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NAME

       t.rast.aggregate.ds   - Aggregates data of an existing space time raster dataset using the
       time intervals of a second space time dataset.

KEYWORDS

       temporal, aggregation, raster, time

SYNOPSIS

       t.rast.aggregate.ds
       t.rast.aggregate.ds --help
       t.rast.aggregate.ds [-n] input=name sample=name  [type=name]  output=name  basename=string
       [suffix=string]          method=string          [offset=integer]          [nprocs=integer]
       [sampling=name[,name,...]]    [where=sql_query]    [--overwrite]   [--help]    [--verbose]
       [--quiet]  [--ui]

   Flags:
       -n
           Register Null maps

       --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

       sample=name [required]
           Time  intervals from this space time dataset (raster, vector or raster3d) are used for
           aggregation computation

       type=name
           Type of the space time dataset from which aggregation will be copied
           Options: strds, stvds, str3ds
           Default: strds

       output=name [required]
           Name of the output space time raster dataset

       basename=string [required]
           Basename of the new generated output maps
           A numerical suffix separated by an underscore will be  attached  to  create  a  unique
           identifier

       suffix=string
           Suffix  to  add  at  basename:  set  ’gran’  for granularity, ’time’ for the full time
           format, ’num’ for numerical suffix with a specific number of digits (default %05)
           Default: gran

       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

       offset=integer
           Offset that is used to create the output map ids,  output  map  id  is  generated  as:
           basename_ (count + offset)
           Default: 0

       nprocs=integer
           Number of r.mapcalc processes to run in parallel
           Default: 1

       sampling=name[,name,...]
           The method to be used for sampling the input dataset
           Options:  equal,  overlaps,  overlapped,  starts, started, finishes, finished, during,
           contains
           Default: contains

       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’

DESCRIPTION

       t.rast.aggregate.ds   works   like  t.rast.aggregate  but  instead  of  defining  a  fixed
       granularity for temporal aggregation the time intervals of all maps registered in a second
       space  time  dataset (can be STRDS, STR3DS or STVDS) are used to aggregate the maps of the
       input space time raster dataset.

NOTES

       The sampling method must be specified from the sampler dataset point of view.  It  defines
       the  temporal  relationships between intervals of the sampling dataset and the input space
       time raster dataset.

EXAMPLES

   Precipitation aggregation
       In this example we create 7 raster maps that will be registered in  a  single  space  time
       raster  dataset named precipitation_daily using a daily temporal granularity. The names of
       the raster maps are stored in a text file that is used for raster map registration.

       A space time vector dataset is created out of two  vector  maps  with  different  temporal
       resolution. The maps are created using v.random. The first map has a granule of 3 days the
       second a granule of 4 days.

