Provided by: grass-doc_8.4.0-1_all 
NAME
r.walk - Creates a raster map showing the anisotropic cumulative cost of moving between
different geographic locations on an input raster map whose cell category values represent
cost.
KEYWORDS
raster, cost surface, cumulative costs, cost allocation
SYNOPSIS
r.walk
r.walk --help
r.walk [-knrib] elevation=name friction=name output=name [solver=name] [nearest=name]
[outdir=name] [start_points=name] [stop_points=name] [start_raster=name]
[start_coordinates=east,north[,east,north,...]]
[stop_coordinates=east,north[,east,north,...]] [max_cost=value] [null_cost=value]
[memory=memory in MB] [walk_coeff=a,b,c,d] [lambda=float] [slope_factor=float]
[--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
-k
Use the ’Knight’s move’; slower, but more accurate
-n
Keep null values in output raster map
-r
Start with values in raster map
-i
Print info about disk space and memory requirements and exit
-b
Create bitmask encoded directions
--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:
elevation=name [required]
Name of input elevation raster map
friction=name [required]
Name of input raster map containing friction costs
output=name [required]
Name for output raster map to contain walking costs
solver=name
Name of input raster map solving equal costs
Helper variable to pick a direction if two directions have equal cumulative costs
(smaller is better)
nearest=name
Name for output raster map with nearest start point
outdir=name
Name for output raster map to contain movement directions
start_points=name
Name of starting vector points map
Or data source for direct OGR access
stop_points=name
Name of stopping vector points map
Or data source for direct OGR access
start_raster=name
Name of starting raster points map
start_coordinates=east,north[,east,north,...]
Coordinates of starting point(s) (E,N)
stop_coordinates=east,north[,east,north,...]
Coordinates of stopping point(s) (E,N)
max_cost=value
Maximum cumulative cost
Default: 0
null_cost=value
Cost assigned to null cells. By default, null cells are excluded
memory=memory in MB
Maximum memory to be used (in MB)
Cache size for raster rows
Default: 300
walk_coeff=a,b,c,d
Coefficients for walking energy formula parameters a,b,c,d
Default: 0.72,6.0,1.9998,-1.9998
lambda=float
Lambda coefficients for combining walking energy and friction cost
Default: 1.0
slope_factor=float
Slope factor determines travel energy cost per height step
Default: -0.2125
DESCRIPTION
r.walk computes anisotropic cumulative cost of moving between different geographic
locations on an input elevation raster map whose cell category values represent elevation
combined with an input raster map layer whose cell values represent friction cost.
r.walk outputs 1) a raster map showing the lowest cumulative cost (time) of moving between
each cell and the user-specified starting points and 2) a second raster map showing the
movement direction to the next cell on the path back to the start point (see Movement
Direction). It uses an input elevation raster map whose cell category values represent
elevation, combined with a second input raster map whose cell values represent friction
costs.
This function is similar to r.cost, but in addition to a friction map, it considers an
anisotropic travel time due to the different walking speed associated with downhill and
uphill movements.
NOTES
The formula from Aitken 1977/Langmuir 1984 (based on Naismith’s rule for walking times)
has been used to estimate the cost parameters of specific slope intervals:
T = a*delta_S + b*delta_H_uphill + c*delta_H_moderate_downhill + d*delta_H_steep_downhill
where:
• T is time of movement in seconds,
• delta S is the horizontal distance covered in meters,
• delta H is the altitude difference in meters.
The a, b, c, d walk_coeff parameters take in account movement speed in the different
conditions and are linked to:
• a: time in seconds it takes to walk for 1 meter a flat surface (1/walking speed)
• b: additional walking time in seconds, per meter of elevation gain on uphill
slopes
• c: additional walking time in seconds, per meter of elevation loss on moderate
downhill slopes (use positive value for decreasing cost)
• d: additional walking time in seconds, per meter of elevation loss on steep
downhill slopes (use negative value for increasing cost)
It has been proved that moving downhill is favourable up to a specific slope value
threshold, after that it becomes unfavourable. The default slope value threshold
(slope_factor) is -0.2125, corresponding to tan(-12), calibrated on human behaviour (>5
and <12 degrees: moderate downhill; >12 degrees: steep downhill). The default values for
a, b, c, d walk_coeff parameters are those proposed by Langmuir (0.72, 6.0, 1.9998,
-1.9998), based on man walking effort in standard conditions.
