Downloading implies acquiring and saving the list of
satellite images in a records
on your machine. This demo
builds on the showcase from the search vignette and so, the first
section reviews the most important code from the previous vignette. The
second section explains how to obtain satellite images with
rsat
. The last section mentions how rtoi
s are
designed to favor collaborative efforts to save downloading time.
As a first step of rsat
’s workflow is specifying the
credentials for the the web services:
The showcase aims at assessing the effect of the Snowstorm
Filomena on the Iberian peninsula during January 10th and 15th, 2021. Hence, the roi and
toi correspond to an sf
polygon around the
peninsula (ip
) and a vector of dates (toi
)
covering the time-span:
ip <- st_sf(st_as_sfc(st_bbox(c(
xmin = -9.755859,
xmax = 4.746094,
ymin = 35.91557,
ymax = 44.02201
), crs = 4326)))
toi <- seq(as.Date("2021-01-10"),as.Date("2021-01-15"),1)
The folders for the database and dataset can be created programmatically as follows:
db.path <- file.path(tempdir(),"database")
ds.path <- file.path(tempdir(),"datasets")
dir.create(db.path)
dir.create(ds.path)
The minimum information to generate a new rtoi
is the
name
, a polygon of the roi, and the paths to
database and dataset:
To limit the amount of data and processing times, the assessment is conducted over MODIS imagery. A total number of 24 images are found for the region over the 6-day period:
Downloading is straightforward with the function
rsat_download()
. The simplest way to use this function is
passing the rtoi
as an input. Depending on the speed of the
internet connection, the following instruction may take from few to
several minutes to run:
The function saves the satellite images automatically in the
database. The path to the database is provided by the
rtoi
:
Another way to download images is using a records
. This
variant requires defining a path for saving the resulting files
(out.dir
). The next line is equivalent to the
rtoi
version but using its records
class
object:
This second time, the message reveals that the function reads the
database first and checks which images in the rtoi
are
already available in the destination path. If it is available, the
function skips its download. This feature becomes handy when teams share
a common database.
rtoi
sThe rtoi
leverages the collective use of the package by
different working groups within the same or different institutions.
Teams working on separate studies or rtoi
s can refer to the
same database increasing its size over time. The database can
progressively turn into a local repository. Eventually, new
rtoi
s may find the requested information in the local
database, skipping their download, and saving processing time. We
encourage rsat
users to develop common databases when
possible on shared machines.
The following vignette explains how to customize the satellite images to turn raw data into valuable information for the aim of the analysis.