       The space time raster dataset precipitation_daily with daily temporal granularity will  be
       aggregated  using  the space time vector dataset resulting in the output space time raster
       dataset precipitation_agg. The  aggregation  method  is  set  to  sum  to  accumulate  the
       precipitation  values  of  all  intervals  in  the space time vector dataset. The sampling
       option assures that only raster maps that are temporally during the time intervals of  the
       space  time  vector  dataset  are  considered  for computation. Hence the option is set to
       contains (time stamped vector map layers temporally contain the raster map layers):
       MAPS="map_1 map_2 map_3 map_4 map_5 map_6 map_7"
       for map in ${MAPS} ; do
           r.mapcalc expression="${map} = 1"
           echo ${map} >> map_list.txt
       done
       t.create type=strds temporaltype=absolute \
                output=precipitation_daily \
                title="Daily precipitation" \
                description="Test dataset with daily precipitation"
       t.register -i type=raster input=precipitation_daily \
                  file=map_list.txt start="2012-08-20" increment="1 days"
       t.info type=strds input=precipitation_daily
        +-------------------- Space Time Raster Dataset -----------------------------+
        |                                                                            |
        +-------------------- Basic information -------------------------------------+
        | Id: ........................ precipitation_daily@PERMANENT
        | Name: ...................... precipitation_daily
        | Mapset: .................... PERMANENT
        | Creator: ................... soeren
        | Temporal type: ............. absolute
        | Creation time: ............. 2014-11-23 16:48:17.686979
        | Modification time:.......... 2014-11-23 16:48:18.302978
        | Semantic type:.............. mean
        +-------------------- Absolute time -----------------------------------------+
        | Start time:................. 2012-09-10 00:00:00
        | End time:................... 2012-09-17 00:00:00
        | Granularity:................ 1 day
        | Temporal type of maps:...... interval
        +-------------------- Spatial extent ----------------------------------------+
        | North:...................... 80.0
        | South:...................... 0.0
        | East:.. .................... 120.0
        | West:....................... 0.0
        | Top:........................ 0.0
        | Bottom:..................... 0.0
        +-------------------- Metadata information ----------------------------------+
        | Raster register table:...... raster_map_register_3225725979b14b5db343a00835b882c7
        | North-South resolution min:. 10.0
        | North-South resolution max:. 10.0
        | East-west resolution min:... 10.0
        | East-west resolution max:... 10.0
        | Minimum value min:.......... 1.0
        | Minimum value max:.......... 1.0
        | Maximum value min:.......... 1.0
        | Maximum value max:.......... 1.0
        | Aggregation type:........... None
        | Number of registered maps:.. 7
        |
        | Title:
        | Daily precipitation
        | Description:
        | Test dataset with daily precipitation
        | Command history:
        | # 2014-11-23 16:48:17
        | t.create type="strds" temporaltype="absolute"
        |     output="precipitation_daily" title="Daily precipitation"
        |     description="Test dataset with daily precipitation"
        | # 2014-11-23 16:48:18
        | t.register -i type="rast" input="precipitation_daily"
        |     file="map_list.txt" start="2012-08-20" increment="1 days"
        |
        +----------------------------------------------------------------------------+
       v.random output=points_1 n=20
       v.random output=points_2 n=20
       t.create type=stvds temporaltype=absolute \
                output=points \
                title="Points" \
                description="Points for aggregation"
       t.register -i type=vector input=points \
                  map=points_1 start="2012-08-20" increment="3 days"
       t.register -i type=vector input=points \
                  map=points_2 start="2012-08-23" increment="4 days"
       t.info type=stvds input=points
        +-------------------- Space Time Vector Dataset -----------------------------+
        |                                                                            |
        +-------------------- Basic information -------------------------------------+
        | Id: ........................ points@PERMANENT
        | Name: ...................... points
        | Mapset: .................... PERMANENT
        | Creator: ................... soeren
        | Temporal type: ............. absolute
        | Creation time: ............. 2014-11-23 16:48:49.193903
        | Modification time:.......... 2014-11-23 16:48:50.185671
        | Semantic type:.............. mean
        +-------------------- Absolute time -----------------------------------------+
