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sits: Satellite Image Time Series Analysis on Earth Observation Data Cubes

Setup

How to use this on-line book

This book contains reproducible code that can be run on an R environment. There are three options to setup your working environment:

  1. Install R and RStudio and the packages required by sits, with specific procedures for each type of operating systems.
  2. Use a Docker image provided by the Brazil Data Cube.
  3. Install sits and all its dependencies using conda.

How to install sits using R and RStudio

We suggest a staged installation, as follows:

  1. Get and install base R from CRAN.
  2. Install RStudio from the Posit website.

Installing sits from CRAN

The Comprehensive R Archive Network (CRAN), a network of servers (also known as mirrors) from around the world that store up-to-date versions of basic code and packages for R. In what follows, we describe how to use CRAN to sits on Windows, Linux and MacOS.

Installing in Microsoft Windows and MacOS environments

Windows and MacOS users are strongly encouraged to install binary packages from CRAN. The sits package relies on the sf and terra packages, which require the GDAL and PROJ libraries. Run RStudio and install binary packages sf and terra, in this order:

After installing the binaries for sf and terra, install sits as follows;

install.packages("sits", dependencies = TRUE)

To run the examples in the book, please also install sitsdata package, which is available from GitHub. It is necessary to use package devtools to install sitsdata.

install.packages("devtools")
devtools::install_github("e-sensing/sitsdata")

To install sits from source, please install Rtools for Windows to have access to the compiling environment. For Mac, please follow the instructions available here.

Installing in Ubuntu environments

For Ubuntu, the first step should be to install the latest version of the GDAL, GEOS, and PROJ4 libraries and binaries. To do so, use the repository ubuntugis-unstable, which should be done as follows:

sudo add-apt-repository ppa:ubuntugis/ubuntugis-unstable
sudo apt-get update
sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev 
sudo apt-get install gdal-bin
sudo apt-get install proj-bin

Getting an error while adding this PPA repository could be due to the absence of the package software-properties-common. After installing GDAL, GEOS, and PROJ4, please install packages sf and terra:

Then please proceed to install sits, which can be installed as a regular R package.

install.packages("sits", dependencies = TRUE)

Installing in Debian environments

For Debian, use the rocker geospatial dockerfiles.

Installing in Fedora environments

In the case of Fedora, the following command installs all required dependencies:

sudo dnf install gdal-devel proj-devel geos-devel sqlite-devel udunits2-devel

Using Docker images

If you are familiar with Docker, there are images for sits available with RStudio or Jupyter notebook. Such images are provided by the Brazil Data Cube team:

On a Windows or Mac platform, install Docker and then obtain one of the two images listed above from the Brazil Data Cube. Both images contain the full sits running environment. When GDAL is running in docker containers, please add the security flag --security-opt seccomp=unconfined on start.

Install sits from CONDA

Conda is an open-source, cross-platform package manager. It is a convenient way to installl Python and R packages. To use conda, first download the software from the CONDA website. After installation, use conda to install sits from the terminal as follows:

# add conda-forge to the download channels 
conda config --add channels conda-forge
conda config --set channel_priority strict
# install sits using conda
conda install conda-forge::r-sits

The conda installer will download all packages and libraries required to run sits. This is the easiest way to install sits on Windows.

Accessing the development version

The source code repository of sits is on GitHub. There are two versions available on GitHub: master and dev. The master contains the current stable version, which is either the same code available in CRAN or a minor update with bug fixes. To install the master version, install devtools (if not already available) and do as follows:

install.packages("devtools")
devtools::install_github("e-sensing/sits", dependencies = TRUE)

To install the dev (development) version, which contains the latest updates but might be unstable, install devtools (if not already available), and then install sits as follows:

install.packages("devtools")
devtools::install_github("e-sensing/sits@dev", dependencies = TRUE)

Additional requirements

To run the examples in the book, please also install the sitsdata package. We recommend installing it using wget. See instructions in the GNU Wget site.

options(download.file.method = "wget")
devtools::install_github("e-sensing/sitsdata")

Using GPUs with sits

The torch package automatically recognizes if a GPU is available on the machine and uses it for training and classification. There is a significant performance gain when GPUs are used instead of CPUs for deep learning models. There is no need for specific adjustments to torch scripts. To use GPUs, torch requires version 11.6 of the CUDA library, which is available for Ubuntu 18.04 and 20.04. Please follow the detailed instructions for setting up torch available here.