tradeoff_mod: Spatial tradeoffs model
In marcusspiegel/agroEcoTradeoff: Landuse Tradeoff analysis model

Description Usage Arguments Details Value Note Examples

Master module that calls four major modules and associated helper functions, to create a single land use tradeoff scenario.

1 2	tradeoff_mod(prod_targ, ybetas, cbetas, input_key = "ZA", ybeta_update = 1, exist_list = NULL, ctype = "+", silent = TRUE)

`prod_targ`	Production targets passed as list. See examples for format.
`ybetas`	list of 2 rasters or 2 vectors providing yield modifications
`cbetas`	Vector of constraints to apply to land use. See examples.
`input_key`	Country/location code indicating input data to load.
`ybeta_update`	1 (default) or 0 - determines whether yield_mod_* is run.
`ctype`	Specific multiplicative ("X") or additive ("+") constraints
`silent`	Silent or verbose mode (TRUE [default] or FALSE)

Much of the detail of running the model, and examples that help to illustrate it, are in the examples for the individual model components, including checks for consistency between "D" and "R" versions.

Data.frame of impacts, and data.table referencing conversions.

The impacts module has to be fixed still to not double-count impacts resulting from multi-season cropping in converted pixels.

# Some inputs
load("data/cropnames.rda")
rc <- run_code(input_key = "ZA")

# # dummy climate/irrigation modifiers
# dfact <- c(0.9, 1.2)
# ybetas <- lapply(1:2, function(x) {
#   m <- brick("external/ext_data/ZA-crop-areas.tif")
#   r <- m
#   r <- setValues(r, values = rnorm(n = ncell(r) * nlayers(r), mean = dfact[x],
#                  sd = 0.05))
# nm_up(mask(r, m, maskvalue = 0), cropnames)
# })

ybetas <- list(1, 1)
prod_targ <- c("maize" = 4, "cassava" = 2, "ground" = 2, "cotton" = 2,
               "soy" = 2, "pulse" = 2, "sunflower" = 2, "sugarcane" = 2,
               "wheat" = 2)

# cbeta vector
cbetas <- c(0.5, 0.5, 0, 0)
names(cbetas) <- c("Ag", "C", "bd", "cost")

# Comparing the two versions
system.time(tdt <- tradeoff_mod(prod_targ, ybetas, cbetas))  # 2.5 seconds
system.time(tdr <- tradeoff_mod(prod_targ, ybetas, cbetas, input = "R"))  # 6
identical(tdt$impacts, tdr$impacts)  # check output stats for consistency

CRSobj <- projection(raster("external/ext_data/ZA-carbon-priorities.tif"))
plot(dt_to_raster(tdt$conv, CRSobj = CRSobj) - tdr$conv)  # check maps