Provided by: grass-doc_7.6.0-1_all bug


       t.rast.series   -  Performs  different  aggregation  algorithms  from r.series on all or a
       subset of raster maps in a space time raster dataset.


       temporal, aggregation, series, raster, time


       t.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]

           Do not assign the space time raster dataset start and end time to the output map

           Propagate NULLs

           Allow output files to overwrite existing files

           Print usage summary

           Verbose module output

           Quiet module output

           Force launching GUI dialog

       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 to calculate for method=quantile
           Options: 0.0-1.0

           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  conditions  of  SQL  statement without ’where’ keyword used in the temporal GIS
           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.


       Estimate average temperature for the whole time series
       t.rast.series input=tempmean_monthly output=tempmean_general method=average
       Estimate  average  temperature  for  all  January  maps  in the time series, the so-called
       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}’"


        r.series, t.create,

       Temporal data processing Wiki


       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

       Last changed: $Date: 2016-01-13 00:28:48 +0100 (Wed, 13 Jan 2016) $


       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