This module is sensitive to the current region and mask settings, hence spatial extent and spatial resolution. In case the registered raster maps of the input space time raster dataset have different spatial resolutions, the default nearest neighbor resampling method is used for runtime spatial aggregation.
This module will shift the start date for each aggregation process depending on the provided temporal granularity. The following shifts will performed:
The specification of the temporal relation between the aggregation intervals and the raster map layers is always formulated from the aggregation interval viewpoint. Hence, the relation contains has to be specified to aggregate map layer that are temporally located in an aggregation interval.
Parallel processing is supported in case that more than one interval is available for aggregation computation. Internally several r.series modules will be started, depending on the number of specified parallel processes (nprocs) and the number of intervals to aggregate.
t.rast.aggregate in=tempmean_monthly out=tempmean_yearly basename=tempmean_year \ granularity='1 year' method=average t.support input=tempmean_yearly \ title="Yearly precipitation" \ description="Aggregated precipitation dataset with yearly resolution" t.info tempmean_yearly +-------------------- Space Time Raster Dataset -----------------------------+ | | +-------------------- Basic information -------------------------------------+ | Id: ........................ tempmean_yearly@climate_2000_2012 | Name: ...................... tempmean_yearly | Mapset: .................... climate_2000_2012 | Creator: ................... lucadelu | Temporal type: ............. absolute | Creation time: ............. 2014-11-27 10:25:21.243319 | Modification time:.......... 2014-11-27 10:25:21.862136 | Semantic type:.............. mean +-------------------- Absolute time -----------------------------------------+ | Start time:................. 2009-01-01 00:00:00 | End time:................... 2013-01-01 00:00:00 | Granularity:................ 1 year | Temporal type of maps:...... interval +-------------------- Spatial extent ----------------------------------------+ | North:...................... 320000.0 | South:...................... 10000.0 | East:.. .................... 935000.0 | West:....................... 120000.0 | Top:........................ 0.0 | Bottom:..................... 0.0 +-------------------- Metadata information ----------------------------------+ | Raster register table:...... raster_map_register_514082e62e864522a13c8123d1949dea | North-South resolution min:. 500.0 | North-South resolution max:. 500.0 | East-west resolution min:... 500.0 | East-west resolution max:... 500.0 | Minimum value min:.......... 7.370747 | Minimum value max:.......... 8.81603 | Maximum value min:.......... 17.111387 | Maximum value max:.......... 17.915511 | Aggregation type:........... average | Number of registered maps:.. 4 | | Title: Yearly precipitation | Monthly precipitation | Description: Aggregated precipitation dataset with yearly resolution | Dataset with monthly precipitation | Command history: | # 2014-11-27 10:25:21 | t.rast.aggregate in="tempmean_monthly" | out="tempmean_yearly" basename="tempmean_year" granularity="1 years" | method="average" | | # 2014-11-27 10:26:21 | t.support input=tempmean_yearly \ | title="Yearly precipitation" \ | description="Aggregated precipitation dataset with yearly resolution" +----------------------------------------------------------------------------+
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