t.rast.accdetect(1grass) GRASS GIS User's Manual t.rast.accdetect(1grass)
NAME
t.rast.accdetect - Detects accumulation patterns in temporally accumu-
lated 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] oc-
currence=name [indicator=name] start=string [stop=string] cy-
cle=string [offset=string] basename=string [suffix=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, other-
wise 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
suffix=string
Suffix to add at basename: set ’gran’ for granularity, ’time’ for
the full time format, ’count’ for numerical suffix with a specific
number of digits (default %05)
Default: gran
range=min,max
The minimum and maximum value of the occurrence of accumulated val-
ues, 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 tempo-
rally accumulated space time raster datasets created by t.rast.accumu-
late. This module’s input is a space time raster dataset resulting
from 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 pro-
duced 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 that should be skipped between two cycles, eg. "4
months". The cycle and offset options must be exactly the same that
were used in the accumulation process that generated the input space
time raster dataset, otherwise the accumulation pattern detection will
produce wrong results.
The minimum and maximum values for 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 allows 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 specify the minimum and maximum values of the ac-
tual granule will be detected using the following temporal relations:
equals, during, overlaps, overlapped and contains. First, all maps with
time stamps equal to the current granule of the input STRDS will be de-
tected, the first minimum map and the first maximum map that are found
will be used as range definitions. If no equal maps are found, then
maps with a temporal during relation will be detected, then maps that
temporally overlap the actual granules and finally, maps that have a
temporal contain relation will be detected. 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: occurrence
and indicator. The occurrence output STRDS stores the time in days from
the beginning of a given 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 integer values to mark raster
cells as beginning, intermediate state or end of an accumulation pat-
tern. By default, the module uses 1 to indicate the start, 2 for the
intermediate state and 3 to mark the end of the accumulation pattern in
a cycle. These default values can be changed using the staend option.
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.se-
ries.accumulate, g.region
AUTHOR
Sören Gebbert, Thünen Institute of Climate-Smart Agriculture
SOURCE CODE
Available at: t.rast.accdetect source code (history)
Accessed: unknown
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