What is sen2r for

The main functions offered by the package are here above listed:

• search the list of available SAFE archives over a user defined area of interest in a certain time window;
• download them, in the level 1C or 2A depending on user requirements¹;
• if level 2A images are not available, download and automatically correct with Sen2Cor the corresponding 1C images;
• perform geometric transformation: merge adjacent tiles, clip (and eventually mask) on the area of interest, reproject and/or resize the output;
• apply a cloud mask, basing of the automatic classification map available in level 2A product;
• compute spectral indices;
• generate RGB images.

Installation and documentation

The source code of the package is hosted on GitHub at ranghetti/sen2r repository (it will be published on CRAN in future) and documented here. The Installation page provides the instructions for installing the package (and its dependences) on several Linux distributions and over Windows. Support for MacOS was not yet provided, but Mac users can use it in a Docker image (see the page Run in a Docker container).

Launching sen2r with the GUI

The most useful feature of sen2r, especially for users with limited R skills, is the possibility to set the parameters of the processing using a graphical user interface. To do it, simply launch the command

sen2r()

Using the GUI is quite self-explaining (some help popups are present in the interface – to see them, click on the icons “”). Here below some screenshots.

Non-interactive execution

The function sen2r() can also be launched without opening the GUI, setting the parameters of the processing using the arguments of the function. To know how to set them, see the sen2r() documentation. See an example here above:

sen2r(
  gui = FALSE,
  timewindow = c(as.Date("2019-01-01"), Sys.Date()),
  extent = "~/sen2rtest/my_extent.kml", extent_name = "Myextent",
  list_prods = c("BOA"),
  list_indices = c("NDVI", "MSAVI2"),
  mask_type = "cloud_and_shadow",
  max_mask = 50, mask_smooth = 30, mask_buffer = 30,
  extent_as_mask = TRUE,
  path_l1c = "~/SAFE", path_l2a = "~/SAFE", path_out = "~/sen2rtest/out1"
)

Moreover, it is possible to interactively set the parameters in a first time, and to non-interactively launch the processing later (or on a different machine). This can be useful i.e. in order to schedule a recurrent execution of a processing chain, so ti keep a local archive updated (I will show how to do it in a future post). To do it, just set the GUI and then click on “Save options as…”: this allows to export a JSON file containing the parameters (which can be eventually edited also by hand). Then, launch the function with

sen2r("~/sen2rtest/param.json")

using the path of the paramter file as argument.

If the user wants to use a saved JSON file changing only some parameters, he can also pass both the file path and some arguments:

sen2r(
  "~/sen2rtest/param.json",
  extent = "~/sen2rtest/another_extent.kml", extent_name = "Anothersite",
  path_out = "~/sen2rtest/out2"
)

this will reproduce the same processing chain in a different area of interest.

sen2r() is not the only function provided by the package; other ones are available to perform intermediate steps or specific tasks. The reference page provides a list of them.

Conclusions

The new package sen2r provides ready to use functions to facilitate the processing of Sentinel-2 images, especially for R users but also for people with limited R skills /thanks to the GUI). Further development is required to implement new features and to improve the stability; users are encouraged to report bugs and suggestions opening an issue on the GitHub page of the package.

@Manual{sen2r,
  title  = {sen2r: an R toolbox to find, download and preprocess Sentinel-2 data},
  author = {Luigi Ranghetti and Lorenzo Busetto},
  year   = {2019},
  note   = {R package version 1.0.0},
  doi    = {10.5281/zenodo.1240384},
  url    = {http://sen2r.ranghetti.info},
}