Create and Process a Sentinel-2 Data Cube

This function generates a data cube from a Sentinel-2 image collection by aggregating the pixel values over a specified spatial extent and date range.

Usage

get.sentinel2_cube(
  s_collection,
  shape,
  date_range,
  aggregation_method = "mean",
  resampling_method = "bicubic",
  get.dataset = T
)

Arguments

s_collection

An object representing the Sentinel-2 image collection, typically created using a function like get.satellite_collection().

shape

An object defining the spatial extent for the data cube, such as a polygon or a raster extent.

date_range

A character vector of length 2 specifying the start and end dates in "YYYY-MM-DD" format for the aggregation period.

aggregation_method

A character string indicating the method of aggregation to apply to the pixel values. Default is "mean". Other options may include "min", "max", "median", or "first"

resampling_method

A character string indicating the method of resampling to apply to the pixel values. Default is "bicubic". Other options may include "near", or "bilinear".

get.dataset

A logical value indicating whether to return the dataset of processed data (default is TRUE).

Value

A processed data cube containing aggregated pixel values over the specified shape and date range. If get.dataset is TRUE, it returns a dataset object; otherwise, it returns the cube object.

Examples

if (FALSE) { # \dontrun{
# Example usage of the get.sentinel2_cube function

# Assuming s_collection has been obtained from a previous call
s_collection <- get.satellite_collection("your_scenario_here", "sentinel-2-l2a",
                                          c("2023-01-01", "2023-01-31"),
                                          cloud_threshold = 20)

# Define the spatial shape (e.g., a polygon)
poly <- list(rbind(c(4.8, 52.2), c(4.8, 52.4), c(5.0, 52.4), c(5.0, 52.2), c(4.8, 52.2)))
shape <- sf::st_as_sf(data.frame(id = 1,
                                  geometry = sf::st_sfc(sf::st_polygon(poly))),
                       crs = 4326)

# Define date range for aggregation
date_range <- c("2023-01-01", "2023-01-31")

# Retrieve the Sentinel-2 data cube
sentinel2_cube <- get.sentinel2_cube(s_collection, shape, date_range,
                                      aggregation_method = "mean", get.dataset = TRUE)

# Print the resulting data cube details
print(sentinel2_cube)
} # }