Conference Agenda

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The NASA-ISRO Synthetic Aperture Radar (NISAR) Mission launched successfully on July 30, 2025, and will begin distributing science data at the end of its commissioning phase, ramping up to full science operations – collecting all land and ice-covered surfaces every 12 days from ascending and descending orbit vantage points. These data will be freely and openly distributed from the NASA Alaska Satellite Facility within days of acquisition. NISAR observations are capable of addressing fundamental and applied research topics spanning disciplines that include ecosystems science, cryosphere science, geodesy, solid earth science, hydrology, disaster response, and resource management. This talk will provide an overview of the mission, including its science and technology innovation, and dive into its status with focus on data and uniqueness of this first-of-its-kind L and S band mission. Particular emphasis will be placed on NISAR’s contributions to the polarimetric and polarimetric-interferometric SAR community, with examples from early science demonstrations that showcase initial research applications.

The Advanced Land Observing Satellite-4 (ALOS-4) was launched by the Japan Aerospace Exploration Agency (JAXA) on July 1, 2024. ALOS-4 carries the Phased Array L-band Synthetic Aperture Radar-3 (PALSAR-3) instrument, extending Japan’s more than 30-year heritage of L-band SAR missions that began with JERS-1 SAR, followed by ALOS PALSAR and ALOS-2 PALSAR-2.

Similar to ALOS-2, ALOS-4 operates in a 12 a.m./p.m. sun-synchronous orbit with a 14-day repeat cycle. A major advancement of PALSAR-3 over its predecessors is its enhanced wide-swath polarimetric capability, which enables quad-polarisation observations across a 100 km swath. This improvement allows for regional, gap-free coverage within only two observation cycles—compared to five cycles required by PALSAR-2.

Under the ALOS-4 Basic Observation Scenario, global quad-polarisation coverage is planned on an annual basis, with higher-frequency fully polarimetric acquisitions over selected regional and local target areas. The Earth Observation Research Center (EORC) of JAXA oversees research coordination, application development, and the generation of research datasets for both ALOS-2 and ALOS-4 missions. Amongst others, EORC coordinates the ALOS Kyoto & Carbon Initiative, which comprises a dedicated activity for polarimetric research using ALOS-2 and ALOS-4.

Through this presentation, we provide an overview of the ALOS-4 PALSAR-3 mission, with emphasis on its polarimetric capabilities, including the plans for polarimetric dataset generation and distribution by JAXA EORC.

We also touch upon the potential role of ALOS-4 in the era of other current and near-future L-band SAR missions, such as NISAR and ROSE-L, and how these missions can complement each other through cross-agency mission coordination.

This contribution presents an ongoing effort to modernize selected components of the PolSARpro toolbox by re-implementing its core algorithms in Python. The work follows recommendations from PolInSAR 2021 and aims to provide a more accessible environment for both research and education while preserving numerical consistency with the original C implementation. The overarching goal is to offer a clean and sustainable foundation for future algorithmic development, teaching, and reproducible experimentation.

Python was chosen as the new language for the PolSARPro routines because it is strongly adopted in the remote sensing and open-source communities The new design relies on Xarray with a Dask backend to overcome two major limitations of NumPy: the absence of metadata and the lack of native parallel execution. This framework enables explicit polarimetric data structures (S, C3, T3, T4 matrices, etc.) whose elements are accessed through intuitive labels such as S.vh or C3.m11. Lazy evaluation plays a central role by delaying actual computations until explicitly requested, which helps limit memory pressure, allows the construction of complex workflows without allocating intermediate arrays, and provides opportunities for Dask to fuse tasks and optimize execution. Combined with Dask’s automatic blockwise scheduling, this setup enables parallel processing without writing explicit tiled or multithreaded code.

Input data adhere to the NetCDF-BEAM format used in SNAP. A dedicated loader interprets the structural metadata and constructs a PolSARpro-compatible dataset, automatically identifying the polarimetric type. If the source dataset has been processed with Range–Doppler terrain correction in SNAP, geolocation information is preserved throughout the workflow, allowing decomposition outputs to be exported as GeoTIFFs and viewed directly in GIS software.

The software is fully open-source under the Apache-2.0 license and hosted on GitHub, with extensive documentation on Read the Docs. The site includes installation instructions, reproducible tutorials linked to executable notebooks, an API reference, and a concise theory section. The package is distributed through conda, and availability on conda-forge is planned to simplify deployment and enable integration into ESA’s MAAP platform. A small ALOS-1 dataset over San Francisco will be released to support hands-on practice.

The current release provides Boxcar and Refined Lee filters, H/A/Alpha, Freeman decompositions, the Yamaguchi three- and four-component decompositions as well as the PWF (Polarimetric Whitening Filter). Additional decompositions, classification tools, and further polarimetric modules are planned. Systematic validation tests ensure continued numerical alignment with the original PolSARpro algorithms.

Although Polarimetric SAR (PolSAR), Polarimetric Interferometric SAR (Pol-InSAR), and multi-frequency SAR systems hold significant scientific and operational potential, their research and application remain relatively underdeveloped. This limitation is to a large extent attributable to the scarcity of consistent, long-term time series of polarimetric data for research and development, as well as the limited availability of (near-)coincident, multi-sensor, multi-frequency datasets required for interoperability studies.

The potential coordinating role of the Committee on Earth Observation Satellites (CEOS)—serving as a conduit between the SAR research community and space agencies operating SAR missions—was highlighted during the ESA PolInSAR Workshop held in Toulouse, France, in June 2023. Following subsequent discussions between the ESA PolInSAR representatives and the CEOS Land Surface Imaging Virtual Constellation (LSI-VC), a dedicated LSI-VC PolSAR activity was initiated in 2024.

The LSI-VC PolSAR activity aims to facilitate coordination among relevant space agencies operating SAR missions with polarimetric capabilities, promoting the systematic acquisition of polarimetric and multi-frequency SAR observations over a defined set of CEOS PolSAR reference sites. Data tasking and acquisitions are conducted on a best-effort basis.

A PolSAR Science Team has been formed, and approximately 25 global reference sites have been identified to represent diverse ecosystems and land cover types. Ten CEOS member agencies have been engaged, with the potential to contribute polarimetric SAR data across all operational radar frequency bands available from space—P, L, S, C, and X. Data acquisitions began in late 2025 and are scheduled to continue through 2026.

Collaboration with the CEOS System Engineering Office (SEO) additionally provides the PolSAR Science Team access to a cloud-based environment for SAR and PolSAR data analysis via the CEOS Analytics Lab (CAL). The CAL platform has been extended to include a suite of SAR analytical tools and software packages, including SNAP and PolSARpro.

In the longer term, and subject to the data policies of the individual SAR missions, the compiled datasets are foreseen to be made available to a wider scientific community engaged in polarimetric and tomographic SAR research. This initiative aims to advance the development of polarimetric and multi-frequency SAR science and applications and to lower the entry bar for new user groups.