| query_points {gdalcubes} | R Documentation |
This function will overlay provided spatiotemporal points with a data cube and return all band values of the cells for each query point, as a data.frame where rows correspond to points and columns represent bands. If needed, point coordinates are automatically transformed to the SRS of the data cube.
query_points(x, px, py, pt, srs)
x |
source data cube |
px |
vector of x coordinates |
py |
vector of y coordinates |
pt |
vector of date/ time coordinates |
srs |
spatial reference system string identifer (as GDAL understands) |
Date and time of the query points can be provided as vector of class character, Date, or POSIXct.
a data.frame with one row per point and one column per data cube band or variable
# 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="2018-01-01", t1="2018-12-02"),
srs="EPSG:32618", nx = 497, ny=526, dt="P14D")
L8.cube = raster_cube(L8.col, v)
L8.rgb = select_bands(L8.cube, c("B02", "B03", "B04"))
x = seq(from = 388941.2, to = 766552.4, length.out = 10)
y = seq(from = 4345299, to = 4744931, length.out = 10)
t = seq(as.Date("2018-01-01"), as.Date("2018-12-02"), length.out = 10 )
query_points(L8.rgb, x, y, t, srs(L8.rgb))