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A tutorial package for Synthetic Aperture Radar Tomography

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Documentation Status PyPI version

EO-College tomography tutorial

This tutorial, developed by the EO-College learning initiative, explores Synthetic Aperture Radar (SAR) tomography with data from DLR's F-SAR system. It consists of a Python package, containing several functions for processing and displaying the data, a Jupyter notebook, a test data set, which can be downloaded here, and a video tutorial.
Please follow the steps below to get started.


The following subsections describe the installation process for different operating systems. Please mind that this tutorial depends on Python 3.


First we want to install GDAL to read our data. For this we add the UbuntuGIS package repository so we can install a more recent version than that supplied by Ubuntu. After this we install GDAL together with its Python bindings:

sudo add-apt-repository ppa:ubuntugis/ppa
sudo apt-get update
sudo apt-get install gdal-bin python3-gdal

Next we install Tkinter for graphical support:

sudo apt-get install python3-tk

As a last step we install the tomography module including its direct Python package dependencies:

sudo python3 -m pip install tomography_tutorial


The easiest way to install Python and Jupyter on Windows is via Anaconda. Please make sure to install the Python 3 version.
Once you have installed it, please add its installation directory to the PATH environment variable. See e.g. here for instructions. Now we can install GDAL via Anaconda's own command line installation program:

conda install -c conda gdal

Finally we can install the tutorial package:

python -m pip install tomography_tutorial

download of tutorial test data

Prior to starting the tutorial you need to download and unpack the data found here.

Starting the notebook

Now that everything is installed you can start the notebook via the tutorial Python module. In the command prompt, start Python and execute the function start:

from tomography_tutorial import start

This will create a custom copy of the notebook if it does not yet exist and start it in the browser. If the directory in which the custom notebook is to be stored does not yet exist, it is created automatically. Please mind that under Windows paths need to be separated with \\ or /, a single backslash will cause an error.
You now have a custom version of the tutorial, which you can modify as you like and restart later via function start.
If you want to restore the original notebook, which was delivered with the Python package, just delete your custom version and run function start again.

API documentation

The documentation of the package functionality which is used in the notebook can be found here.

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