NAME
t.rast.series.py - Performs different aggregation algorithms from r.series on all or a subset of raster maps in a space time raster dataset.
KEYWORDS
temporal,
series,
raster,
time
SYNOPSIS
t.rast.series.py
t.rast.series.py --help
t.rast.series.py [-tn] input=name method=string [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
- 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
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 for monthly aggregation with complex
where statements
to aggregate a single month in a time series of several years:
# January averages
t.rast.series input=tempmean_monthly \
output=jan_average method=average \
where="start_time = datetime(start_time, 'start of year', '0 month')"
# February averages
t.rast.series input=tempmean_monthly \
output=feb_average method=average \
where="start_time = datetime(start_time, 'start of year', '1 month')"
# March averages
t.rast.series input=tempmean_monthly \
output=mar_average method=average \
where="start_time = datetime(start_time, 'start of year', '2 month')"
r.series,
t.create,
t.info
Temporal data processing Wiki
Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
Last changed: $Date: 2015-07-20 16:16:59 +0200 (po, 20 7 2015) $
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GRASS Development Team,
GRASS GIS 7.0.2 Reference Manual