image.SpatialGridDataFrame {sp} | R Documentation

## image gridded spatial data, or convert to format for image

### Description

Convert gridded data in SpatialGridDataFrame to image format; call image on data in SpatialGridDataFrame format

### Usage

    image.SpatialGridDataFrame(x, attr = 1, xcol = 1, ycol = 2, asp = 1, axes = FALSE, ...)
    as.image.SpatialGridDataFrame(x, xcol = 1, ycol = 2)

### Arguments

`x` | object of class SpatialGridDataFrame
`attr` | column number of attribute variable; this may be the column name in the data.frame of `data` (as.data.frame(data)), or a column number
`xcol` | column number of x-coordinate, in the coordinate matrix
`ycol` | column number of y-coordinate, in the coordinate matrix
`asp` | aspect ratio of unit x and unit y axis
`axes` | logical; should coordinate axes be drawn?
`...` | arguments passed to image, see examples

### Value

`as.image.SpatialGridDataFrame` returns the list with elements `x` and `y`, containing the coordinates of the cell centres of a matrix `z`, containing the attribute values in matrix form as needed by image.

### Note

Providing `xcol` and `ycol` attributes seems obsolete, and it is for 2D data, but it may provide opportunities for plotting certain slices in 3D data. I haven't given this much thought yet.

filled.contour seems to misinterpret the coordinate values, if we take the image.default manual page as the reference.

### Author(s)

Edzer J. Pebesma

### References

### See Also

image.default, SpatialGridDataFrame-class, levelplot in package `lattice`

### Examples

    data(meuse.grid)
    coordinates(meuse.grid) = c("x", "y") # promote to SpatialPointsDataFrame
    gridded(meuse.grid) = TRUE            # promote to SpatialGridDataFrame
    image(meuse.grid["dist"], main = "Distance to river Meuse")
    data(meuse)
    coordinates(meuse) = c("x", "y")
    points(coordinates(meuse), pch = "+")

[Package sp version 0.7-12 Index]