filter_pixel: Filter data cube pixels by a user-defined predicate on band values

Description

Create a proxy data cube, which evaluates a predicate over all pixels of a data cube. For all pixels that fulfill the predicate, the original band values are returned. Other pixels are simply filled with NANs. The predicate may access band values by name.

Usage

filter_pixel(cube, pred)

Arguments

cube

source data cube

pred

predicate to be evaluated over all pixels

Value

a proxy data cube object

Details

gdalcubes uses and extends 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.

Examples

Run this code

# 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")) 
}

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="2018-01", 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.filtered = filter_pixel(L8.ndvi, "NDVI > 0.5") 
L8.ndvi.filtered
# }

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