Welcome to the polsartools Example Notebooks repository! This repo contains a collection of Jupyter notebooks showcasing various features and usage of the polsartools package.

These notebooks serve as hands-on tutorials and demonstrate how to use the core functionalities of Polsartools with various SAR sensors.

This repository includes a set of example notebooks that you can run to explore and learn how to use polsartools. These notebooks cover a variety of use cases and will help you get up to speed with the package quickly.

To run the notebooks in this repository, follow these steps:

Installing gdal via pip may fail. Therefore, we recommend using conda to install it:

conda install gdal -c conda-forge

Before running the notebooks, you'll need to install the core polsartools package.

Option A: Install from PyPI pip (stable release)

pip install polsartools

Option B: Install from conda (stable release)

conda install polsartools -c bnarayanarao

Option C: Install the latest version from GitHub (if you need recent updates or fixes)

pip install git+https://github.com/Narayana-Rao/polsartools.git#egg=polsartools

Note: If you encounter a "module not found" error or require newer features, prefer the GitHub installation.

After successfully installing polsartools, you can verify it by importing the package:

import polsartools as pst

If this runs without errors, you're ready to explore and run the notebooks.

If you use polsartools in your research or projects, please cite the official journal paper:

Bhogapurapu, N., Siqueira, P., & Bhattacharya, A. 2026. polsartools: A Cloud-Native Python Library for Processing Open Polarimetric SAR Data at Scale. SoftwareX, 33, 102490. doi: 10.1016/j.softx.2025.102490

@article{bhogapurapu2025polsartools,
title = {Polsartools: A cloud-native python library for processing open polarimetric SAR data at scale},
author = {Narayanarao Bhogapurapu and Paul Siqueira and Avik Bhattacharya},journal = {SoftwareX},
volume = {33},
pages = {102490},
year = {2026},
publisher={Elsevier},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2025.102490},
}