r.spreadgrass - Online in the Cloud

PROGRAM:

NAME

r.spread - Simulates elliptically anisotropic spread.
Generates a raster map of the cumulative time of spread, given raster maps containing the
rates of spread (ROS), the ROS directions and the spread origins. It optionally produces
raster maps to contain backlink UTM coordinates for tracing spread paths. Usable for fire
spread simulations.

KEYWORDS

raster, fire, spread, hazard, model

SYNOPSIS

r.spread
r.spread --help
r.spread [-si] base_ros=string max_ros=string direction_ros=string start=string
[spotting_distance=string] [wind_speed=string] [fuel_moisture=string]
[least_size=odd int] [comp_dens=decimal] [init_time=int (>= 0)] [lag=int (>= 0)]
[backdrop=string] output=string [x_output=string] [y_output=string] [--overwrite]
[--help] [--verbose] [--quiet] [--ui]

Flags:
-s
Consider spotting effect (for wildfires)

-i
Use start raster map values in output spread time raster map
Designed to be used with output of previous run of r.spread when computing spread
iteratively. The values in start raster map are considered as time. Allowed values in
raster map are from zero to the value of init_time option. If not enabled, init_time
is used in the area of start raster map

--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:
base_ros=string [required]
Raster map containing base ROS (cm/min)
Name of an existing raster map layer in the user’s current mapset search path
containing the ROS values in the directions perpendicular to maximum ROSes’
(cm/minute). These ROSes are also the ones without the effect of directional factors.

max_ros=string [required]
Raster map containing maximal ROS (cm/min)
Name of an existing raster map layer in the user’s current mapset search path
containing the maximum ROS values (cm/minute).

direction_ros=string [required]
Raster map containing directions of maximal ROS (degree)
Name of an existing raster map layer in the user’s current mapset search path
containing directions of the maximum ROSes, clockwise from north (degree).

start=string [required]
Raster map containing starting sources
Name of an existing raster map layer in the user’s current mapset search path
containing starting locations of the spread phenomenon. Any positive integers in this
map are recognized as starting sources (seeds).

spotting_distance=string
Raster map containing maximal spotting distance (m, required with -s)
Name of an existing raster map layer in the user’s current mapset search path
containing the maximum potential spotting distances (meters).

wind_speed=string
Raster map containing midflame wind speed (ft/min, required with -s)
Name of an existing raster map layer in the user’s current mapset search path
containing wind velocities at half of the average flame height (feet/minute).

fuel_moisture=string
Raster map containing fine fuel moisture of the cell receiving a spotting firebrand
(%, required with -s)
Name of an existing raster map layer in the user’s current mapset search path
containing the 1-hour (<.25") fuel moisture (percentage content multiplied by 100).

least_size=odd int
Basic sampling window size needed to meet certain accuracy (3)
An odd integer ranging 3 - 15 indicating the basic sampling window size within which
all cells will be considered to see whether they will be reached by the current spread
cell. The default number is 3 which means a 3x3 window.
Options: 3, 5, 7, 9, 11, 13, 15

comp_dens=decimal
Sampling density for additional computing (range: 0.0 - 1.0 (0.5))
A decimal number ranging 0.0 - 1.0 indicating additional sampling cells will be
considered to see whether they will be reached by the current spread cell. The closer
to 1.0 the decimal number is, the longer the program will run and the higher the
simulation accuracy will be. The default number is 0.5.

init_time=int (>= 0)
Initial time for current simulation (0) (min)
A non-negative number specifying the initial time for the current spread simulation
(minutes). This is useful when multiple phase simulation is conducted. The default
time is 0.
Default: 0

lag=int (>= 0)
Simulating time duration LAG (fill the region) (min)
A non-negative integer specifying the simulating duration time lag (minutes). The
default is infinite, but the program will terminate when the current geographic
region/mask has been filled. It also controls the computational time, the shorter the
time lag, the faster the program will run.

backdrop=string
Name of raster map as a display backdrop
Name of an existing raster map layer in the user’s current mapset search path to be
used as the background on which the "live" movement will be shown.

output=string [required]
Raster map to contain output spread time (min)
Name of the new raster map layer to contain the results of the cumulative spread time
needed for a phenomenon to reach each cell from the starting sources (minutes).

x_output=string
Name of raster map to contain X back coordinates
Name of the new raster map layer to contain the results of backlink information in UTM
easting coordinates for each cell.

y_output=string
Name of raster map to contain Y back coordinates
Name of the new raster map layer to contain the results of backlink information in UTM
northing coordinates for each cell.

