This indicator estimates the food (in kg/year) produced by urban agriculture initiatives in your city. It uses a range of production for each type of initiative 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
food_production(
x,
edible_df = 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.
- edible_df
A dataframe of categories that are considered as urban agriculture with three columns:
'land_uses': Column with the land_use to be considered in the calculations corresponding to 'land_use' column in 'x'.
'food1': The low range of food production in each land_use (in kg/year/m2).
'food2': The high range of food production of each land_use (in kg/year/m2).
- 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 land_use.
- 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 (in kg/year). Otherwise, it returns a vector of length 1000 with all simulated values (in kg/year)
Examples
# Estimate the food production within 95% confidence interval
food_production(city_example, interval = 0.95, verbose = FALSE)
#> 5% 50% 95%
#> 45.7319 191.3548 335.5519
# Get the raw values instead of the confidence interval
result <- food_production(city_example, verbose = TRUE)
result[1:10]
#> [1] 110.40829 330.28469 159.89522 300.02355 325.68234 67.75734 111.05618
#> [8] 102.54753 215.10314 303.94120