as.data.frame: Coerce objects to data.frame

In simonmoulds/lulcc2: Land Use Change Modelling in R

Description

This function extracts data from all raster objects in LulcRasterStack or ExpVarRasterStack objects for a specified timestep.

Usage

## S3 method for class 'ExpVarRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

## S3 method for class 'DiscreteLulcRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

## S3 method for class 'ContinuousLulcRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

## S4 method for signature 'ExpVarRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

## S4 method for signature 'DiscreteLulcRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

## S4 method for signature 'ContinuousLulcRasterStack'
as.data.frame(x, row.names = NULL,
  optional = FALSE, cells, t, ...)

Arguments

x	an ExpVarRasterStack or LulcRasterStack object
row.names	NULL or a character vector giving the row.names for the data.frame. Missing values are not allowed
optional	logical. If TRUE, setting row names and converting column names (to syntactic names: see make.names) is optional
cells	index of cells to be extracted, which may be a SpatialPoints* object or a numeric vector representing cell numbers (see raster::extract)
t	numeric indicating the time under consideration
...	additional arguments (none)

Details

If x is a DiscreteLulcRasterStack object the raster corresponding to t is first transformed to a RasterBrick with a boolean layer for each class with raster::layerize.

Value

A data.frame.

See Also

as.data.frame, LulcRasterStack, ExpVarRasterStack, partition

Examples

## Not run: 

## Plum Island Ecosystems

## load observed land use maps
lu <- DiscreteLulcRasterStack(x=stack(pie[1:3]),
                              categories=c(1,2,3),
                              labels=c("Forest","Built","Other"),
                              t=c(0,6,14))

## explanatory variables
idx <- data.frame(var=c("ef_001","ef_002","ef_003"),
                  yr=c(0,0,0),
                  dynamic=c(FALSE,FALSE,FALSE))

ef <- ExpVarRasterStack(x=stack(pie[4:6]), index=idx)

## separate data into training and testing partitions
part <- partition(x=lu[[1]], size=0.1, spatial=TRUE)
df1 <- as.data.frame(x=lu, cells=part[["all"]], t=0)
df2 <- as.data.frame(x=ef, cells=part[["all"]], t=0)
df <- cbind(df1,df2)


## End(Not run)

simonmoulds/lulcc2 documentation built on Dec. 23, 2021, 2:24 a.m.