xenial (1) t.rast.accdetect.1grass.gz

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NAME

       t.rast.accdetect   -  Detects  accumulation patterns in temporally accumulated space time raster datasets
       created by t.rast.accumulate.

KEYWORDS

       temporal, accumulation, raster, time

SYNOPSIS

       t.rast.accdetect
       t.rast.accdetect --help
       t.rast.accdetect [-nr] input=name   [minimum=name]    [maximum=name]   occurrence=name   [indicator=name]
       start=string     [stop=string]     cycle=string     [offset=string]    basename=string    [range=min,max]
       [staend=start,intermediate,end]   [--overwrite]  [--help]  [--verbose]  [--quiet]  [--ui]

   Flags:
       -n
           Register empty maps in the output space time raster dataset, otherwise they will be deleted

       -r
           Reverse time direction in cyclic accumulation

       --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

       minimum=name
           Input space time raster dataset that specifies the minimum values to detect the accumulation pattern

       maximum=name
           Input space time raster dataset that specifies the maximum values to detect the accumulation pattern

       occurrence=name [required]
           The output space time raster dataset that stores the occurrence of the the accumulation pattern using
           the provided data range

       indicator=name
           The output space time raster dataset that stores the indication of the start, intermediate and end of
           the specified data range

       start=string [required]
           The temporal starting point to begin the accumulation, eg ’2001-01-01’

       stop=string
           The temporal date to stop the accumulation, eg ’2009-01-01’

       cycle=string [required]
           The temporal cycle to restart the accumulation, eg ’12 months’

       offset=string
           The temporal offset to the begin of the next cycle, eg ’6 months’

       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

       range=min,max
           The minimum and maximum value of the occurrence of accumulated values, these values will be  used  if
           the min/max space time raster datasets are not specified

       staend=start,intermediate,end
           The  user  defined  values  that  indicate start, intermediate and end status in the indicator output
           space time raster dataset
           Default: 1,2,3

DESCRIPTION

       t.rast.accdetect is designed to detect accumulation pattern in temporally accumulated space  time  raster
       datasets  created by t.rast.accumulate.  This module expects a space time raster dataset as input that is
       the result of a t.rast.accumulate run.

       The start time and the end time of the pattern detection process  must  be  set,  eg.  start="2000-03-01"
       end="2011-01-01".   The  start  and  end time do not need to be the same as for the accumulation run that
       produced the input space time raster dataset.  In addition a cycle, eg. "8  months",  can  be  specified,
       that  defines  after  which time interval the accumulation pattern detection process restarts. The offset
       option specifies the time between two cycles that should be skipped, eg. "4  months".  Please  make  sure
       that  the  cycle and offset options are same as in the accumulation process that produces the input space
       time raster dataset, otherwise the accumulation pattern detection will produce wrong results.

       The minimum and maximum values of the pattern detection process can be set, either by  using  space  time
       raster datasets or by using fixed values for all raster cells and time steps.

       Using  space  time  raster  datasets allow specifying minimum and maximum values for each raster cell and
       each time step. For example, we want to detect the germination (minimum value)  and  harvesting  (maximum
       value)  dates for different crops in Germany using the growing-degree-day (GDD) method for several years.
       Different crops may grow in different raster cells and change with time because of crop  rotation.  Hence
       we  need  to  specify  different GDD germination/harvesting (minimum/maximum) values for different raster
       cells and different years.

       The raster maps that specifies the minimum and maximum values of the  actual  granule  will  be  detected
       using the following temporal relations: equals, during, overlaps, overlapped and contains. First all maps
       with equal time stamps to the current granule of the input STRDS will be detected, the first minimum  map
       and  the first maximum map that were found are used as range definitions. If no equal maps are found then
       maps with a temporal during relation are detected, then maps that temporally overlap the actual granules,
       until  maps  are  detected that have a temporal contain relation. If no maps are found or minimum/maximum
       STRDS are not set, then the range option is used, eg. range=480,730.

       The base name of of the generated maps must always be set.

       This module produces two output space time raster datasets. The occurrence output STRDS stores  the  time
       in  days from the begin of a cycle for each raster cell and time step that has a value within the minimum
       and maximum definition. These values can be used to compute the duration of the  recognized  accumulation
       pattern.  The  indicator output STRDS uses three values, that can be set using the staend option, to mark
       raster cells with integer values that indicate the start,  the  intermediate  state  and  the  end  of  a
       accumulation  pattern. As default specifies the value 1 the start, the value 2 the intermediate state and
       the value 3 the end of the accumulation pattern in a cycle.

EXAMPLE

       Please have a look at the t.rast.accumulate example.

SEE ALSO

        t.rast.accumulate, t.rast.aggregate, t.rast.mapcalc, t.info, r.series.accumulate, g.region

AUTHOR

       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture

       Last changed: $Date: 2015-07-11 16:04:13 +0200 (Sat, 11 Jul 2015) $

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