NAME
r.pi.searchtime - Individual-based dispersal model for connectivity analysis (time-based)KEYWORDS
rasterSYNOPSIS
r.pi.searchtime
r.pi.searchtime --helpr.pi.searchtime [-acdi] input=name [suitability=string] output=name [out_immi=string] [immi_matrix=string] [binary_matrix=string] [threshold=float] keyval=integer step_length=integer [step_range=float] [perception=integer] [multiplicator=float] n=integer percent=float stats=string[,string,...] [maxsteps=integer] [out_freq=integer] [title="phrase"] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
- -a
- Set for 8 cell-neighbors. 4 cell-neighbors are default
- -c
- Include cost of the path in the calculation of steps
- -d
- Output diversity map
- -i
- Output Shannon- and Simpson-index
- --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 input raster map
- suitability=string
- Name of the costmap with values from 0-100
- output=name [required]
- Name for output raster map
- out_immi=string
- Name of the optional raster file for patch immigrants count
- immi_matrix=string
- Name for immigrants matrix ASCII-file
- binary_matrix=string
- Name for binary immigrants matrix ASCII-file
- threshold=float
- Percentage of individuals which must have immigrated successfully to be considered for the binary immigrants matrix
- keyval=integer [required]
- Category value of the patches
- step_length=integer [required]
- Length of a single step measured in pixels
- step_range=float
- Range to choose the next step direction from, in degrees [default = 180°]
- perception=integer
- Perception range
- multiplicator=float
- Attractivity of patches [1-inf]
- n=integer [required]
- Number of individuals
- percent=float [required]
- Percentage of individuals which must have arrived successfully to stop the model-run
- stats=string[,string,...] [required]
- Statistical method to perform on the values
- Options: average, variance, standard deviation, median, min, max
- maxsteps=integer
- Maximum steps for each individual
- out_freq=integer
- Output an intermediate state of simulation each [out_freq] steps
- title="phrase"
- Title for resultant raster map
Table of contents
DESCRIPTION
Individual-based dispersal model for connectivity analysis (time-based)This module provides information about the isolation or connectivity of individual fragments derived of a landcover classification. Unlike r.pi.energy this module provides information about the time from emigration to immigration. The individual based dispersal model results are based on the step length and range, the perception distance and the attractivity to move towards patches.
NOTES
The suitability matrix impacts the step direction of individuals. If individuals are moving beyond the mapset borders the indivuals are set back to their original source patches.EXAMPLE
An example for the North Carolina sample dataset:The connectivity of patches of the landclass96 class 5 are computed using the time from emigration to immigration. The step length is set to 5 pixel, the output statistics are set to average time and variance of searchtime. For each patch 1000 individuals were released and the model stopped when at least 80% of all individuals sucessfully immigrated:
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 step_range=10
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 perception=10
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 multiplicator=10
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 maxsteps=10
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 out_freq=10
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 out_immi=immi_counts
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 binary_matrix=binary_matrix.txt
r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 immi_matrix=immi_counts.txt
# it is assumed that our species is a forest species and cannot move # through water, hence a cost of 100, does not like urban areas # (class: 6, cost: 10) but can disperse through shrubland (class 4, # cost=1) better than through grassland (class 3, cost: 2): r.mapcalc "suit_raster = if(landclass96==5,1,if(landclass96 == 1, 10, if (landclass96==3,2, if(landclass96==4,1,if(landclass96==6,100)))))" r.pi.searchtime input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 suitability=suit_raster
SEE ALSO
r.pi.searchtime.pr, r.pi.searchtime.mw, r.piAUTHORS
Programming: Elshad ShirinovScientific concept: Dr. Martin Wegmann
Department of Remote Sensing
Remote Sensing and Biodiversity Unit
University of Wuerzburg, Germany
Port to GRASS GIS 7: Markus Metz
SOURCE CODE
Available at: r.pi.searchtime source code (history)
Latest change: Wed Feb 2 21:46:15 2022 in commit: 2e3dcb5eafe36d640aa68585be0192f07ca1eabb
Main index | Raster index | Topics index | Keywords index | Graphical index | Full index
© 2003-2022 GRASS Development Team, GRASS GIS 8.0.3dev Reference Manual