Developing PyCam: Software for acquiring and processing volcanic UV SO2 camera data

Monitoring of sulphur dioxide (SO2) emission rates in volcanic plumes provides valuable insights into the state of a volcanic system, aiding eruption forecasting efforts for many volcanoes worldwide. SO2 cameras exploit the strong absorption signature of SO2 at ultraviolet (UV) wavelengths to measure emission rates with UV-sensitive cameras. However, this approach has been limited by the cost of traditional scientific-grade equipment. In 2016 a group from The University of Sheffield developed PiCam UV, an imaging system based on a low-cost modified visible imaging detector that produces comparable data to traditional equipment at a fraction of the cost.

Whilst previous work has developed open-source libraries for processing SO2 camera data, the software has been complex and incredibly difficult for end users to utilise. Development of the PyCam software began in mid-2019 to provide a user-friendly, graphical interface for interacting with PiCam systems, i.e. remotely adjusting settings and on- and off-line processing of collected data. RSE involvement began in early 2023 and will continue until at least 2025, with the aim of improving the quality, sustainability and usability of the software going forward. This is of particular importance to this project since the end users may not be experts in remote sensing or programming, but need to generate reliable SO2 emission rates to combine with other strands of volcano monitoring data (e.g. seismics).

Here, we give a brief overview of the PiCam hardware and PyCam software, describe the work already completed to improve PyCam, and outline the future work planned.