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
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_]*).
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
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,
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 represenation 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 refered 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 optionally 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).
Note that all lines and boundaries can be polylines (with vertices in between).
Area topology also holds information about isles. These isles are located
within that area, not touching the boundaries of the outer area. Isles
consist of one or more areas and 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 v.digit
or, to some extent, automatically in v.clean.
A dedicated vector editing module is v.edit
which supports global and local editing operations. Additionally,
new advanced topological operations are available in the
wxGUI vector digitizer.
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 between it and its
boundaries. 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"
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.
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.addcol and
v.db.dropcol. A table column can be renamed with
v.db.renamecol. 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
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 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
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
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.select and the other db.* modules.
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
The module v.in.region saves the
current region boundary into a vector area.
Split vector lines can be changes to polylines by
v.build.polylines. Long lines can be
split by v.split and
Buffer and circles can be generated with v.buffer
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
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.
Triangulation and point-to-polygon conversions can be done with v.delaunay, v.hull,
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.
Statistics can be generated by v.qcount,
Distances between vector objects are calculated with v.distance.
The v.to.db transfers vector information
into database tables.
v.to.rast and v.to.rast3
conversions are performed.
Vector maps can be queried with v.what and
Raster values can be transferred to vector maps with
Vector network analysis
GRASS provides support for vector network analysis. The following algorithms
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.
- Network preparation and maintenance: v.net
- Shortest path: d.path and
- Allocation of sources (create subnetworks, e.g. police station zones):
- Iso-distances (from centers): v.net.iso
- Minimum Steiner trees (star-like connections, e.g. broadband cable
- Traveling salesman (round trip): v.net.salesman
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,
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):
Lidar data processing
Lidar point clouds (first and last return) are imported from text files with v.in.ascii (use 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).
Main index - vector index - full index
© 2008-2012 GRASS Development Team