        | Start time:................. 2012-08-20 00:00:00
        | End time:................... 2012-08-27 00:00:00
        | Granularity:................ 1 day
        | Temporal type of maps:...... interval
        +-------------------- Spatial extent ----------------------------------------+
        | North:...................... 79.283411
        | South:...................... 5.724954
        | East:.. .................... 118.881168
        | West:....................... 0.016755
        | Top:........................ 0.0
        | Bottom:..................... 0.0
        +-------------------- Metadata information ----------------------------------+
        | Vector register table:...... vector_map_register_6f02d33e0ee243d1a521aaaca39ecb31
        | Number of points ........... 40
        | Number of lines ............ 0
        | Number of boundaries ....... 0
        | Number of centroids ........ 0
        | Number of faces ............ 0
        | Number of kernels .......... 0
        | Number of primitives ....... 40
        | Number of nodes ............ 0
        | Number of areas ............ 0
        | Number of islands .......... 0
        | Number of holes ............ 0
        | Number of volumes .......... 0
        | Number of registered maps:.. 2
        |
        | Title:
        | Points
        | Description:
        | Points for aggregation
        | Command history:
        | # 2014-11-23 16:48:49
        | t.create type="stvds" temporaltype="absolute"
        |     output="points" title="Points" description="Points for aggregation"
        | # 2014-11-23 16:48:49
        | t.register -i type="vect" input="points"
        |     map="points_1" start="2012-08-20" increment="3 days"
        | # 2014-11-23 16:48:50
        | t.register -i type="vect" input="points"
        |     map="points_2" start="2012-08-23" increment="4 days"
        |
        +----------------------------------------------------------------------------+
       t.rast.aggregate.ds input=precipitation_daily \
                           output=precipitation_agg \
                           sample=points type=stvds \
                           basename=prec_agg \
                           method=sum sampling=contains
       t.support input=precipitation_agg \
                 title="Aggregated precipitation" \
                 description="Aggregated precipitation dataset"
       t.info type=strds input=precipitation_agg
        +-------------------- Space Time Raster Dataset -----------------------------+
        |                                                                            |
        +-------------------- Basic information -------------------------------------+
        | Id: ........................ precipitation_agg@PERMANENT
        | Name: ...................... precipitation_agg
        | Mapset: .................... PERMANENT
        | Creator: ................... soeren
        | Temporal type: ............. absolute
        | Creation time: ............. 2014-11-23 16:53:23.488799
        | Modification time:.......... 2014-11-23 16:53:28.714886
        | Semantic type:.............. mean
        +-------------------- Absolute time -----------------------------------------+
        | Start time:................. 2012-08-20 00:00:00
        | End time:................... 2012-08-27 00:00:00
        | Granularity:................ 1 day
        | Temporal type of maps:...... interval
        +-------------------- Spatial extent ----------------------------------------+
        | North:...................... 80.0
        | South:...................... 0.0
        | East:.. .................... 120.0
        | West:....................... 0.0
        | Top:........................ 0.0
        | Bottom:..................... 0.0
        +-------------------- Metadata information ----------------------------------+
        | Raster register table:...... raster_map_register_7b025eb7431747c98c5c1ad971e8c282
        | North-South resolution min:. 10.0
        | North-South resolution max:. 10.0
        | East-west resolution min:... 10.0
        | East-west resolution max:... 10.0
        | Minimum value min:.......... 3.0
        | Minimum value max:.......... 4.0
        | Maximum value min:.......... 3.0
        | Maximum value max:.......... 4.0
        | Aggregation type:........... sum
        | Number of registered maps:.. 2
        |
        | Title:
        | Aggregated precipitation
        | Description:
        | Aggregated precipitation dataset
        | Command history:
        | # 2014-11-23 16:53:23
        | t.rast.aggregate.ds input="precipitation_daily"
        |     output="precipitation_agg" sample="points" type="stvds" basename="prec_agg"
        |     method="sum" sampling="contains"
        | # 2014-11-23 16:53:28
        | t.support input="precipitation_agg"
        |     title="Aggregated precipitation"
        |     description="Aggregated precipitation dataset"
        |
        +----------------------------------------------------------------------------+

