by David Stone , Head of Communications

May 7, 2024

Permian Global has released its in-house developed software for processing satellite imagery as open-source. The release is intended to help others working in remote sensing to analyse biomass and land-use imagery. The plan is also to grow a community of programmers who can help refine and improve the usefulness of the code.

The software package, named rsi, is designed for the R programming language. It helps users download and process satellite imagery from, for example, the Landsat and Sentinel missions. It also enables the extraction of many vital metrics from these different data sources including spectral and radar indices.

As a conservation project developer, it is important for Permian Global to derive accurate insights for the forest areas it is working on. This includes reliable analysis of landcover change and biomass stocks. Spatial and, more specifically, remote sensing data plays a pivotal role in this process, alongside fieldwork and forest plot measurements.

Working with remote sensing imagery comes with many challenges including data access, image pre-processing and the calculation of derived metrics. rsi helps to streamline these data processing workflows. rsi was developed by Mike Mahoney during an internship with the Permian Global technical team.

Dr. Hugh Graham, Remote Sensing Analyst, Permian Global, said: “With an ever-increasing amount of satellite data being made available and open, there is a need to increase the efficiency with which we process these data. rsi provides a high-level coding interface to be able to streamline our data analysis pipelines, in turn increasing the reliability and scalability of our projects. The development of robust and dependable software is crucial to our work in the Permian technical team and really excited to continue developing rsi and other open software in support of our goals to generate high-integrity projects based on strong scientific research.”

“The decision to make rsi open-source was two-fold. First, greater access to high quality remote sensing data is essential for tackling systemic challenges like deforestation and climate change. This software can support others in their work.

“Second, open-source software is proven to generate more rapid improvement and progress; we hope to build a community around rsi, who may contribute through bug reporting, improving documentation, and submitting improvements and new features. By working with a wider community on these data challenges, we can all benefit and make progress on our shared goals!”


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