Read/write between GDAL grid maps and Spatial objects

Share:

Description

The functions read or write GDAL grid maps. They will set the spatial reference system if available. GDALinfo reports the size and other parameters of the dataset. create2GDAL creates a GDAL data set from a SpatialGridDataFrame object, in particular to be able to save to GDAL driver formats that only permit copying rather than creation.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
 
readGDAL(fname, offset, region.dim, output.dim, band, p4s=NULL, ...,
 half.cell=c(0.5, 0.5), silent = FALSE, OVERRIDE_PROJ_DATUM_WITH_TOWGS84=NULL,
 allowedDrivers = NULL, options=NULL)
asSGDF_GROD(x, offset, region.dim, output.dim, p4s=NULL, ...,
 half.cell=c(0.5,0.5), OVERRIDE_PROJ_DATUM_WITH_TOWGS84=NULL)
writeGDAL(dataset, fname, drivername = "GTiff", type = "Float32",
 mvFlag = NA, options=NULL, copy_drivername = "GTiff", setStatistics=FALSE,
 colorTables = NULL, catNames=NULL)
create2GDAL(dataset, drivername = "GTiff", type = "Float32", mvFlag = NA,
 options=NULL, fname = NULL, setStatistics=FALSE, colorTables = NULL,
 catNames=NULL)
GDALinfo(fname, silent=FALSE, returnRAT=FALSE, returnCategoryNames=FALSE,
 returnStats=TRUE, returnColorTable=FALSE,
 OVERRIDE_PROJ_DATUM_WITH_TOWGS84=NULL, returnScaleOffset=TRUE,
 allowedDrivers = NULL, options=NULL)
GDALSpatialRef(fname, silent=FALSE, OVERRIDE_PROJ_DATUM_WITH_TOWGS84=NULL,
 allowedDrivers = NULL, options=NULL)

Arguments

fname

file name of grid map; in create2GDAL provides a way to pass through a file name with driver-required extension for sensitive drivers

x

A GDALReadOnlyDataset object

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

output.dim

The number of rows and columns to return in the created object using GDAL's method to take care of image decimation / replication; presently ordered (y,x) - this may change

band

if missing, all bands are read

p4s

PROJ4 string defining CRS, if default (NULL), the value is read from the GDAL data set

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 and non-fatal CPL driver errors suppressed

OVERRIDE_PROJ_DATUM_WITH_TOWGS84

logical value, default NULL, which case the cached option set by set_OVERRIDE_PROJ_DATUM_WITH_TOWGS84 is used. Ignored if the GDAL version is less than “1.8.0” or if the CPLConfigOption variable is already set; see getProjectionRef for further details

allowedDrivers

a character vector of suggested driver short names may be provided starting from GDAL 2.0

...

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, copy_drivername

GDAL driver name; if the chosen driver does not support dataset creation, an attempt is made to use the copy_drivername driver to create a dataset, and copyDatset to copy to the target driver

type

GDAL write data type, one of: ‘Byte’, ‘Int16’, ‘Int32’, ‘Float32’, ‘Float64’; ‘UInt16’, ‘UInt32’ are available but have not been tests

mvFlag

default NA, missing value flag for output file; the default value works for ‘Int32’, ‘Float32’, ‘Float64’, but suitable in-range value that fits the data type should be used for other data types, for example 255 for ‘Byte’, -32768 for ‘Int16’, and so on; see Details below.

options

driver-specific options to be passed to the GDAL driver; only available for opening datasets from GDAL 2.0; see copying and creation details below

setStatistics

default FALSE, if TRUE, attempt to set per-band statistics in the output file (driver-dependent)

colorTables

default NULL, if not NULL, a list of length equal to the number of bands, with NULL components for bands with no color table, or either an integer matrix of red, green, blue and alpha values (0-255), or a character vector of colours. The number of colours permitted may vary with driver.

