GRASS logo

NAME

r.futures.parallelpga - Simulates landuse change using FUTURES (r.futures.pga) on multiple CPUs in parallel.
Module uses Patch-Growing Algorithm (PGA) to simulate urban-rural landscape structure development.

KEYWORDS

raster, patch growing, urban, landscape, modeling

SYNOPSIS

r.futures.parallelpga
r.futures.parallelpga --help
r.futures.parallelpga [-d] nprocs=integer repeat=integer developed=name subregions=name [subregions_potential=name] output=name [output_series=basename] [num_steps=integer] predictors=name[,name,...] devpot_params=name development_pressure=name n_dev_neighbourhood=integer development_pressure_approach=string gamma=float scaling_factor=float demand=name discount_factor=float compactness_mean=float compactness_range=float num_neighbors=integer seed_search=string patch_sizes=name [incentive_power=float] [potential_weight=name] [random_seed=integer] [memory=float] [--overwrite] [--help] [--verbose] [--quiet] [--ui]

Flags:

-d
Runs each subregion separately
r.futures.pga runs for each subregion and after all subregions are completed, the results are patched together
--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:

nprocs=integer [required]
Number of processes to run in parallel
Default: 1
repeat=integer [required]
Number of times stochastic simulation is repeated
Default: 10
developed=name [required]
Raster map of developed areas (=1), undeveloped (=0) and excluded (no data)
subregions=name [required]
Raster map of subregions
subregions_potential=name
Raster map of subregions used with potential file
If not specified, the raster specified in subregions parameter is used
output=name [required]
State of the development at the end of simulation
output_series=basename
Basename for raster maps of development generated after each step
Name for output basename raster map(s)
num_steps=integer
Number of steps to be simulated
predictors=name[,name,...] [required]
Names of predictor variable raster maps
Listed in the same order as in the development potential table
devpot_params=name [required]
Development potential parameters for each region
Each line should contain region ID followed by parameters (intercepts, development pressure, other predictors). Values are separated by tabs. First line is ignored, so it can be used for header
development_pressure=name [required]
Raster map of development pressure
n_dev_neighbourhood=integer [required]
Size of square used to recalculate development pressure
development_pressure_approach=string [required]
Approaches to derive development pressure
Options: occurrence, gravity, kernel
Default: gravity
gamma=float [required]
Influence of distance between neighboring cells
scaling_factor=float [required]
Scaling factor of development pressure
demand=name [required]
Control file with number of cells to convert
discount_factor=float [required]
Discount factor of patch size
compactness_mean=float [required]
Mean value of patch compactness to control patch shapes
compactness_range=float [required]
Range of patch compactness to control patch shapes
num_neighbors=integer [required]
The number of neighbors to be used for patch generation (4 or 8)
Options: 4, 8
Default: 4
seed_search=string [required]
The way location of a seed is determined (1: uniform distribution 2: development probability)
Options: random, probability
Default: probability
patch_sizes=name [required]
File containing list of patch sizes to use
incentive_power=float
Exponent to transform probability values p to p^x to simulate infill vs. sprawl
Values > 1 encourage infill, < 1 urban sprawl
Options: 0-10
Default: 1
potential_weight=name
Raster map of weights altering development potential
Values need to be between -1 and 1, where negative locally reduces probability and positive increases probability.
random_seed=integer
Seed for random number generator
The same seed can be used to obtain same results or random seed can be generated by other means.
memory=float
Memory for single run in GB

Table of contents

DESCRIPTION

Since FUTURES model is stochastic, multiple runs are recommended. Module r.futures.parallelpga is a script for running r.futures.pga on multiple CPUs. All options of r.futures.pga are available (except for random seed options which are handled by r.futures.parallelpga).

Option repeat changes the number of times the simulation is repeated with the same settings but different random seed. Option nprocs sets the number of parallel processes to be used, which depends on number of available CPUs. Flag -d switches on parallelization on subregion level. Subregions are split and simulation runs on each subregion individually. This approach is convenient if available memory is not sufficient for the entire study area. However, as each subregion is handled separately, development pressure on the edge of a subregion does not influence its neighbors. This can influence the results in case of significant development happening on the subregion boundary.

EXAMPLES

SEE ALSO

FUTURES, r.futures.pga, r.futures.devpressure, r.futures.potsurface, r.futures.demand, r.futures.calib, r.futures.potential, r.sample.category

REFERENCES

AUTHOR

Anna Petrasova, NCSU GeoForAll

SOURCE CODE

Available at: r.futures.parallelpga source code (history)

Latest change: Thursday Feb 03 09:32:35 2022 in commit: f17c792f5de56c64ecfbe63ec315307872cf9d5c

Main index | Raster index | Topics index | Keywords index | Graphical index | Full index

© 2003-2023 GRASS Development Team, GRASS GIS 8.2.2dev Reference Manual