**-a**- Set for 8 cell-neighbors. 4 cell-neighbors are default
**-c**- Include cost of the path in the calculation of steps
**--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

**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
**keyval**=*integer***[required]**- Category value of the patches
**step_length**=*integer***[required]**- Length of a single step measured in pixels
**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 pathlengths of the individuals
- Options:
*average, variance, standard deviation, median, min, max* **maxsteps**=*integer*- Maximum steps for each individual
**size**=*integer*- Size of the moving window
**title**=*"phrase"*- Title for resultant raster map

r.pi.searchtime.mw input=landclass96 output=searchtime_mw1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000

r.pi.searchtime.mw input=landclass96 output=searchtime_mw1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 size=7

r.pi.searchtime.mw input=landclass96 output=searchtime_mw1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 size=7 perception=10

r.pi.searchtime.mw input=landclass96 output=searchtime_mw1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 size=7 multiplicator=10

# 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.mw input=landclass96 output=searchtime1 keyval=5 step_length=5 stats=average,variance percent=80 n=1000 size=7 suitability=suit_raster

Scientific concept: Dr. Martin Wegmann

Department of Remote Sensing

Remote Sensing and Biodiversity Unit

University of Wuerzburg, Germany

Port to GRASS GIS 7: Markus Metz

*Last changed: $Date: 2017-05-10 23:56:34 +0200 (Wed, 10 May 2017) $*

Available at: r.pi.searchtime.mw source code (history)

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