I am a PhD Research Student in the School of Environment, Earth and Ecosystem Sciences, working on a Satellite-based volcano monitoring project. Focus of my research is on Mt Etna in Sicily, Italy, a persistently active volcano, surrounded by almost one million people. Prior to starting my PhD post in 2016, I completed B.Sc. (Hons) in Geosciences (OU 2014) and M.Sc. in Geophysical Hazards (UCL 2015).
PROJECT OVERVIEW: Satellite data interpretation relies on certain assumptions and input parameters, some of which, such as emissivity, are not well quantified for molten materials. Emissivity has a very close relationship with temperature. Therefore, the computation of surface temperature from spaceborne data and models that rely on these temperatures to track cooling with time can produce variation in lava flow distance-to-run estimates.
My laboratory-based results, using FTIR spectroscopy approach, indicate that emissivity is temperature dependent, as measured emissivity decreases with temperature increase. The current spaceborne and modelling applications neglect the link between emissivity and range of temperatures involved in an active lava flow (~1350 K on Mt Etna), so my Dynamic Emissivity-Temperature Rule produced in this project will serve to improve accuracy of lava surface temperature derivation and operational lava flow forecasts.
Satellite based Automated Volcano Monitoring
Less than 10% of the ∼1500 active subaerial volcanoes around the world are monitored with appropriate quality, frequency and timeliness.
A combination of passive and active remote sensing is accepted to be a technological solution for bridging critical gaps in volcanic hazard assessment and risk mitigation. Whereas many examples of satellite borne volcano monitoring are known since the early Eighties, we note that the exceptionally large literature available on optical remote sensing of very-high temperature features lacks in detailed information on some key-parameters as, in particular, spectral emissivity and its behaviour at high-to-very high temperature.
What is Spectral Emissivity – defined as the efficiency with which a surface radiates its thermal energy – spectral emissivity is seldom measured and mostly assumed or estimated. Nonetheless, it is a critical variable in spaceborne volcano monitoring due to its close relationship with Land Surface Temperature (LST) values, and the inherent impact on the estimate of mass eruption rates.
To fill this gap in knowledge, we designed a multi-stage experiment to measure spectral emissivity of rock samples collected in a grid, scaled to the spatial resolution of High-Resolution multispectral payloads provided with Thermal InfraRed channels – in particular, Terra’s ASTER and Landsat 8’s TIRS - from which spectral emissivity can be derived.
The aim of this approach is (i) to estimate the lateral spatial heterogeneity of spectral emissivity on ground at known volcanic targets, (ii) to assess the capacity of reproducing it from spaceborne observations at the scale of a satellite image/pixel, and (iii) to develop a method for incorporating the experimental laws into the techniques of automated eruption detection and quantitative monitoring. The suite of lava flow samples from Mount Etna, Italy (1999 to 2017) were investigated using laboratory-based Fourier Transform Infra-Red (FTIR) spectroscopy at 0.4 to 14.5 μm wavelength range and moderate-to-high temperatures (400 K to 1000 K).
To develop a general method of spectral emissivity valuation, the initial investigation assesses the correlation of laboratory measured data with (i) petrological composition, (ii) sample properties and (iii) high resolution RS data of the same target. Measured emissivity results are further used in remote sensing applications to constrain very high-temperature thermal anomalies (i.e. active lava flows with integrated pixel temperatures - close to or above 1000 K) and in melt mass flux investigations.
Spaceborne EO and a Combination of Inverse and Forward Modelling for Monitoring Lava Flow Advance (2019-12)
Rogic, Nikola; Cappello, Annalisa; Ganci, Gaetana; Maturilli, Alessandro; Rymer, Hazel; Blake, Stephen and Ferrucci, Fabrizio
Remote Sensing, 11, Article 3032(24)
Role of Emissivity in Lava Flow ‘Distance-to-Run’ Estimates from Satellite-Based Volcano Monitoring (2019-03-19)
Rogic, Nikola; Cappello, Annalisa and Ferrucci, Fabrizio
Remote Sensing, 11, Article 662(6)