Set land types and their attributes

Usage

clue_landtype(
  scene,
  name,
  resistance,
  suitability,
  production = NULL,
  conversion = NULL,
  neighborhood = NULL,
  preference = NULL
)

Arguments

scene

scene(1)
the CLUE scene to which to add a land type.

name

character(1)
name of the land type.

resistance

numeric(1)
the relative conversion resistance to land change.

suitability

data.frame
obligatory table of the result of regression analysis. Has at least two rows. Must have columns

driver: from line 2 onward the name of the driver (must correspond to names of gridded items of type = "driver" as defined in clue_gridded) and
beta: the respective regression coefficient (beta_{1, 2, ...}).

The first row must have the driver "const" with the respective beta_0 value.

production

data.frame
optional table of goods and services produced by this land type (for the demand to produce, see clue_goods). Each row contains one good. Must have 3 columns

name: the name of the good or service,
amount: how much each cell in the map produces and
priority: an integer value that indicates the priority with which the good or service is produced by the focal land type. If a good is produced by more than one land type, the land type with a smaller number here is produced with a higher priority.

conversion

data.frame
optional table of land types into which this land type can be converted. Each row contains one type into which it can be converted. Must have a columns

to: name of the land type into which to convert and
label: name of the conversion process,

and optionally, for the details of conversion one of

min: number of time-steps that need to pass until the conversion can take place,
max: number of time-steps within which the conversion can take place,
auto: number of time-steps after which a conversion must take place (from local dynamics and not to fulfill demand of a good or service) or
mask: name of a gridded item (with values 0, 1 and NA/-9999) that indicates with value 1 where conversion can take place and with 0, where they cannot take place.

neighborhood

data.frame
optional table of neighborhood parameters. Has at least four rows. Must have columns

type: from line 4 onward the name of the land type that influences the suitability of the focal land type if it's in the neighborhood (must correspond to names of other land types defined with this function) and
beta: the respective regression coefficient (beta_{1, 2, ...})

The first row has the number of a kernel that must have been defined with clue_gridded and the second row the weight assigned to the neighborhood function, and the third row must have the type "const" with the respective beta_0 value.

preference

data.frame
optional table of suitability preferences. One row only. Must have columns layer and weight. Layer names must correspond to names of gridded items of type = "preference" as defined in clue_gridded.

Suitability

mention specifics about suitabilities

Production

mention specifics about production

Conversion

Conversions are implicitly always set from a focal class to itself. By default, this conversion is allowed indefinitely and one does not have to set it. However, if one wants to limit the persistence of a land type to, e.g., 5 years in a row, one needs to specify

clue_landtype(...,
              name = "it",
              conversion = tibble(to = "it",
                                  label = "limit_self",
                                  max = 5))

Neighborhood

mention specifics about neighborhood

Preference

mention specifics about preferences