gdalcubes (version 0.7.0)

fill_time: Fill NA data cube pixels by simple time series interpolation

Description

Create a proxy data cube, which fills NA pixels of a data cube by nearest neighbor or linear time series interpolation.

Usage

fill_time(cube, method = "near")

Value

a proxy data cube object

Arguments

cube

source data cube

method

interpolation method, can be "near" (nearest neighbor), "linear" (linear interpolation), "locf" (last observation carried forward), or "nocb" (next observation carried backward)

Details

Please notice that completely empty (NA) time series will not be filled, i.e. the result cube might still contain NA values.

Examples

# 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"), quiet = TRUE) 
}
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="2018-12"),
              srs="EPSG:32618", nx = 497, ny=526, dt="P3M", aggregation = "median")
L8.cube = raster_cube(L8.col, v, mask=image_mask("BQA", bits=4, values=16))
L8.rgb = select_bands(L8.cube, c("B02", "B03", "B04"))
L8.filled = fill_time(L8.rgb, "linear")
L8.filled

# \donttest{
plot(L8.filled, rgb=3:1, zlim=c(5000,12000))
# }