gdalcubes (version 0.2.5)

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")

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)

Value

a proxy data cube object

Details

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

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="2018-12"),
              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

# }
# NOT RUN {
plot(L8.filled, rgb=3:1, zlim=c(5000,12000))
# }
# NOT RUN {
# }

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