1t.rast.accdetect(1) GRASS GIS User's Manual t.rast.accdetect(1)
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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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10 temporal, accumulation, raster, time
11
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]
20 Flags:
22 -n
23 Register empty maps in the output space time raster dataset, other‐
24 wise they will be deleted
25 -r
27 Reverse time direction in cyclic accumulation
28 --overwrite
30 Allow output files to overwrite existing files
31 --help
33 Print usage summary
34 --verbose
36 Verbose module output
37 --quiet
39 Quiet module output
40 --ui
42 Force launching GUI dialog
43 Parameters:
45 input=name [required]
46 Name of the input space time raster dataset
47 minimum=name
49 Input space time raster dataset that specifies the minimum values
50 to detect the accumulation pattern
51 maximum=name
53 Input space time raster dataset that specifies the maximum values
54 to detect the accumulation pattern
55 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
59 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
63 start=string [required]
65 The temporal starting point to begin the accumulation, eg
66 ’2001-01-01’
67 stop=string
69 The temporal date to stop the accumulation, eg ’2009-01-01’
70 cycle=string [required]
72 The temporal cycle to restart the accumulation, eg ’12 months’
73 offset=string
75 The temporal offset to the begin of the next cycle, eg ’6 months’
76 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
81 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
87 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
92 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
97
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.
103 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.
115 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.
119 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.
128 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.
140 The base name of of the generated maps must always be set.
142 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.
153
155 Please have a look at the t.rast.accumulate example.
156
158 t.rast.accumulate, t.rast.aggregate, t.rast.mapcalc, t.info,
159 r.series.accumulate, g.region
160
162 Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
163
165 Available at: t.rast.accdetect source code (history)
166 Main index | Temporal index | Topics index | Keywords index | Graphical
168 index | Full index
169 © 2003-2020 GRASS Development Team, GRASS GIS 7.8.5 Reference Manual
171GRASS 7.8.5 t.rast.accdetect(1)