The temporal GIS framework in GRASS introduces three new datatypes that are designed to handle time series data:

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

See also