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66 lines
2.9 KiB
R
66 lines
2.9 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/window.R
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\name{window_time}
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\alias{window_time}
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\title{Apply a moving window operation over the time dimension of a data cube}
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\usage{
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window_time(x, expr, ..., kernel, window)
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}
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\arguments{
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\item{x}{source data cube}
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\item{expr}{either a single string, or a vector of strings defining which reducers wlil be applied over which bands of the input cube}
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\item{...}{optional additional expressions (if expr is not a vector)}
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\item{kernel}{numeric vector with elements of the kernel}
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\item{window}{integer vector with two elements defining the size of the window before and after a cell, the total size of the window is window[1] + 1 + window[2]}
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}
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\value{
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proxy data cube object
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}
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\description{
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Create a proxy data cube, which applies one ore more moving window functions to selected bands over pixel time series of a data cube.
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The function can either apply a built-in aggregation function or apply a custom one-dimensional
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convolution kernel.
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}
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\details{
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The function either applies a kernel convolution (if the \code{kernel} argument is provided) or a general reducer function
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over moving temporal windows. In the former case, the kernel convolution will be applied over all bands of the input
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cube, i.e., the output cube will have the same number of bands as the input cubes. If a kernel is given and the \code{window} argument is missing,
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the window will be symmetric to the center pixel with the size of the provided kernel. For general reducer functions, the window argument must be provided and
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several expressions can be used to create multiple bands in the output cube.
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Notice that expressions have a very simple format: the reducer is followed by the name of a band in parantheses. You cannot add
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more complex functions or arguments.
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Possible reducers include "min", "max", "sum", "prod", "count", "mean", and "median".
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}
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\note{
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Implemented reducers will ignore any NAN values (as na.rm=TRUE does).
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This function returns a proxy object, i.e., it will not start any computations besides deriving the shape of the result.
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}
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\examples{
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# create image collection from example Landsat data only
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# if not already done in other examples
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if (!file.exists(file.path(tempdir(), "L8.db"))) {
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L8_files <- list.files(system.file("L8NY18", package = "gdalcubes"),
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".TIF", recursive = TRUE, full.names = TRUE)
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create_image_collection(L8_files, "L8_L1TP", file.path(tempdir(), "L8.db"), quiet = TRUE)
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}
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L8.col = image_collection(file.path(tempdir(), "L8.db"))
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v = cube_view(extent=list(left=388941.2, right=766552.4,
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bottom=4345299, top=4744931, t0="2018-01", t1="2018-07"),
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srs="EPSG:32618", nx = 400, dt="P1M")
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L8.cube = raster_cube(L8.col, v)
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L8.nir = select_bands(L8.cube, c("B05"))
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L8.nir.min = window_time(L8.nir, window = c(2,2), "min(B05)")
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L8.nir.min
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L8.nir.kernel = window_time(L8.nir, kernel=c(-1,1), window=c(1,0))
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L8.nir.kernel
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}
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