This indicator estimates the number of full-time jobs created by commercial urban agriculture initiatives in your city. It uses a range of jobs per square meter to create the median and the confidence interval of the number of jobs by simulating a random uniform distribution of 1000 values within the provided range.
Usage
edible_jobs(
x,
jobs = c(0.000163, 0.022),
edible = NULL,
area_col = "edible_area",
interval = 0.95,
verbose = FALSE
)Arguments
- x
An 'sf' object with the urban model of your city and a 'land_use' column with categories of urban features.
- jobs
A vector of length 2 with the range of jobs created by square meter of edible gardens.
- edible
The categories in 'land_uses' that represent commercial edible gardens. If NULL, the land_uses from 'city_land_uses' dataset are used where jobs is TRUE.
- area_col
The column to be used as the area of each feature. If NULL, the area is calculated with sf::st_area()
- interval
A numeric value with the confidence interval returned by the function.
- verbose
If TRUE, the indicators returns a vector (N=1000) with all simulated values.
Value
If verbose is FALSE, it returns a named vector with the median and the low and high confidence intervals. Otherwise, it returns a vector of length 1000 with all simulated values.
Examples
# First, we set a scenario with commercial gardens that create jobs
scenario <- set_scenario(city_example, pCommercial = 1, quiet = TRUE)
# Get the 95% confidence interval
edible_jobs(scenario, interval = 0.95)
#> 5% 50% 95%
#> 166.2169 1486.2948 2795.3369
# Get the raw values from the Monte Carlo simulation and adjust the number of jobs by square meter.
result <- edible_jobs(scenario, jobs = c(0.02, 0.03), verbose = TRUE)
result[1:10]
#> [1] 2766.513 3132.452 4013.966 3308.472 2951.240 3003.976 3397.788 3508.167
#> [9] 3297.537 3378.124