The friction cost parameter represents a time penalty in seconds of additional walking
time to cross 1 meter distance. Friction cost can be any floating point value ≥ 0. A
friction map is a required parameter; if no friction costs are desired, a friction map
should be a raster in which all cells have a value of 0.
The lambda parameter is a dimensionless scaling factor of the friction cost:
total cost = movement time cost + lambda * friction costs * delta_S
For a more accurate result, the "knight’s move" option can be used (although it is more
time consuming). In the diagram below, the center location (O) represents a grid cell from
which cumulative distances are calculated. Those neighbours marked with an x are always
considered for cumulative cost updates. With the "knight’s move" option, the neighbours
marked with a K are also considered.
K K
K x x x K
x O x
K x x x K
K K
The minimum cumulative costs are computed using Dijkstra’s algorithm, that find an optimum
solution (for more details see r.cost, that uses the same algorithm).
Movement Direction
The movement direction surface is created to record the sequence of movements that created
the cost accumulation surface. This movement direction surface can be used by r.path to
recover a path from an end point back to the start point. The direction of each cell
points towards the next cell. The directions are recorded as degrees CCW from East:
112.5 67.5 i.e. a cell with the value 135
157.5 135 90 45 22.5 means the next cell is to the north-west
180 x 360
202.5 225 270 315 337.5
247.5 292.5
Once r.walk computes the cumulative cost map as a linear combination of friction cost
(from friction map) and the altitude and distance covered (from the digital elevation
model), the associated movement direction map can be used by r.path to find the minimum
cost path.
r.walk, like most all GRASS raster programs, is also made to be run on maps larger that
can fit in available computer memory. As the algorithm works through the dynamic list of
cells it can move almost randomly around the entire area. r.walk divides the entire area
into a number of pieces and swaps these pieces in and out of memory (to and from disk) as
needed. This provides a virtual memory approach optimally designed for 2-D raster maps.
The amount of memory to be used by r.walk can be controlled with the memory option,
default is 300 MB. For systems with less memory this value will have to be set to a lower
value.
EXAMPLES
We compute a map showing how far a lost person could get from the point where he or she
was last seen while taking into account the topography and landcover.
g.region swwake_30m -p
# create friction map based on land cover
r.recode landclass96 out=friction rules=- << EOF
1:3:0.1:0.1
4:5:10.:10.
6:6:1000.0:1000.0
7:7:0.3:0.3
EOF
r.walk -k elevation=elev_ned_30m friction=friction output=walkcost \
start_coordinates=635576,216485 lambda=0.5 max=10000
# compute contours on the cost surface to better understand
# how far the person can get in certain time (1000 is in seconds)
r.contour walkcost output=walkcost step=1000
Figure: Walkshed over a cost surface derived from topography and landcover
REFERENCES
• Aitken, R. 1977. Wilderness areas in Scotland. Unpublished Ph.D. thesis.
University of Aberdeen.
• Steno Fontanari, University of Trento, Italy, Ingegneria per l’Ambiente e il
Territorio, 2000-2001. Svilluppo di metodologie GIS per la determinazione
dell’accessibilità territoriale come supporto alle decisioni nella gestione
ambientale.
• Langmuir, E. 1984. Mountaincraft and leadership. The Scottish Sports Council/MLTB.
Cordee, Leicester.
SEE ALSO
r.cost, r.path, r.in.ascii, r.mapcalc, r.recode, r.out.ascii
AUTHORS
Based on r.cost written by :
Antony Awaida, Intelligent Engineering, Systems Laboratory, M.I.T.
James Westervelt, U.S.Army Construction Engineering Research Laboratory
Updated for Grass 5 by Pierre de Mouveaux (pmx@audiovu.com)
Initial version of r.walk:
Steno Fontanari, 2002
Current version of r.walk:
Franceschetti Simone, Sorrentino Diego, Mussi Fabiano and Pasolli Mattia
Correction by: Fontanari Steno, Napolitano Maurizio and Flor Roberto
In collaboration with: Franchi Matteo, Vaglia Beatrice, Bartucca Luisa, Fava Valentina and
Tolotti Mathias, 2004
Updated for GRASS 6.1:
Roberto Flor and Markus Neteler
Updated for GRASS GIS 7:
Markus Metz
Multiple path directions sponsored by mundialis
SOURCE CODE
Available at: r.walk source code (history)
Accessed: Thursday Aug 01 11:30:34 2024
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