gdalcubes (version 0.3.1)

apply_pixel.cube: Apply arithmetic expressions over all pixels of a data cube

Description

Create a proxy data cube, which applies arithmetic expressions over all pixels of a data cube. Expressions may access band values by name.

Usage

# S3 method for cube
apply_pixel(x, expr, names = NULL, keep_bands = FALSE, ..., FUN)

Arguments

x

source data cube

expr

character vector with one or more arithmetic expressions (see Details)

names

optional character vector with the same length as expr to specify band names for the output cube

keep_bands

logical; keep bands of input data cube, defaults to FALSE, i.e. original bands will be dropped

...

not used

FUN

user-defined R function that is applied on all pixels (see Details)

Value

a proxy data cube object

Details

The function can either apply simple arithmetic C expressions given as a character vector (expr argument), or apply a custom R reducer function if FUN is provided.

In the former case, gdalcubes uses the tinyexpr library to evaluate expressions in C / C++, you can look at the library documentation to see what kind of expressions you can execute. Pixel band values can be accessed by name.

FUN receives values of the bands from one pixel as a (named) vector and should return a numeric vector with identical length for all pixels. Elements of the result vectors will be interpreted as bands in the result data cube.

Examples

# NOT RUN {
# create image collection from example Landsat data only 
# if not already done in other examples
if (!file.exists(file.path(tempdir(), "L8.db"))) {
  L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
                         ".TIF", recursive = TRUE, full.names = TRUE)
  create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db")) 
}

# 1. Apply a C expression
L8.col = image_collection(file.path(tempdir(), "L8.db"))
v = cube_view(extent=list(left=388941.2, right=766552.4, 
              bottom=4345299, top=4744931, t0="2018-04", t1="2018-06"),
              srs="EPSG:32618", nx = 497, ny=526, dt="P1M")
L8.cube = raster_cube(L8.col, v) 
L8.cube = select_bands(L8.cube, c("B04", "B05")) 
L8.ndvi = apply_pixel(L8.cube, "(B05-B04)/(B05+B04)", "NDVI") 
L8.ndvi

# }
# NOT RUN {
plot(L8.ndvi)
# }
# NOT RUN {
# 2. Apply a user defined R function
L8.ndvi.noisy = apply_pixel(L8.cube, names="NDVI_noisy", 
   FUN=function(x) {
       rnorm(1, 0, 0.1) + (x["B05"]-x["B04"])/(x["B05"]+x["B04"])
   })
L8.ndvi.noisy

# }
# NOT RUN {
plot(L8.ndvi.noisy)
# }
# NOT RUN {
 
# }