1t.rast.accdetect(1)         GRASS GIS User's Manual        t.rast.accdetect(1)
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NAME

6       t.rast.accdetect  - Detects accumulation patterns in temporally accumu‐
7       lated space time raster datasets created by t.rast.accumulate.
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KEYWORDS

10       temporal, accumulation, raster, time
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SYNOPSIS

13       t.rast.accdetect
14       t.rast.accdetect --help
15       t.rast.accdetect  [-nr]  input=name   [minimum=name]     [maximum=name]
16       occurrence=name     [indicator=name]     start=string     [stop=string]
17       cycle=string    [offset=string]     basename=string     [suffix=string]
18       [range=min,max]      [staend=start,intermediate,end]      [--overwrite]
19       [--help]  [--verbose]  [--quiet]  [--ui]
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21   Flags:
22       -n
23           Register empty maps in the output space time raster dataset, other‐
24           wise they will be deleted
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26       -r
27           Reverse time direction in cyclic accumulation
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29       --overwrite
30           Allow output files to overwrite existing files
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32       --help
33           Print usage summary
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35       --verbose
36           Verbose module output
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38       --quiet
39           Quiet module output
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41       --ui
42           Force launching GUI dialog
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44   Parameters:
45       input=name [required]
46           Name of the input space time raster dataset
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48       minimum=name
49           Input  space  time raster dataset that specifies the minimum values
50           to detect the accumulation pattern
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52       maximum=name
53           Input space time raster dataset that specifies the  maximum  values
54           to detect the accumulation pattern
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56       occurrence=name [required]
57           The  output space time raster dataset that stores the occurrence of
58           the the accumulation pattern using the provided data range
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60       indicator=name
61           The output space time raster dataset that stores the indication  of
62           the start, intermediate and end of the specified data range
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64       start=string [required]
65           The   temporal   starting  point  to  begin  the  accumulation,  eg
66           ’2001-01-01’
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68       stop=string
69           The temporal date to stop the accumulation, eg ’2009-01-01’
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71       cycle=string [required]
72           The temporal cycle to restart the accumulation, eg ’12 months’
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74       offset=string
75           The temporal offset to the begin of the next cycle, eg ’6 months’
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77       basename=string [required]
78           Basename of the new generated output maps
79           A numerical suffix separated by an underscore will be  attached  to
80           create a unique identifier
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82       suffix=string
83           Suffix  to  add at basename: set ’gran’ for granularity, ’time’ for
84           the full time format, ’count’ for numerical suffix with a  specific
85           number of digits (default %05)
86           Default: gran
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88       range=min,max
89           The minimum and maximum value of the occurrence of accumulated val‐
90           ues, these values will be used if the  min/max  space  time  raster
91           datasets are not specified
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93       staend=start,intermediate,end
94           The  user  defined values that indicate start, intermediate and end
95           status in the indicator output space time raster dataset
96           Default: 1,2,3
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DESCRIPTION

99       t.rast.accdetect is designed to detect accumulation pattern  in  tempo‐
100       rally  accumulated space time raster datasets created by t.rast.accumu‐
101       late.  This module’s input is a space  time  raster  dataset  resulting
102       from a t.rast.accumulate run.
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104       The  start  time and the end time of the pattern detection process must
105       be set, eg. start="2000-03-01" end="2011-01-01".   The  start  and  end
106       time  do  not need to be the same as for the accumulation run that pro‐
107       duced the input space time raster dataset.  In addition a cycle, eg. "8
108       months",  can  be specified, that defines after which time interval the
109       accumulation pattern detection  process  restarts.  The  offset  option
110       specifies  the  time  that should be skipped between two cycles, eg. "4
111       months". The cycle and offset options must be  exactly  the  same  that
112       were  used  in  the accumulation process that generated the input space
113       time raster dataset, otherwise the accumulation pattern detection  will
114       produce wrong results.
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116       The minimum and maximum values for the pattern detection process can be
117       set either by using space time raster datasets or by using fixed values
118       for all raster cells and time steps.
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120       Using  space time raster datasets allows specifying minimum and maximum
121       values for each raster cell and each time step. For example, we want to
122       detect  the  germination (minimum value) and harvesting (maximum value)
123       dates for different crops in Germany using the growing-degree-day (GDD)
124       method  for several years. Different crops may grow in different raster
125       cells and change with time because of crop rotation. Hence we  need  to
126       specify  different  GDD germination/harvesting (minimum/maximum) values
127       for different raster cells and different years.
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129       The raster maps that specify the minimum  and  maximum  values  of  the
130       actual granule will be detected using the following temporal relations:
131       equals, during, overlaps, overlapped and contains. First, all maps with
132       time  stamps  equal  to  the current granule of the input STRDS will be
133       detected, the first minimum map and the  first  maximum  map  that  are
134       found  will  be  used as range definitions. If no equal maps are found,
135       then maps with a temporal during relation will be detected,  then  maps
136       that temporally overlap the actual granules and finally, maps that have
137       a temporal contain relation will be detected. If no maps are  found  or
138       minimum/maximum  STRDS  are not set, then the range option is used, eg.
139       range=480,730.
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141       The base name of of the generated maps must always be set.
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143       This module produces two output space time raster datasets:  occurrence
144       and indicator. The occurrence output STRDS stores the time in days from
145       the beginning of a given cycle for each raster cell and time step  that
146       has a value within the minimum and maximum definition. These values can
147       be used to compute the duration of the recognized accumulation pattern.
148       The  indicator  output  STRDS  uses three integer values to mark raster
149       cells as beginning, intermediate state or end of an  accumulation  pat‐
150       tern.  By  default,  the module uses 1 to indicate the start, 2 for the
151       intermediate state and 3 to mark the end of the accumulation pattern in
152       a cycle. These default values can be changed using the staend option.
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EXAMPLE

155       Please have a look at the t.rast.accumulate example.
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SEE ALSO

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

162       Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
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SOURCE CODE

165       Available at: t.rast.accdetect source code (history)
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167       Main index | Temporal index | Topics index | Keywords index | Graphical
168       index | Full index
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170       © 2003-2020 GRASS Development Team, GRASS GIS 7.8.5 Reference Manual
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174GRASS 7.8.5                                                t.rast.accdetect(1)
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