Polsartools: A cloud-native python library for processing open polarimetric SAR data at scale

The current generation of Synthetic Aperture Radar (SAR) satellite missions, such as NASA-ISRO SAR (NISAR), ISRO's EOS-04, ESA's BIOMASS, and Sentinel-1, is starting to deliver petabytes of data annually. This volume of open-access SAR data opens up new opportunities for research and applications, but also presents significant software challenges. Traditional tools for working with polarimetric SAR (PolSAR) data are primarily GUI-based, difficult to scale, and unsuited for cloud-native workflows. To address these issues, we introduce polsartools, an open-source Python library designed for scalable and reproducible processing and analysis of PolSAR data. This library is intended for researchers and academicians by supporting a variety of sensors and polarimetric modes. In addition to enabling cloud-native workflows through seamless integration with Jupyter-based platforms and cloud-optimized output formats, polsartools is also designed as a readable and modular reference implementation to support education, community adoption, and extensibility in polarimetric SAR processing. This article outlines the architecture, functionality, and design decisions behind polsartools, and offers insight into building modern, domain-specific scientific software that meets the demands of big data and open science.