The goal of rsat
is to help you handling time-series of
satellite images from multiple platforms in a local, efficient, and
standardized way. The package provides tools to;
vignette("rsat1_search", package = "rsat")
command)vignette("rsat2_download", package = "rsat")
command)vignette("rsat3_customize", package = "rsat")
command)vignette("rsat4_process", package = "rsat")
command)satellite images from Landsat, MODIS, and Sentinel for a region and time of interest.
You can install the development version from GitHub with:
install.packages(c('usethis', 'pkgdown', 'rcmdcheck', 'rversions', 'urlchecker'))
# check and install devtools
if(!require("devtools")){
install.packages("devtools")
}# check and install rmarkdown
if(!require("rmarkdown")){
install.packages("rmarkdown")
}
::install_github("spatialstatisticsupna/rsat", build_vignettes=TRUE) devtools
In Linux, you need to install additional libraries before starting
with rsat
. Use the following commands for:
sudo apt update
sudo apt install r-cran-rcpp gdal-bin libgdal-dev libproj-dev openssl libssl-dev xml2 libxml2-dev libmagick++-dev libfreetype6-dev libpng-dev libtiff5-dev libjpeg-dev libharfbuzz-dev libfribidi-dev
sudo dnf install gdal gdal-devel proj-devel xml2 libxml2-devel libcurl-devel openssl-devel ImageMagick-c++-devel R-devel udunits2-devel sqlite-devel geos-devel pandoc harfbuzz-devel fribidi-devel freetype-devel libpng-devel libtiff-devel libjpeg-devel
The registration in the following online portals is required to get a
full access to satellite images with rsat
; - USGS USGS is the sole
science agency for the Department of the Interior of United States.
Provide access to Modis Images. More information about USGS can be found
Here. - EarthData: A repository of
NASA’s earth observation data-sets. More information about EarthData can
be found here. - DataSpace, a web service
giving access to Copernicus’ scientific data hub. Please go here to find more details
about the data hub.
For convenience, try to use the same username and password for all of them. To satisfy the criteria of all web services make sure that the username is \(4\) characters long and includes a period, number or underscore. The password must be \(12\) character long and should include characters with at least one capital letter, and numbers.
This is a basic example which shows you how to compute the Normalized Difference Vegetation Index from a MODIS image captured on January 11th, 2020 in northern Spain (Navarre):
library(rsat)
# replace with your own "username" and "password"
set_credentials("username", "password")
# region and time of interest: rtoi
<- ex.navarre
roi <- as.Date("2020-01-11")
toi <- tempdir()
rtp
set_database(file.path(tempdir(), "DATABASE"))
<- new_rtoi("Navarre", roi, rtp)
navarre
# search, acquire, customize, and process
rsat_search(region = navarre, product = "mod09ga", dates = toi)
rsat_download(navarre)
rsat_mosaic(navarre, overwrite = TRUE)
rsat_derive(navarre,
product = "mod09ga",
variable = "NDVI")
# plot the results
plot(navarre, "view" ,
product = "mod09ga",
variable = "NDVI",
breaks = seq(0, 1, 0.1))
plot(navarre,"dates")
See the vignettes for more examples:
browseVignettes("rsat")
R has become an outstanding tool for remote sensing image analysis. There are several tools for the search and acquisition of satellite images, however, rsat is the first package that standardizes all the procedures in data acquisition to provide an unique workflow for any multispectral satellite.
Currently there are several packages dedicated to remote sensing topic, but they are usually ad-hoc packages for each satellite. Here is a list of some of the most popular R packages dedicated to satellite imagery:
The closest package to rsat
is RGISTools.
rsat
is the redefinition of the RGISTools package
reprogrammed from scrach in the object-oriented programming paradigm.
Many of the RGISTools code lines have been used to develop
rsat
, but these have been optimized and redundancies in the
code have been removed in order to facilitate its maintenance. In
addition, rsat
contains new features and R classes to make
it more user-friendly.
getSpatialData
is another package very similar to
rsat
. The package has the same philosophy of having a
single package for searching and downloading satellite images. However,
the development of rsat
goes a bit further and in addition
to search and download, the package helps you to organize all the
downloaded information in a structured database. rsat
allows you to use the metadata of the images to see the direct relation
with your region of interest before downloading it. Also all image
processing standardization is not developed in
getSpatialData
.
The last package dedicated to image downloading is
luna
.Searching and downloading images compared to rsat is a
bit more complicated. It is only able to search and download Modis and
Landsat images, and does not help you in organizing the image
products.
rLandsat
makes it easy to search for Landsat8 product
IDs, place an order on USGS-ESPA and download the data.
rsat
on the other hand is able to do the image search
without knowing all the ids, just using a polygon of the region of
interest, making the search process much easier.
getlandsat
provides access to Landsat 8 metadata and
images hosted on AWS S3 at. The package only data for the users, and
does not help in further use, as rsat does.
sen2r
is an R library which helps to download and
preprocess Sentinel-2 optical images. This is done through a GUI,
something that can be very interesting for users but limits the analysis
of the information prior to downloading, which can be done with
rsat
.
rsat
helps you to search, download and pre-process the
images, but once these procedures are done it allows you to extract all
the processed information into the most used raster classes in R
(raster
, stars
or spatRaster
).
The image processing packages can be used for further analysis in these
R classes.
We accept contributions to improve the package. Before contributing, please follow these steps:
citation("rsat")[1]
To cite the package:
U. Pérez-Goya, M. Montesino-SanMartin, A F Militino, M D Ugarte (2021). rsat: Dealing with Multiplatform Satellite Images from Landsat, MODIS, and Sentinel. R package version 0.1.16. https://github.com/ropensci/rsat.
This work has been financed by projects MTM2017-82553-R (AEI/FEDER, UE) and PID2020-113125RB-I00/MCIN/AEI/10.13039/501100011033.