readGDAL {rgdal} | R Documentation |
The functions read or write GDAL grid maps. They will set the spatial reference system if available.
readGDAL(fname, offset, region.dim, ..., half.cell=c(0.5, 0.5), silent = FALSE) writeGDAL(dataset, fname, drivername = "GTiff", type = "Float32", mvFlag = NA, options="" )
fname |
file name of grid map |
offset |
Number of rows and columns from the origin (usually the upper left corner) to begin reading from; presently ordered (y,x) - this may change |
region.dim |
The number of rows and columns to read from the dataset; presently ordered (y,x) - this may change |
half.cell |
Used to adjust the intra-cell offset from corner to centre, usually as default, but may be set to c=(0,0) if needed; presently ordered (y,x) - this may change |
silent |
logical; if TRUE, comment is suppressed |
... |
arguments passed to either getRasterData , or
getRasterTable , depending on rotation angles (see below);
see the rgdal documentation for the available options (subsetting
etc.) |
dataset |
object of class SpatialGridDataFrame-class or SpatialPixelsDataFrame-class |
drivername |
GDAL driver name |
type |
GDAL write data type (others than this default have not been tested) |
mvFlag |
missing value flag for output file |
options |
driver-specific options to be passed to the GDAL driver |
read.GDAL
returns the data in the file as a Spatial object.
Usually, GDAL maps will be north-south oriented, in which case the rgdal
function getRasterData
is used to read the data, and an object
of class SpatialGridDataFrame-class is returned.
Some map formats supported by GDAL are not north-south oriented grids. If
this is the case, readGDAL
returns the data as a set of point
data, being of class SpatialPointsDataFrame-class. If the points
are on a 45 or 90 degree rotated grid, you can try to enforce gridding
later on by e.g. using gridded(x)=TRUE
.
Edzer J. Pebesma, e.pebesma@geo.uu.nl
as.image.SpatialGridDataFrame
, image
, readAsciiGrid
x <- readGDAL(system.file("external/test.ag", package="sp")[1]) class(x) image(x) summary(x) x@data[[1]][x@data[[1]] > 10000] <- NA summary(x) image(x) x <- readGDAL(system.file("external/simple.ag", package="sp")[1]) class(x) image(x) summary(x) y = readGDAL(system.file("pictures/Rlogo.jpg", package = "rgdal")[1]) summary(y) spplot(y, zcol=1:3, names.attr=c("red","green","blue"), col.regions=grey(0:100/100), main="example of three-layer (RGB) raster image", as.table=TRUE) data(meuse.grid) gridded(meuse.grid) = ~x+y proj4string(meuse.grid) = CRS("+init=epsg:28992") fn <- tempfile() writeGDAL(meuse.grid["dist"], fn) mg2 <- readGDAL(fn) proj4string(mg2) SP27GTIF <- readGDAL(system.file("pictures/SP27GTIF.TIF", package = "rgdal")[1]) summary(SP27GTIF) image(SP27GTIF, col=grey(1:99/100)) cea <- readGDAL(system.file("pictures/cea.tif", package = "rgdal")[1]) summary(cea) image(cea, col=grey(1:99/100)) erdas_spnad83 <- readGDAL(system.file("pictures/erdas_spnad83.tif", package = "rgdal")[1]) summary(erdas_spnad83) image(erdas_spnad83, col=grey(1:99/100))