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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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