   MODIS satellite sensor daily data aggregation to 8 days
       In this example the aggregation from daily data to eight days is shown.   This  "eight-day
       week" is used in some MODIS satellite sensor products.
       # NOTE: the example is written in shell language
       # create maps every 8 days as seed maps
       for year in `seq 2000 2001` ; do
          for doy in `seq -w 1 8 365` ; do
             r.mapcalc -s expression="8day_${year}_${doy} = rand(0.0,40.0)"
          done
       done
       # From de name of each map, we take year and doy, and convert it
       # to a YYYY-MM-DD date for start and end, and create a file with
       # mapnames, start date and end date
       g.list type=raster pattern=8day_20??_* > names_list
       for NAME in `cat names_list` ; do
          # Parse
          YEAR=`echo $NAME | cut -d’_’ -f2`
          DOY=`echo $NAME | cut -d’_’ -f3`
          # convert YYYY_DOY to YYYY-MM-DD
          DOY=`echo "$DOY" | sed ’s/^0*//’`
          doy_end=0
          if [ $DOY -le "353" ] ; then
             doy_end=$(( $DOY + 8 ))
          elif [ $DOY -eq "361" ] ; then
             if [ $[$YEAR % 4] -eq 0 ] && [ $[$YEAR % 100] -ne 0 ] || [ $[$YEAR % 400] -eq 0 ] ; then
                doy_end=$(( $DOY + 6 ))
             else
                 doy_end=$(( $DOY + 5 ))
             fi
          fi
          DATE_START=`date -d "${YEAR}-01-01 +$(( ${DOY} - 1 ))days" +%Y-%m-%d`
          DATE_END=`date -d "${YEAR}-01-01 +$(( ${doy_end} -1 ))days" +%Y-%m-%d`
          # text file with mapnames, start date and end date
          echo "$NAME|$DATE_START|$DATE_END" >> list_map_start_end_time.txt
       done
       # check the list created.
       cat list_map_start_end_time.txt
       8day_2000_001|2000-01-01|2000-01-09
       8day_2000_009|2000-01-09|2000-01-17
       ...
       8day_2000_353|2000-12-18|2000-12-26
       8day_2000_361|2000-12-26|2001-01-01
       8day_2001_001|2001-01-01|2001-01-09
       8day_2001_009|2001-01-09|2001-01-17
       ...
       8day_2001_345|2001-12-11|2001-12-19
       8day_2001_353|2001-12-19|2001-12-27
       8day_2001_361|2001-12-27|2002-01-01
       # all maps except for the last map in each year represent 8-days
       # intervals. But the aggregation starts all over again every
       # January 1st.
       # create 8-day MODIS-like strds
       t.create type=strds temporaltype=absolute \
          output=8day_ts title="8 day time series" \
          description="STRDS with MODIS like 8 day aggregation"
       # register maps
       t.register type=raster input=8day_ts \
          file=list_map_start_end_time.txt
       # check
       t.info input=8day_ts
       t.rast.list input=8day_ts
       # finally, copy the aggregation to a daily time series
       t.rast.aggregate.ds input=daily_ts sample=8day_ts \
          output=8day_agg basename=8day_agg method=average \
          sampling=contains suffix=gran
       # add metadata
       t.support input=8day_agg \
          title="8 day aggregated ts" \
          description="8 day MODIS-like aggregated dataset"
       # check map list in newly created aggregated strds
       t.rast.list input=8day_agg
       name|mapset|start_time|end_time
       8day_agg_2000_01_01|modis|2000-01-01 00:00:00|2000-01-09 00:00:00
       8day_agg_2000_01_09|modis|2000-01-09 00:00:00|2000-01-17 00:00:00
       8day_agg_2000_01_17|modis|2000-01-17 00:00:00|2000-01-25 00:00:00
       ...
       8day_agg_2000_12_18|modis|2000-12-18 00:00:00|2000-12-26 00:00:00
       8day_agg_2000_12_26|modis|2000-12-26 00:00:00|2001-01-01 00:00:00
       8day_agg_2001_01_01|modis|2001-01-01 00:00:00|2001-01-09 00:00:00
       ...
       8day_agg_2001_12_11|modis|2001-12-11 00:00:00|2001-12-19 00:00:00
       8day_agg_2001_12_19|modis|2001-12-19 00:00:00|2001-12-27 00:00:00
       8day_agg_2001_12_27|modis|2001-12-27 00:00:00|2002-01-01 00:00:00

SEE ALSO

        t.rast.aggregate, t.create, t.info

AUTHOR

       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

       Last changed: $Date: 2016-09-19 12:29:41 +0200 (Mon, 19 Sep 2016) $

SOURCE CODE

       Available at: t.rast.aggregate.ds source code (history)

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