catNames

default NULL, if not NULL, a list of length equal to the number of bands, with NULL components for bands with no category names, or a string vector of category names

returnRAT

default FALSE, if TRUE, return a list with a Raster Attribute Table or NULL for each band

returnCategoryNames

default FALSE, if TRUE, return a list with a character vector of CategoryNames or NULL for each band

returnStats

default TRUE, return band-wise statistics if avaliable (from 0.7-20 set to NA if not available)

returnColorTable

default FALSE; if TRUE return band-wise colour tables in a list attribute “ColorTables”

returnScaleOffset

default TRUE, return a matrix of bandwise scales and offsets

Details

In writeGDAL, if types other than ‘Int32’, ‘Float32’, ‘Float64’ are used, the “mvFlag” argument should be used to set a no data value other than the default NA. Note that the flag only replaces NA values in the data being exported with the value of the argument - it does not mark data values equal to “mvFlag” as missing. The value is stored in the file being written in driver-specific ways, and may be used when the file is read. When the default “mvFlag=NA” is used, no NoDataValue is written to the file, and the input data is written as is.

Also in writeGDAL, the “options” argument may be used to pass a character vector of one or more options to the driver, for example ‘options=“INTERLEAVE=PIXEL”’, or ‘options=c(“INTERLEAVE=PIXEL”, “COMPRESS=DEFLATE”)’. Typical cases are given in the examples below; it may also be necessary in some cases to escape quotation markes if included in the string passed to the driver.

Value

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-methods(x)=TRUE.

Warning

Some raster files may have an erroneous positive y-axis resolution step, leading to the data being flipped on the y-axis. readGDAL will issue a warning: Y axis resolution positive, examine data for flipping, when the step is positive, but this need not mean that the data are flipped. Examine a display of the data compared with your knowledge of the file to determine whether this is the case (one known case is interpolation files created under Qgis up to February 2010 at least). To retreive the correct orientation, use flipVertical.

Note

Non-fatal CPL errors may be displayed for some drivers, currently for the AIG ArcInfo 9.3 binary raster driver using GDAL >= 1.6.2; the data has been read correctly, but the contents of the info directory did not meet the specifications used to reverse engineer the driver used in GDAL (see http://trac.osgeo.org/gdal/ticket/3031)

Author(s)

Edzer Pebesma, Roger Bivand

See Also

image, asciigrid

Examples

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
library(grid)
GDALinfo(system.file("external/test.ag", package="sp")[1])
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)
x <- readGDAL(system.file("pictures/big_int_arc_file.asc", package="rgdal")[1])
summary(x)
cat("if the range is not 10000, 77590, your GDAL does not detect big\n")
cat("integers for this driver\n")
y = readGDAL(system.file("pictures/Rlogo.jpg", package = "rgdal")[1], band=1)
summary(y)
y = readGDAL(system.file("pictures/Rlogo.jpg", package = "rgdal")[1])
summary(y)
spplot(y, 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)
GDALinfo(fn)
writeGDAL(meuse.grid["dist"], fn, setStatistics=TRUE)
GDALinfo(fn)
mg2 <- readGDAL(fn)
proj4string(mg2)
SP27GTIF <- readGDAL(system.file("pictures/SP27GTIF.TIF", 
package = "rgdal")[1], output.dim=c(100,100))
summary(SP27GTIF)
image(SP27GTIF, col=grey(1:99/100))

GDALinfo(system.file("pictures/cea.tif", package = "rgdal")[1])
GDALSpatialRef(system.file("pictures/cea.tif", package = "rgdal")[1])
cea <- readGDAL(system.file("pictures/cea.tif", package = "rgdal")[1], 
output.dim=c(100,100))
summary(cea)
image(cea, col=grey(1:99/100))
fn <- system.file("pictures/erdas_spnad83.tif", package = "rgdal")[1]
erdas_spnad83 <- readGDAL(fn, offset=c(50, 100), region.dim=c(400, 400), 
output.dim=c(100,100))
summary(erdas_spnad83)
image(erdas_spnad83, col=grey(1:99/100))
erdas_spnad83a <- readGDAL(fn, offset=c(50, 100), region.dim=c(400, 400))
bbox(erdas_spnad83)
bbox(erdas_spnad83a)
gridparameters(erdas_spnad83)
gridparameters(erdas_spnad83a)
tf <- tempfile()
writeGDAL(erdas_spnad83, tf, drivername="GTiff", type="Byte", options=NULL)
all.equal(erdas_spnad83, readGDAL(tf))
writeGDAL(erdas_spnad83, tf, drivername="GTiff", type="Byte", 
options="INTERLEAVE=PIXEL")
all.equal(erdas_spnad83, readGDAL(tf))
writeGDAL(erdas_spnad83, tf, drivername="GTiff", type="Byte",
options=c("INTERLEAVE=PIXEL", "COMPRESS=DEFLATE"))
all.equal(erdas_spnad83, readGDAL(tf))

