ursa_as: Create raster image from R objects or GDAL raster files.

In ursa: Non-Interactive Spatial Tools for Raster Processing and Visualization

Create raster image from R objects or GDAL raster files.

Description

as.ursa converts R base objects matrix, array, numeric, data.frame list, sp objects SpatialGridDataFrame, SpatialPixelsDataFrame and SpatialPointsDataFrame, raster objects raster, stack and brick, and GDAL raster files (using functions from rgdal package) to ursaRaster object.

Usage

as.ursa(obj, ...)
as_ursa(obj, ...)

Arguments

obj	R object for coercion
...	Depending on class of obj, arguments are passed to repsective functions.

Details

as_ursa is a synonym to as.ursa.

This is a high-level function to create ursaRaster objects. The follwed classes of R objects are implemented:

‘Data Class’	‘Appropriate method’
array	ursa_new
matrix	ursa_new
numeric	ursa_new
data.frame	allocate
SpatialPointsDataFrame (sp)	allocate
SpatialPixelsDataFrame (sp)	allocate
SpatialGridDataFrame (sp)	ursa_new
list of ursaRaster objects	unlist
list returned by sf::gdal_read	ursa_new
list (general)	Items $x and $y are required, If lengths of $x and $y are equal to dim of data, then allocate, else: 1) raster grid is defined from $x and $y, 2) ursa_new is called.
ggmap (ggmap)	ursa_new.
raster (raster)	ursa_new.
brick (raster)	ursa_new.
stack (raster)	ursa_new.
bitmap (magick)	ursa_new.
character (GDAL supported file name)	read_gdal.

Generally, allocate is used for objects with non-regular grid, and ursa_new is used for regular grids. The raster grid is defined from object properties or from sessional grid.

Color tables are supported for GDAL file names and raster objects (raster, brick, stack).

For ENVI *.hdr Labelled Raster Files there are alternatives:

1. Read object with GDAL (read_gdal);

2. Read object without GDAL (read_envi).

Value

Object of class ursaRaster

Author(s)

Nikita Platonov [e-mail]

Examples

session_grid(NULL)
a1 <- as.ursa(volcano)
print(a1)
display(a1)

session_grid(NULL)
b <- ursa_dummy(mul=1/16,bandname=format(Sys.Date()+seq(3)-1,"%A"))
print(b)

c1 <- b[[1]] ## equal to 'c1 <- as.matrix(b[1],coords=TRUE)'
str(c1)
b1a <- as.ursa(c1)
print(c(original=b[1],imported=b1a))
print(c(projection.b1a=ursa_proj(b1a)))
session_grid(NULL)
b1b <- as.ursa(c1$z)
print(b1b)
print(c(projection.b1b=ursa_proj(b1b)))

c2 <- as.data.frame(b)
str(c2)
session_grid(NULL)
b2a <- as.ursa(c2)
print(b2a)

session_grid(NULL)
attr(c2,"crs") <- NULL
b2b <- as.ursa(c2)
print(b2b)
print(ursa_grid(b2b))

c3 <- unclass(as.matrix(b,coords=TRUE))
str(c3)
session_grid(b)
b3a <- as.ursa(c3)
print(b3a)
print(ursa_grid(b3a))
session_grid(NULL)
b3b <- as.ursa(c3)
print(b3b)
print(ursa_grid(b3b))

c4 <- as.array(b)
str(c4)
session_grid(b)
b4a <- as.ursa(c4)
print(b4a)
print(ursa_grid(b4a))
session_grid(NULL)
b4b <- as.ursa(c4)
print(b4b)
print(ursa_grid(b4b))

n <- 20
c5 <- data.frame(y=runif(n,min=1000000,max=5000000)
                ,x=runif(n,min=-3000000,max=1000000)
                ,value=runif(n,min=0,max=10))
print(head(c5))
session_grid(b)
b5a <- as.ursa(c5)
print(b5a)
 ## to avoid over-timing during tests -- begin
   display(b5a)
 ## to avoid over-timing during tests -- end
session_grid(NULL)
b5b <- as.ursa(c5)
print(b5b)
 ## to avoid over-timing during tests -- begin
   display(b5b)
 ## to avoid over-timing during tests -- end

# b6 <- as.ursa(system.file("pictures/erdas_spnad83.tif",package="rgdal"))
b6 <- as.ursa(system.file("tif/geomatrix.tif",package="sf"))
print(b6)
display(b6,pal=c("black","white"),coast=FALSE,col="orange")

 ## package 'raster' is required -- begin
if (requireNamespace("raster")) {
   r <- raster::brick(system.file("external/rlogo.gri",package="raster"))
   print(r)
   b7 <- as.ursa(r)
   ursa_proj(b7) <- ""
   print(b7)
   display_rgb(b7)
}
 ## package 'raster' is required -- end

ursa documentation built on April 3, 2025, 6 p.m.