DESCRIPTION

r.spread is part of the wildfire simulation toolset. Preparational steps for the fire
simulation are the calculation of the rate of spread (ROS) with r.ros, and the creating of
spread map with r.spread. Eventually, the fire path(s) based on starting point(s) are
calculated with r.spreadpath.

Spread phenomena usually show uneven movement over space. Such unevenness is due to two
reasons:

1 the uneven conditions from location to location, which can be called spatial
heterogeneity, and

2 the uneven conditions in different directions, which can be called anisotropy.

The anisotropy of spread occurs when any of the determining factors have directional
components. For example, wind and topography cause anisotropic spread of wildfires.

One of the simplest spatial heterogeneous and anisotropic spread is elliptical spread, in
which, each local spread shape can be thought as an ellipse. In a raster setting, cell
centers are foci of the spread ellipses, and the spread phenomenon moves fastest toward
apogees and slowest to perigees. The sizes and shapes of spread ellipses may vary cell by
cell. So the overall spread shape is commonly not an ellipse.

r.spreadsimulates elliptically anisotropic spread phenomena, given three raster map layers
about ROS (base ROS, maximum ROS and direction of the maximum ROS) plus a raster map layer
showing the starting sources. These ROS layers define unique ellipses for all cell
locations in the current computational region as if each cell center was a potential
spread origin. For some wildfire spread, these ROS layers can be generated by another
GRASS raster program r.ros. The actual locations reached by a spread event are constrained
by the actual spread origins and the elapsed spread time.

r.spreadoptionally produces raster maps to contain backlink UTM coordinates for each
raster cell of the spread time map. The spread paths can be accurately traced based on the
backlink information by r.spreadpath module.

Part of the spotting function in r.spread is based on Chase (1984) and Rothermel (1983).
More information on r.spread, r.ros and r.spreadpath can be found in Xu (1994).

Options spot_dist, w_speed and f_mois must all be given if the -s (spotting) flag is used.

EXAMPLE

Assume we have inputs, the following simulates a spotting- involved wildfire and generates
three raster maps to contain spread time, backlink information in UTM northing and easting
coordinates:
r.spread -s max=my_ros.max dir=my_ros.maxdir base=my_ros.base \
start=fire_origin spot_dist=my_ros.spotdist w_speed=wind_speed \
f_mois=1hour_moisture output=my_spread \
x_output=my_spread.x y_output=my_spread.y

NOTES

1. r.spread is a specific implementation of the shortest path algorithm. r.cost module
served as the starting point for the development of r.spread. One of the major
differences between the two programs is that r.cost only simulates isotropic spread while
r.spread can simulate elliptically anisotropic spread, including isotropic spread as a
special case.

2. Before running r.spread, the user should prepare the ROS (base, max and direction) maps
using appropriate models. For some wildfire spread, the r.ros module based on Rothermel’s
fire equation does such work. The combination of the two forms a simulation of wildfire
spread.

3. The relationship of the start map and ROS maps should be logically correct, i.e. a
starting source (a positive value in the start map) should not be located in a spread
barrier (zero value in the ROS maps). Otherwise the program refuses to run.

4. r.spread uses the current computational region settings. The output map layer will not
go outside the boundaries set in the region, and will not be influenced by starting
sources outside. So any change of the current region may influence the output. The
recommendation is to use slightly larger region than needed. Refer to g.region to set an
appropriate computational region.

5. The user should be sure that the inputs to r.spread are in proper units.

6. r.spread is a computationally intensive program. The user may need to choose
appropriate size of the computational region and resolution.

7. A low and medium (i.e. <= 0.5) sampling density can improve accuracy for elliptical
simulation significantly, without adding significantly extra running time. Further
increasing the sample density will not gain much accuracy while requiring greatly
additional running time.

REFERENCES

· Chase, Carolyn, H., 1984, Spotting distance from wind-driven surface fires --
extensions of equations for pocket calculators, US Forest Service, Res. Note
INT-346, Ogden, Utah.

· Rothermel, R. C., 1983, How to predict the spread and intensity of forest and
range fires. US Forest Service, Gen. Tech. Rep. INT-143. Ogden, Utah.

· Xu, Jianping, 1994, Simulating the spread of wildfires using a geographic
information system and remote sensing, Ph. D. Dissertation, Rutgers University,
New Brunswick, New Jersey (ref).

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