Towards global volcano monitoring using Sentinel-1 data and the LiCSAlert algorithm

Abstract:

The Earth’s subaerial volcanoes pose a variety of threats, yet the vast majority remain unmonitored. However, with the advent of the latest synthetic aperture radar (SAR) satellites, interferometric SAR has evolved into a tool that can be used to monitor the majority of these volcanoes. Whilst challenges such as the automatic and timely creation of interferograms have been addressed, further developments are required to construct a comprehensive monitoring algorithm that is able to automate the interpretation of these data.

We present a new algorithm named LiCSAlert, which builds on the results of the Looking inside the Continents from Space (LiCS) grant to monitor ~10 volcanoes using Sentinel-1 data. Automatic creation of interferograms is performed by LiCSAR, and time series are formed using LiCSBAS, before the LiCSAlert algorithm endeavours to determine the latent signals present in a baseline time series. Changes in either the spatial or temporal nature of these signals are then used to determine if a volcano has entered a period of unrest.

Of particular importance for volcano monitoring using InSAR is the ability to differentiate between signals caused by changes in the atmosphere, and those caused by deformation. Our algorithm is designed to mitigate this through characterising the atmospheric signals observed in the baseline data, and we present results of a comparison between the application of our algorithm to raw interferograms, and to interferograms corrected using the results of weather models.

The LiCSAlert algorithm also contains a deep learning module which is able to differentiate between spatial signals within the baseline data that are caused by deformation, and those caused by changes in the atmosphere. We present the results of using this module at volcanoes which feature steady state deformation, and show that it can be used to detect latent deformation signals that are of particular importance for volcano monitoring.