The temporal GIS framework in GRASS introduces three new datatypes 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
prefix t.rast.
- 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
prefix t.vect.
Temporal data management in general
List of general management modules:
Space time datasets are stored in a temporal database. SQLite3 or
PostgreSQL are supported as SQL database back end.
Connection settings are performed with t.connect.
As default a sqlite3 database will be created in the PERMANENT mapset that
stores all space time datasets and registered time series maps from all
mapsets in the location.
New space time datasets can be 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. Optional the temporal type (absolute, relative)
and semantic informations can be provided. The module
t.remove will remove the space time datasets
from the temporal database. Use t.support
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.
You can rename a space time dataset with t.rename.
The module t.register was designed to
register raster, 3D raster and vector maps in the temporal database and
optionally in a space time dataset. It supports different input options. Maps
to register can be provided as a comma separated string on 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 or the temporal database.
To print informations 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 a space time datasets the
module t.topology was designed. The module
t.sample samples the input space time dataset(s)
with a sample space time dataset and print the result to standard output.
Several different sample methods are supported that can be combined.
Modules to process space time raster datasets
The focus of the temporal GIS framework is the processing and analysis of
raster time series. Hence several modules that process space time raster
datasets are implemented.
Querying and map calculation
Registered maps of a space time raster datasets can be listed using
t.rast.list. This module supports several
methods how the maps should be listed using SQL queries do determine how
they are selected and sorted. Subsets of space time raster datasets can
be extracted with t.rast.extract that
allows additionally to perform mapcalc operations on the selected raster
maps.
Aggregation
The temporal framework support 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
t.rast.aggregate. The module
t.rast.aggregate.ds allows the
aggregation of raster map series using the intervals of the maps (raster,
3D raster and vector) of a 2. space time dataset. A simple interface to
r.series is the module
t.rast.series that processes the whole
input space time raster dataset or a subset of it.
Export/import conversion
Statistics and gap filling