NAME
r.futures.validation - Module for land change simulation validation and accuracy assessment
KEYWORDS
raster,
statistics,
accuracy,
validation
SYNOPSIS
r.futures.validation
r.futures.validation --help
r.futures.validation simulated=name reference=name [original=name] [format=string] [--help] [--verbose] [--quiet] [--ui]
Flags:
- --help
- Print usage summary
- --verbose
- Verbose module output
- --quiet
- Quiet module output
- --ui
- Force launching GUI dialog
Parameters:
- simulated=name [required]
- Simulated land use raster
- reference=name [required]
- Reference land use raster
- original=name
- Original land use raster
- Required for kappa simulation
- format=string
- Output format
- Options: plain, shell, json
- Default: plain
Tool
r.futures.validation allows to
validate land change simulation results.
It computes:
- Allocation disagreement (total and per class), see Pontius et al, 2011
- Quantity disagreement (total and per class), see Pontius et al, 2011
- Cohen's Kappa
- Kappa simulation, see van Vliet et al, 2011
This tool can be used for any number of classes.
Input raster
original represents the initial conditions
and is needed for Kappa simulation and for change detection metrics.
When original is provided and the input rasters contain
only binary categories (0 for undeveloped and 1 for developed),
the tool additionally computes change detection metrics:
- Hits: observed change correctly simulated as change
- Misses: observed change incorrectly simulated as persistence
- False alarms: observed persistence incorrectly simulated as change
- Null successes: observed persistence correctly simulated as persistence
- Figure of merit: hits / (hits + misses + false alarms)
- Producer's accuracy: hits / (hits + misses)
- User's accuracy: hits / (hits + false alarms)
These metrics are reported as proportions of the total number of cells.
Cells already developed in the
original raster are excluded
from the change analysis and reported separately as initially developed.
When more than two categories are present, these metrics are skipped.
Validate land change simulation output by computing quantity and allocation
disagreement, kappa statistics, and change detection metrics.
First, reclassify the FUTURES simulation output
(where -1 is undeveloped, 0 is initially developed,
and 1 to N is the step when a cell became developed)
to binary (0 = undeveloped, 1 = developed).
Create a file
reclass_rules.txt with the following content:
-1 = 0 undeveloped
0 thru 1000 = 1 developed
Then reclassify and run the validation:
r.reclass input=simulated_2016 output=simulated_2016_reclass rules=reclass_rules.txt
r.futures.validation simulated=simulated_2016_reclass reference=reference_2016 \
original=orig_2001 format=json
Example output:
{
"quantity_class_0": 0.015,
"quantity_class_1": 0.015,
"allocation_class_0": 0.023,
"allocation_class_1": 0.023,
"total_quantity": 0.015,
"total_allocation": 0.023,
"kappa": 0.852,
"kappasimulation": 0.15,
"misses": 0.032,
"hits": 0.04,
"false_alarms": 0.021,
"null_successes": 0.507,
"figure_of_merit": 0.4301,
"producer": 0.5556,
"user": 0.6557,
"initially_developed": 0.4
}
Validation references:
FUTURES references:
-
Meentemeyer, R. K., Tang, W., Dorning, M. A., Vogler, J. B., Cunniffe, N. J., & Shoemaker, D. A. (2013).
FUTURES: Multilevel Simulations of Emerging Urban-Rural Landscape Structure Using a Stochastic Patch-Growing Algorithm.
Annals of the Association of American Geographers, 103(4), 785-807.
DOI: 10.1080/00045608.2012.707591
-
Dorning, M. A., Koch, J., Shoemaker, D. A., & Meentemeyer, R. K. (2015).
Simulating urbanization scenarios reveals tradeoffs between conservation planning strategies.
Landscape and Urban Planning, 136, 28-39.
DOI: 10.1016/j.landurbplan.2014.11.011
-
Petrasova, A., Petras, V., Van Berkel, D., Harmon, B. A., Mitasova, H., & Meentemeyer, R. K. (2016).
Open Source Approach to Urban Growth Simulation.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B7, 953-959.
DOI: 10.5194/isprsarchives-XLI-B7-953-2016
-
Sanchez, G.M., A. Petrasova, A., M.M. Skrip, E.L. Collins, M.A. Lawrimore,
J.B. Vogler, A. Terando, J. Vukomanovic, H. Mitasova, and R.K. Meentemeyer (2023).
Spatially interactive modeling of land change identifies location-specific adaptations most likely to lower future flood risk.
Sci Rep 13, 18869.
DOI: 10.1038/s41598-023-46195-9
FUTURES,
r.futures.simulation,
r.futures.parallelpga,
r.futures.devpressure,
r.futures.potential,
r.futures.potsurface,
r.futures.demand,
r.futures.calib,
r.futures.gridvalidation
For alternative validation metrics see
r.confusionmatrix,
r.kappa
Corresponding author:
Anna Petrasova, akratoc ncsu edu,
Center for Geospatial Analytics, NCSU
Original standalone version:
Ross K. Meentemeyer,
Wenwu Tang,
Monica A. Dorning,
John B. Vogler,
Nik J. Cunniffe,
Douglas A. Shoemaker
(Department of Geography and Earth Sciences, UNC Charlotte)
Jennifer A. Koch
(Center for Geospatial Analytics, NCSU)
Port to GRASS and GRASS-specific additions:
Vaclav Petras,
NCSU GeoForAll
Development pressure, demand, calibration, validation, preprocessing tools and maintenance:
Anna Petrasova,
NCSU GeoForAll
Climate forcing submodel:
Anna Petrasova,
NCSU GeoForAll
Georgina Sanchez,
Center for Geospatial Analytics, NCSU
Zoning:
Margaret Lawrimore,
Center for Geospatial Analytics, NCSU
Anna Petrasova,
NCSU GeoForAll
SOURCE CODE
Available at:
r.futures.validation source code
(history)
Latest change: Friday Apr 17 16:26:46 2026 in commit: bc11ef4ff4ec4adc9e7936158549a9868d09a1d9
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