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NAMEt.rast.aggregate - Aggregates temporally the maps of a space time raster dataset by a user defined granularity.KEYWORDStemporal, aggregation, raster, timeSYNOPSISt.rast.aggregatet.rast.aggregate --help t.rast.aggregate [-n] input=name output=name basename=string [suffix=string] granularity=string method=string [offset=integer] [nprocs=integer] [file_limit=integer] [sampling=name[,name,...]] [where=sql_query] [--overwrite] [--help] [--verbose] [--quiet] [--ui] Flags:
Parameters:
DESCRIPTIONt.rast.aggregate temporally aggregates space time raster datasets by a specific temporal granularity. This module support absolute and relative time. The temporal granularity of absolute time can be seconds, minutes, hours, days, weeks, months or years. Mixing of granularities eg. "1 year, 3 months 5 days" is not supported. In case of relative time the temporal unit of the input space time raster dataset is used. The granularity must be specified with an integer value.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. NOTESThe raster module r.series is used internally. Hence all aggregate methods of r.series are supported. See the r.series manual page for details.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. EXAMPLESAggregation of monthly data into yearly dataIn this example the user is going to aggregate monthly data into yearly data, running:t.rast.aggregate input=tempmean_monthly output=tempmean_yearly \ basename=tempmean_year \ granularity="1 years" 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 input="tempmean_monthly" | output="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" +----------------------------------------------------------------------------+ Different aggregations and map name suffix variantsExamples of resulting naming schemes for different aggregations when using the suffix option:Weekly aggregationt.rast.aggregate input=daily_temp output=weekly_avg_temp \ basename=weekly_avg_temp method=average granularity="1 weeks" t.rast.list weekly_avg_temp name|mapset|start_time|end_time weekly_avg_temp_2003_01|climate|2003-01-03 00:00:00|2003-01-10 00:00:00 weekly_avg_temp_2003_02|climate|2003-01-10 00:00:00|2003-01-17 00:00:00 weekly_avg_temp_2003_03|climate|2003-01-17 00:00:00|2003-01-24 00:00:00 weekly_avg_temp_2003_04|climate|2003-01-24 00:00:00|2003-01-31 00:00:00 weekly_avg_temp_2003_05|climate|2003-01-31 00:00:00|2003-02-07 00:00:00 weekly_avg_temp_2003_06|climate|2003-02-07 00:00:00|2003-02-14 00:00:00 weekly_avg_temp_2003_07|climate|2003-02-14 00:00:00|2003-02-21 00:00:00Variant with suffix set to granularity: t.rast.aggregate input=daily_temp output=weekly_avg_temp \ basename=weekly_avg_temp suffix=gran method=average \ granularity="1 weeks" t.rast.list weekly_avg_temp name|mapset|start_time|end_time weekly_avg_temp_2003_01_03|climate|2003-01-03 00:00:00|2003-01-10 00:00:00 weekly_avg_temp_2003_01_10|climate|2003-01-10 00:00:00|2003-01-17 00:00:00 weekly_avg_temp_2003_01_17|climate|2003-01-17 00:00:00|2003-01-24 00:00:00 weekly_avg_temp_2003_01_24|climate|2003-01-24 00:00:00|2003-01-31 00:00:00 weekly_avg_temp_2003_01_31|climate|2003-01-31 00:00:00|2003-02-07 00:00:00 weekly_avg_temp_2003_02_07|climate|2003-02-07 00:00:00|2003-02-14 00:00:00 weekly_avg_temp_2003_02_14|climate|2003-02-14 00:00:00|2003-02-21 00:00:00 Monthly aggregationt.rast.aggregate input=daily_temp output=monthly_avg_temp \ basename=monthly_avg_temp suffix=gran method=average \ granularity="1 months" t.rast.list monthly_avg_temp name|mapset|start_time|end_time monthly_avg_temp_2003_01|climate|2003-01-01 00:00:00|2003-02-01 00:00:00 monthly_avg_temp_2003_02|climate|2003-02-01 00:00:00|2003-03-01 00:00:00 monthly_avg_temp_2003_03|climate|2003-03-01 00:00:00|2003-04-01 00:00:00 monthly_avg_temp_2003_04|climate|2003-04-01 00:00:00|2003-05-01 00:00:00 monthly_avg_temp_2003_05|climate|2003-05-01 00:00:00|2003-06-01 00:00:00 monthly_avg_temp_2003_06|climate|2003-06-01 00:00:00|2003-07-01 00:00:00 Yearly aggregationt.rast.aggregate input=daily_temp output=yearly_avg_temp \ basename=yearly_avg_temp suffix=gran method=average \ granularity="1 years" t.rast.list yearly_avg_temp name|mapset|start_time|end_time yearly_avg_temp_2003|climate|2003-01-01 00:00:00|2004-01-01 00:00:00 yearly_avg_temp_2004|climate|2004-01-01 00:00:00|2005-01-01 00:00:00 SEE ALSOt.rast.aggregate.ds, t.rast.extract, t.info, r.series, g.region, r.maskTemporal data processing Wiki AUTHORSören Gebbert, Thünen Institute of Climate-Smart AgricultureSOURCE CODEAvailable at: t.rast.aggregate source code (history)Main index | Temporal index | Topics index | Keywords index | Graphical index | Full index © 2003-2021 GRASS Development Team, GRASS GIS 7.8.6 Reference Manual
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