might take, combining
several roads by assigning the same id. While this example can also be dealt with
in an attribute table, another example of the use of layers that shows their
specific advantage is the possibility to identify the same geometrical features as
representing different thematic objects. For example, in a map with a series of
polygons representing fields in which at the same time the boundaries of these
fields have a meaning as linear features, e.g. as paths, one can give a unique id
to each field as area in layer 1, and a unique id in layer 2 to those boundary
lines that are paths. If the paths will always depend on the field boundaries (and
might change if these boundaries change) then keeping them in the same map can be
helpful. Trying to reproduce the same functionality through attributes is much
more complicated.
If a vector object has zero categories in a layer, then it does not appear in that
layer. In this fashion some vector objects may appear in some layers but not in
others. Taking the example of the fields and paths, only some boundaries, but not
all, might have a category value in layer 2. With option=report, v.category lists
available categories in each layer.
Optionally, each layer can (but does not have to) be linked to an attribute table.
The link is made by the category values of the features in that layer which have
to have corresponding entries in the specified key column of the table. Using
v.db.connect connections between layers and attribute tables can be listed or
maintained.
In most modules, the first layer (layer=1) is active by default. Using layer=-1
one can access all layers.
• SQL support
The DBF driver provides only very limited SQL support (as DBF is not an SQL DB)
while the other DBMS backends (such as SQLite, PostgreSQL, MySQL etc) provide full
SQL support since the SQL commands are sent directly to the DBMI. SQL commands can
be directly executed with db.execute, db.select and the other db.* modules.
When creating vector maps from scratch, in general an attribute table must be created and
the table must be populated with one row per category (using v.to.db). However, this can
be performed in a single step using v.db.addtable along with the definition of table
column types. Column adding and dropping can be done with v.db.addcolumn and
v.db.dropcolumn. A table column can be renamed with v.db.renamecolumn. To drop a table
from a map, use v.db.droptable. Values in a table can be updated with v.db.update. Tables
can be joined with with v.db.join.
Editing vector attributes
To manually edit attributes of a table, the map has to be queried in ’edit mode’ using
d.what.vect. To bulk process attributes, it is recommended to use SQL (db.execute).
Geometry operations
The module v.in.region saves the current region extents as a vector area. Split vector
lines can be converted to polylines by v.build.polylines. Long lines can be split by
v.split and v.segment. Buffer and circles can be generated with v.buffer and v.parallel.
v.generalize is module for generalization of GRASS vector maps. 2D vector maps can be
changed to 3D using v.drape or v.extrude. If needed, the spatial position of vector
points can be perturbed by v.perturb. The v.type command changes between vector types
(see list above). Projected vector maps can be reprojected with v.proj. Unprojected maps
can be geocoded with v.transform. Based on the control points, v.rectify rectifies a
vector map by computing a coordinate transformation for each vector object. Triangulation
and point-to-polygon conversions can be done with v.delaunay, v.hull, and v.voronoi. The
v.random command generated random points.
Vector overlays and selections
Geometric overlay of vector maps is done with v.patch, v.overlay and v.select, depending
on the combination of vector types. Vectors can be extracted with v.extract and
reclassified with v.reclass.
Vector statistics
Statistics can be generated by v.qcount, v.sample, v.normal, v.univar, and v.vect.stats.
Distances between vector objects are calculated with v.distance.
Vector-Raster-DB conversion
The v.to.db transfers vector information into database tables. With v.to.points,
v.to.rast and v.to.rast3 conversions are performed. Note that a raster mask ("MASK") will
not be respected since it is only applied when reading an existing GRASS raster map.
Vector queries
Vector maps can be queried with v.what and v.what.vect.
Vector-Raster queries
Raster values can be transferred to vector maps with v.what.rast and v.rast.stats.
Vector network analysis
GRASS provides support for vector network analysis. The following algorithms are
implemented:
• Network preparation and maintenance: v.net
• Shortest path: d.path and v.net.path
• Shortest path between all pairs of nodes v.net.allpairs
• Allocation of sources (create subnetworks, e.g. police station zones): v.net.alloc
• Iso-distances (from centers): v.net.iso
• Computes bridges and articulation points: v.net.bridge
• Computes degree, centrality, betweeness, closeness and eigenvector centrality
measures: v.net.centrality
• Computes strongly and weakly connected components: v.net.components
• Computes vertex connectivity between two sets of nodes: v.net.connectivity
• Computes shortest distance via the network between the given sets of features:
v.net.distance
• Computes the maximum flow between two sets of nodes: v.net.flow
• Computes minimum spanning tree:v.net.spanningtree
• Minimum Steiner trees (star-like connections, e.g. broadband cable connections):
v.net.steiner
• Finds shortest path using timetables: v.net.timetable
• Traveling salesman (round trip): v.net.salesman
Vector directions are defined by the digitizing direction (a-->--b). Both directions are
supported, most network modules provide parameters to assign attribute columns to the
forward and backward direction.
Vector networks: Linear referencing system (LRS)
LRS uses linear features and distance measured along those features to positionate
objects. There are the commands v.lrs.create to create a linear reference system,
v.lrs.label to create stationing on the LRS, v.lrs.segment to create points/segments on
LRS, and v.lrs.where to find line id and real km+offset for given points in vector map
using linear reference system.
The LRS tutorial explains further details.
Interpolation and approximation
Some of the vector modules deal with spatial or volumetric approximation (also called
interpolation): v.kernel, v.surf.idw, v.surf.rst, and v.vol.rst.
Lidar data processing
Lidar point clouds (first and last return) are imported from text files with v.in.ascii or
from LAS files with v.in.lidar. Both modules recognize the -b flag to not build topology.
Outlier detection is done with v.outlier on both first and last return data. Then, with
v.lidar.edgedetection, edges are detected from last return data. The building are
generated by v.lidar.growing from detected edges. The resulting data are post-processed
with v.lidar.correction. Finally, the DTM and DSM are generated with v.surf.bspline (DTM:
uses the ’v.lidar.correction’ output; DSM: uses last return output from outlier
detection).
In addition, v.decimate can be used to decimates a point cloud.
See also
• Introduction to raster data processing
• Introduction to 3D raster data (voxel) processing
• Introduction to vector data processing
• Introduction to image processing
• Introduction into temporal data processing
• Introduction to database management
• Projections and spatial transformations
SOURCE CODE
Available at: Vector data processing in GRASS GIS source code (history)
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© 2003-2018 GRASS Development Team, GRASS GIS 7.4.0 Reference Manual