x <- GDAL.open(system.file("pictures/erdas_spnad83.tif", package = "rgdal")[1])
erdas_spnad83 <- asSGDF_GROD(x, output.dim=c(100,100))
GDAL.close(x)
summary(erdas_spnad83)
image(erdas_spnad83, col=grey(1:99/100))

tf <- tempfile()
xx <- create2GDAL(erdas_spnad83, type="Byte")
xxx <- copyDataset(xx, driver="PNG")
saveDataset(xxx, tf)
GDAL.close(xx)
GDAL.close(xxx)
GDALinfo(tf)

tf2 <- tempfile()
writeGDAL(erdas_spnad83, tf2, drivername="PNG", type="Byte")
GDALinfo(tf2)

GT <- GridTopology(c(0.5, 0.5), c(1, 1), c(10, 10))
set.seed(1)
SGDF <- SpatialGridDataFrame(GT, data=data.frame(z=runif(100)))
opar <- par(mfrow=c(2,2), mar=c(1,1,4,1))
image(SGDF, "z", col=colorRampPalette(c("blue", "yellow"))(20))
title(main="input values")
pfunc <- colorRamp(c("blue","yellow"))
RGB <- pfunc(SGDF$z)
SGDF$red <- RGB[,1]
SGDF$green <- RGB[,2]
SGDF$blue <- RGB[,3]
image(SGDF, red="red", green="green", blue="blue")
title(main="input RGB")
tf <- tempfile()
writeGDAL(SGDF[c("red", "green", "blue")], tf, type="Byte", drivername="PNG")
t1 <- readGDAL(tf)
image(t1, red=1, green=2, blue=3)
title(main="output PNG RGB")
par(opar)

t0 <- meuse.grid["ffreq"]
fullgrid(t0) <- TRUE
t0$ffreq <- as.integer(t0$ffreq)-1
# convert factor to zero-base integer
CT <- c("red", "orange", "green", "transparent")
CT
cN <- c("annual", "2-5 years", "infrequent")
tf <- tempfile()
writeGDAL(t0, tf, type="Byte", colorTable=list(CT), catNames=list(cN),
 mvFlag=3L)
attr(GDALinfo(tf, returnStats=FALSE, returnCategoryNames=TRUE),
 "CATlist")[[1]]
ds <- GDAL.open(tf)
displayDataset(ds)
t(col2rgb(getColorTable(ds)[1:4]))
GDAL.close(ds)

fn <- system.file("pictures/test_envi_class.envi", package = "rgdal")[1]
Gi <- GDALinfo(fn, returnColorTable=TRUE, returnCategoryNames=TRUE)
CT <- attr(Gi, "ColorTable")[[1]]
CT
attr(Gi, "CATlist")[[1]]
with <- readGDAL(fn)
with <- readGDAL(fn, silent=TRUE)
table(with$band1)
table(as.numeric(with$band1))
with1 <- readGDAL(fn, as.is=TRUE)
table(with1$band1)
spplot(with, col.regions=CT)
tf <- tempfile()
cN <- levels(with$band1)
with$band1 <- as.integer(with$band1)-1
writeGDAL(with, tf, drivername="ENVI", type="Int16", colorTable=list(CT),
 catNames=list(cN), mvFlag=11L)
cat(paste(readLines(paste(tf, "hdr", sep=".")), "\n", sep=""), "\n")
wGi <- GDALinfo(tf, returnColorTable=TRUE, returnCategoryNames=TRUE)
CTN <- attr(wGi, "ColorTable")[[1]]
CTN
attr(wGi, "CATlist")[[1]]
withN <- readGDAL(tf)
table(withN$band1)
withN1 <- readGDAL(tf, as.is=TRUE)
table(withN1$band1)
spplot(withN, col.regions=CTN)


# a file with scale and offset
fn <- system.file("pictures/scaleoffset.vrt", package = "rgdal")[1]
g <- GDALinfo(fn)
attr(g, 'ScaleOffset')
g