Azayaka is a project that provides free tools for processing Synthetic Aperture Radar (SAR) data.
The main goals of the Azayaka members are learning and personal interest.
In addition, formulas and diagrams are stored together with the project.
The Azayaka project provides two components.
Python libraryQGIS plugin
The Python implementation includes the core processing and formulas for SAR/InSAR.
You can download and install it via the Python package manager PyPI.
On QGIS, it provides a UI that passes processing to the Python library. This allows you to go from SAR/InSAR processing to visualization through operations in the QGIS interface.
It can also be searched, downloaded, and installed from the QGIS Plugin Manager.
You can install it in one of the following two ways.
Automatic installation from PyPI (recommended)
pip install azayakaBuild from source code
git clone azayaka
cd azayaka
pip install -r requirements.txt
pip install -e .Set up the environment for the plugin.
In the QGIS plugin search screen, search for QGIS Pip Manager and click Install.
In the search section, select azayaka and click Install/Upgrade.
(If you are familiar with the QGIS Python path, you can also install it directly with pip.)
In the QGIS plugin search screen, search for azayaka and click Install.
- Python 3.9 or later
- The Python library has been lightly tested with Python 3.9 to 3.12.
- The QGIS plugin has been confirmed on Windows 11 and macOS 14.3.
A tutorial notebook is available on Colab.
Note: the free CPU runtime does not have enough memory, so select a TPU or high-memory runtime.
- In QGIS, select "Plugins" → "Azayaka Plugin" from the menu.
- In the dialog, select the processing tab you want to run (InSAR or Geocoding).
- Set the required input parameters and click the OK button.
- When processing is complete, the results are saved in the specified output directory.
© JAXA © OpenStreetMap
Coming soon
Materials for formulas and figures (PDF)
Only the Japanese version is currently available. The English version will be published soon.
For the processing details and basics, the following book is used as a reference.
https://github.com/syu-tan/sar-python-book
