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The TheiaR package provides an efficient and clean interface to search, download and manage products from Theia website.
The basic functionalities are:
.meta4
file)
obtained from Theia website.RasterStack
objects (with the
raster
library)gdalcubes
objects (with the
gdalcubes
library)NOTE: 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.
You can install the latest stable version from Github with:
::install_github('norival/theiaR')
devtools
# or, to install the development version
::install_github('norival/theiaR', 'devel') devtools
Or, you can install it from CRAN:
isntall.packages('theiaR')
A workflow to search and download tiles would be something like:
library(theiaR)
# create a list containing the query
<- list(collection = "SENTINEL2",
myquery town = "Grenoble",
start.date = "2018-07-01",
end.date = "2018-07-06")
# create a collection from the query
<- TheiaCollection$new(query = myquery, dir.path = ".", check = TRUE)
mycollection
# check available tiles fro the query
$status
mycollection
# download the tiles into 'dir.path'
$download(auth = "path/to/auth/file.txt") mycollection
The first step is to create a collection of tile(s). This can be done either from a query or from a cart file (downloaded from Theia’s website).
A query is simply a named list
of search terms. For
example:
<- list(collection = "SENTINEL2",
myquery town = "Grenoble",
start.date = "2018-07-01",
end.date = "2018-07-06")
will create a query to Theia database, looking for tiles from Sentinel2 satellite around Grenoble, between 2018-07-01 and 2018-07-31.
See the vignette for all the available options.
You can then create your collection with:
<- TheiaCollection$new(query = myquery, dir.path = ".", check = TRUE) mycollection
where dir.path
is the path you want your tiles to be
further downloaded (This only queries Theia’s catalog for available
tiles, nothing is 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. Set check = FALSE
to skip file’s check.
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 the resulting .meta4
file to your disk.
You can then create your collection using this file:
<- TheiaCollection$new(cart.path = "path/to/cart/file.meta4",
mycollection dir.path = ".",
check = TRUE)
As above, it will check the hash of files if they are already present
in dir.path
.
You can access the tiles from your collection using:
mycollection$tiles
which returns a list
of tiles. You can also see the
status of your collection with:
$status mycollection
The next step is to download your collection. To download all tiles in a collection, simply run:
$download(auth = "path/to/auth/file.txt") mycollection
where path/to/auth/file.txt
is the path to a file
storing your Theia credentials. It is a simple text file with the
Theia’s account email on the first line and the account’s password on
the second line:
user@example.com MyTheiaPassword
If it does not exist yet, you will be securely prompted for your login and password, and the file will be created.
The download()
method 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:
$download(auth = "path/to/auth/file.txt", overwrite = TRUE) mycollection
You can then read bands directly from the zip archives (by using the
vsizip
interface provided by GDAL). Use:
$bands mytile
to get a list of available bands. Then:
<- mytile$read(bands = c("B5", "B6")) mybands
to load the bands into memory (returns a RasterStack
object). It performs the necessary corrections on the values.
You can also read bands from a collection by running:
<- mycollection$read(bands = c("B5", "B6")) mybands
which returns a list
of RasterStack
objects.
NOTE: Be careful when loading several tiles as it needs a lot of memory (~900MB/tile)
gdalcubes
collectionAlternatively, you can use the great gdalcubes package to create a three dimensional representation of the tiles. Simply run:
library(gdalcubes)
<- mycollection$as_gdalcube("path/to/gdalcubes.sqlite") gdalcubes
where path/to/gdalcubes.sqlite
is the path to store the
gdalcubes object data.
If you want to extract full archives, you can run:
<- mycollection$extract() file.path
which will extract tiles into the same directory as the archives.
This is not recommended, as this will take a large amount of disk space
Thanks to Olivier Hagolle for his work on
theia_download.py
(github),
which has inspired this package.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.