r.futures.validation - GRASS manual

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

DESCRIPTION
EXAMPLES
REFERENCES
SEE ALSO
AUTHORS

DESCRIPTION

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.

EXAMPLES

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
}

REFERENCES

Validation references:

Robert Gilmore Pontius Jr & Marco Millones (2011). Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. International Journal of Remote Sensing, 32:15, 4407-4429
Jasper van Vliet, Arnold K. Bregt, Alex Hagen-Zanker (2011) Revisiting Kappa to account for change in the accuracy assessment of land-use change models. Ecological Modelling, Volume 222, Issue 8.

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

AUTHORS

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)

Accessed: Monday Jul 27 12:29:20 2026