The TheiaR package intends to provide a clean interface to download and manage data issued by Theia through its API (Application Programming Interface).
The basic functionalities are (for now):
.meta4file) obtained from Theia website.
NOTE: ongoing development, more functionalities shall be added in the future
First, load the package.
To search and download data from Theia, you will need to register to their website.
NOTE: In order to use Landsat or SpotWorldHeritage products, you'll need to make a first manual download to agree to the license and validate your account.
The first step is to create a collection of tile(s). This can be done either from a query or from a cart file.
A query is simply a named
list of search terms. For example:
myquery <- list(collection = "SENTINEL2", town = "Grenoble", start.date = "2018-07-01", end.date = "2018-07-06")
will create a query to Theia database, looking for tiles from Sentinel2 satellite around Grenoble, between 2018-07-01 and 2018-07-31.
It accepts the following terms. Terms with a
* are mandatory.
collection*: The collection to look for. Accepted values are:
platform: The platform to look for. Accepted values are:
To specify the location of the tiles, several alternatives are available. You can specify the town around which you want your data with:
You can specify directly the tile ID if you know it:
You can specify a point by giving its x/y coordinates:
latitude: The x coordinate of a point.
longitude: The y coordinate of a point.
Or you can specify a rectangle by giving its min/max coordinates:
latmin: The minimum latitude to search.
latmax: The maximum latitude to search.
lonmin: The minimum longitude to search.
lonmax: The maximum longitude to search.
Finally, you can filter results by giving the date range and the maximum cloud cover:
max.clouds: The maximum of cloud cover wanted (0-100).
start.date: The first date to look for (format:
end.date: The last date to look for (format:
You can then create your collection with:
mycollection <- TheiaCollection$new(query = myquery, dir.path = ".")
dir.path is the path you want your tiles to be downloaded. If tiles are
already present in
dir.path, they will be checked by computing a checksum and
comparing it to the hash provided by Theia (only available for Sentinel2 data,
no hash is provided for other collections, and files are then assumed to be
correct). This ensures that the files have been correctly downloaded.
print(mycollection) #> An collection of tiles from Theia #> #> Number of tiles: 11 #> Directory path : '.' #> #> Obtained from query
Alternatively, you can download a cart from Theia. To create a cart, login to
Theia website, make a search
for tiles, and add wanted tiles to your cart. Then, download your cart and save
.meta4 file to your disk.
You can then create your collection using this file:
cart.path <- system.file("extdata", "cart.meta4", package = "theiaR") mycollection <- TheiaCollection$new(cart.path = cart.path, dir.path = ".") print(mycollection) #> An collection of tiles from Theia #> #> Number of tiles: 2 #> Directory path : '.' #> #> Obtained from cart file
As above, it will check the hash of files if they are already present in
The next step is to download your collection. You can get the status of your collection by running:
mycollection$status #> tile exists checked correct #> SENTINEL2B_20190128-104831-308_L2A_T31TGK_D FALSE FALSE FALSE #> SENTINEL2A_20190113-104826-809_L2A_T31TGK_D FALSE FALSE FALSE
To download all tiles in a collection, simply run:
mycollection$download(auth = myauth)
where myauth is the path to file storing your Theia credentials. If it does not exist yet, you will be securely prompted for your login and password, and the file will be created.
This will check if files are present, check their hashes, and download them if needed (if files do not exist or checksums are wrong). To overwrite existing files, run:
mycollection$download(auth = myauth, overwrite = TRUE)
Once you have downloaded every tile (as an archive), you can read images contained in the archive without extracting it. This allows to save a lot of disk space.
First, get a list of bands available in the tiles by running:
Then you can read bands with:
images.list <- mycollection$read(bands = c("B2", "B3")
bands is a vector with bands names.
It will return a list of
RasterLayer objects, that you can manipulate with
functions from the
If you want to extract full archives, you can run:
file.path <- mycollection$extract()
which will extract tiles into the same directory as the archives.
Thanks to Olivier Hagolle for his work on
(github), which has inspired