Temporal data processing in GRASS GIS
The temporal enabled GRASS introduces three new data types that
are designed to handle time series data:
- Space time raster datasets (strds) are designed to manage
raster map time series. Modules that process strds have the naming
- Space time 3D raster datasets (str3ds) are designed to
manage 3D raster map time series. Modules that process str3ds have the
naming prefix t.rast3d.
- Space time vector datasets (stvds) are designed to manage
vector map time series. Modules that process stvds have the naming
These new data types can be managed, analyzed and processed with temporal modules that
are based on the GRASS GIS temporal framework.
Space time datasets are stored in a temporal database. A core principle of the
temporal framework is that temporal databases are mapset specific. A new temporal
database is created when a temporal command is invoked in a mapset that does not
contain any temporal databases yet. For example, when a mapset was recently created.
Therefore, as space-time datasets are mapset specific, they can only register
raster, 3D raster or vector maps from the same mapset.
By default, space-time datasets can not register maps from other mapsets. This is
a security measure, since the registration of maps in a space-time dataset will
always modify the metadata of the registered map. This is critical if:
The user has no write access to the maps from other mapsets he wants to register
If registered maps are removed from other mapsets, the temporal database will not be updated
and will contain ghost maps
SQLite3 or PostgreSQL are supported as temporal database backends.
Temporal databases stored in other mapsets can be accessed as long as those
other mapsets are in the user's current mapset search path (managed with
). Access to space-time datasets from
other mapsets is read-only. They can not be modified or removed.
Connection settings are performed with t.connect.
As default, a SQLite3 database will be created in the current mapset that
stores all space-time datasets and registered time series maps.
New space-time datasets are created in the temporal database with
t.create. The name of the new dataset, the
type (strds, str3ds, stvds), the title and the description must be
provided for creation. Optionally, the temporal type (absolute, relative)
and the semantic information can be provided.
The module t.register is designed to
register raster, 3D raster and vector maps in the temporal database and
in the space-time datasets. It supports different input options. Maps
to register can be provided as a comma separated string at the command line, or
in an input file. The module supports the definition of time stamps
(time instances or intervals) for each map in the input file.
With t.unregister maps can be unregistered
from space-time datasets and from the temporal database.
Use only temporal commands like t.register to attach a time stamp to
raster, 3D raster and vector maps. The commands r.timestamp, r3.timestamp and
v.timestamp should not be used, since they do not register maps in
the temporal database and modify only the metadata of the map in the
spatial database. However, maps with timestamps attached with *.timestamp modules
can be registered in space-time datasets using the existing timestamp.
The module t.remove will remove the space-time datasets
from the temporal database and optionally all registered maps. It will take care
of multiple map registration, hence if maps are registered in several space-time
datasets in the current mapset.
to modify the metadata of space time datasets or to update the metadata
that is derived from registered maps. This module also checks for removed
and modified maps and updates the space-time datasets accordingly.
Rename a space-time dataset with t.rename.
To print information about space-time datasets or registered maps, the
module t.info can be used.
t.list will list all space-time datasets and
registered maps in the temporal database.
To compute and check the temporal topology of space-time datasets the
module t.topology was designed. The module
t.sample samples input space-time dataset(s)
with a sample space-time dataset and prints the result to standard output.
Different sampling methods are supported and can be combined.
List of general management modules:
The focus of the temporal GIS framework is the processing and analysis of
raster time series. Hence, the majority of the temporal modules are designed
to process space-time raster datasets. However, there are several modules to
process space-time 3D raster datasets and space-time vector datasets.
Querying and map calculation
Registered maps of a space-time raster dataset can be listed using
. This module supports several
methods to list maps and uses SQL queries to determine how these maps
are selected and sorted. Subsets of space-time raster datasets can
be extracted with t.rast.extract
allows performing additional mapcalc operations on the selected raster
Moreover, there is v.what.strds
, that uploads
space-time raster dataset values at positions of vector points, to the
attribute table of the vector map.
Aggregation and accumulation analysis
The temporal framework supports the aggregation of space-time raster
datasets. It provides three modules to perform aggregation using different
approaches. To aggregate a space-time raster map using a temporal
granularity like 4 months, 7 days and so on use
. The module
aggregation of a raster map time series using the intervals of the maps (raster,
3D raster and vector) of another space-time dataset. A simple interface to
is the module
that processes the whole
input space-time raster dataset or a subset of it.
Space-time raster datasets can be exported with t.rast.export
as a compressed tar archive. Such archives can then be imported
The module t.rast.to.rast3 converts
space-time raster datasets into space-time voxel cubes. All 3D raster modules
can be used to process such voxel cubes. This conversion allows the export of
space-time raster datasets as netCDF files that include time as one dimension.
Statistics and gap filling
Several space-time vector dataset modules were developed to allow the handling
of vector time series data.
The space-time 3D raster dataset modules are doing exactly the same as their
raster pendants, but with 3D raster map layers:
Available at: Temporal data processing in GRASS GIS source code (history)
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GRASS Development Team,
GRASS GIS 7.2.3svn Reference Manual