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t.rast.series(1grass) | Grass User's Manual | t.rast.series(1grass) |
NAME¶
t.rast.series - Performs different aggregation algorithms from r.series on all or a subset of raster maps in a space time raster dataset.KEYWORDS¶
temporal, aggregation, series, raster, timeSYNOPSIS¶
t.rast.seriest.rast.series --help
t.rast.series [-tn] input=name method=string [quantile=float] [order=string[,string,...]] [where=sql_query] output=name [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:¶
- -t
-
Do not assign the space time raster dataset start and end time to the output map - -n
-
Propagate NULLs - --overwrite
-
Allow output files to overwrite existing files - --help
-
Print usage summary - --verbose
-
Verbose module output - --quiet
-
Quiet module output - --ui
-
Force launching GUI dialog
Parameters:¶
- input=name [required]
-
Name of the input space time raster dataset - method=string [required]
-
Aggregate operation to be performed on the raster maps
Options: average, count, median, mode, minimum, min_raster, maximum, max_raster, stddev, range, sum, variance, diversity, slope, offset, detcoeff, quart1, quart3, perc90, quantile, skewness, kurtosis
Default: average - quantile=float
-
Quantile to calculate for method=quantile
Options: 0.0-1.0 - order=string[,string,...]
-
Sort the maps by category
Options: id, name, creator, mapset, creation_time, modification_time, start_time, end_time, north, south, west, east, min, max
Default: start_time - where=sql_query
-
WHERE conditions of SQL statement without ’where’ keyword used in the temporal GIS framework
Example: start_time > ’2001-01-01 12:30:00’ - output=name [required]
-
Name for output raster map
DESCRIPTION¶
t.rast.series is a simple wrapper for the raster module r.series. It supports a subset of the aggregation methods of r.series.The input of this module is a single space time raster dataset, the output is a single raster map layer. A subset of the input space time raster dataset can be selected using the where option. The sorting of the raster map layer can be set using the order option. Be aware that the order of the maps can significantly influence the result of the aggregation (e.g.: slope). By default the maps are ordered by start_time.
EXAMPLE¶
Estimate average temperature for the whole time seriest.rast.series input=tempmean_monthly output=tempmean_general method=averageEstimate average temperature for all January maps in the time series, the so-called climatology
t.rast.series input=tempmean_monthly \ method=average output=tempmean_january \ where="strftime(’%m’, start_time)=’01’" # equivalently, we can use t.rast.series input=tempmean_monthly \ output=tempmean_january method=average \ where="start_time = datetime(start_time, ’start of year’, ’0 month’)" # if we want also February and March averages t.rast.series input=tempmean_monthly \ output=tempmean_february method=average \ where="start_time = datetime(start_time, ’start of year’, ’1 month’)" t.rast.series input=tempmean_monthly \ output=tempmean_march method=average \ where="start_time = datetime(start_time, ’start of year’, ’2 month’)"Generalizing a bit, we can estimate monthly climatologies for all months by means of different methods
for i in `seq -w 1 12` ; do for m in average stddev minimum maximum ; do t.rast.series input=tempmean_monthly method=${m} output=tempmean_${m}_${i} \ where="strftime(’%m’, start_time)=’${i}’" done done
SEE ALSO¶
r.series, t.create, t.infoTemporal data processing Wiki
AUTHOR¶
Sören Gebbert, Thünen Institute of Climate-Smart AgricultureLast changed: $Date: 2016-01-13 00:28:48 +0100 (Wed, 13 Jan 2016) $
SOURCE CODE¶
Available at: t.rast.series source code (history)Main index | Temporal index | Topics index | Keywords index | Graphical index | Full index
© 2003-2019 GRASS Development Team, GRASS GIS 7.6.0 Reference Manual
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