calcPerformance {optimLanduse} | R Documentation |
Attach portfolio performance and distance to target
Description
The Portfolio performances are calculated and attached to the solved optimLanduse object. Each performance measure describes the relative proportion to the maximum achievable (the "target") of the indicator, given the current land use distribution and the uncertainty scenario set. The lowest performing scenario of all indicators is the degree of minimal fulfillment under the worst-possible outcome. It can thus be interpreted as the guaranteed performance. At least this proportion will be achieved across all indicators.
Usage
calcPerformance(x)
Arguments
x |
An optimized optimLanduse object. |
Details
For further information and calculation, see the supplement of Gosling et al. (2020), Formula S5 (in the supplement of the paper) and also the paragraph optimLanduse functions and workflow - Post-processing in Husmann et al. (2022).
Value
An optimized optimLanduse object with attached portfolio performance.
References
Gosling, E., Reith, E., Knoke T., Gerique, A., Paul, C. (2020): Exploring farmer perceptions of agroforestry via multi-objective optimisation: a test application in Eastern Panama. Agroforestry Systems 94. doi:10.1007/s10457-020-00519-0
Husmann, K., von Groß, V., Bödeker, K., Fuchs, J. M., Paul, C., & Knoke, T. (2022). optimLanduse: A package for multiobjective land-cover composition optimization under uncertainty. Methods in Ecology and Evolution, 00, 1– 10. https://doi.org/10.1111/2041-210X.14000
Examples
require(ggplot2)
require(readxl)
dat <- read_xlsx(exampleData("exampleGosling.xlsx"))
init <- initScenario(dat, uValue = 2,
optimisticRule = "expectation",
fixDistance = 3)
result <- solveScenario(x = init)
performance <- calcPerformance(result)
# Visualize the distance
ggplot(performance$scenarioTable,
aes(x = indicator,
y = performance,
color = indicator)) +
geom_point() +
geom_hline(yintercept =
min(performance$scenarioTable$performance),
linetype = "dashed", color = "red") +
ylim(0, 1)