Remote sensing is an established technological solution for bridging critical gaps in volcanic hazard assessment and risk mitigation. The enormous amount of remote sensing data available today at a range of temporal and spatial resolutions can aid emergency management in volcanic crises by detecting and measuring high-temperature thermal anomalies and providing lava flow propagation forecasts. In such thermal estimates, an important role is played by emissivity—the efficiency with which a surface radiates its thermal energy at various wavelengths. Emissivity has a close relationship with land surface temperatures and radiant fluxes, and it impacts directly on the prediction of lava flow behavior, as mass flux estimates depend on measured radiant fluxes. Since emissivity is seldom measured and mostly assumed, we aimed to fill this gap in knowledge by carrying out a multi-stage experiment, combining laboratory-based Fourier transform infrared (FTIR) analyses, remote sensing data, and numerical modeling. We tested the capacity for reproducing emissivity from spaceborne observations using ASTER Global Emissivity Database (GED) while assessing the spatial heterogeneity of emissivity. Our laboratory-satellite emissivity values were used to establish a realistic land surface temperature from a high-resolution spaceborne payload (ETM+) to obtain an instant temperature–radiant flux and eruption rate results for the 2001 Mount Etna (Italy) eruption. Forward-modeling tests conducted on the 2001 ‘aa’ lava flow by means of the MAGFLOW Cellular Automata code produced differences of up to ~600 m in the simulated lava flow ‘distance-to-run’ for a range of emissivity values. Given the density and proximity of urban settlements on and around Mount Etna, these results may have significant implications for civil protection and urban planning applications.

We aim here to improve the understanding of the relationship between emissivity of the lava and temperature by carrying out a multi-stage experiment for the 2017 Mt Etna (Italy) eruption. We combine laboratory, spaceborne, and numerical modelling data, to quantify the emissivity–temperature relationship. Our laboratory-based Fourier-transform infrared (FTIR) results indicate that emissivity and temperature are inversely correlated, which supports the argument that emissivity of molten material is significantly lower than that of the same material in its solid state. Our forward-modelling tests using MAGFLOW Cellular Automata suggest that a 35% emissivity variation (0.95 to 0.60) can produce up to 46% overestimation (for constant emissivity 0.60) in simulated/forecasted lava flow lengths (compared to actual observed). In comparison, our simulation using a ‘two-component’ emissivity approach (i.e., different emissivity values for melt and cooled lava) and constant emissivity 0.95 compares well (≤10% overestimation) with the actual 2017 lava flow lengths. We evaluated the influence of variable emissivity on lava surface temperatures using spaceborne data by performing several parametrically controlled assessments, using both constant (‘uniform’) and a ‘two-component’ emissivity approach. Computed total radiant fluxes, using the same spaceborne scene (Landsat 8 Operational Land Imager (OLI)), differ ≤15% depending on emissivity endmembers (i.e., 0.95 and 0.60). These results further suggest that computed radiant flux using high-spatial resolution data is bordering at lower boundary (range) values of the moderate-to-high temporal resolution spaceborne data (i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and Spinning Enhanced Visible and Infrared Imager (SEVIRI)), acquired for the same target area (and the same time interval). These findings may have considerable impact on civil protection decisions made during volcanic crisis involving lava flows as they approach protected or populated areas. Nonetheless, the laboratory work, reported here, should be extended to include higher volcanic eruptive temperatures (up to 1350 K).

Spaceborne detection and measurements of high-temperature thermal anomalies enable monitoring and forecasts of lava flow propagation. The accuracy of such thermal estimates relies on the knowledge of input parameters, such as emissivity, which notably affects computation of temperature, radiant heat flux, and subsequent analyses (e.g., effusion rate and lava flow distance to run) that rely on the accuracy of observations. To address the deficit of field and laboratory-based emissivity data for inverse and forward modelling, we measured the emissivity of ‘a’a lava samples from the 2001 Mt. Etna eruption, over the wide range of temperatures (773 to 1373 K) and wavelengths (2.17 to 21.0 µm). The results show that emissivity is not only wavelength dependent, but it also increases non-linearly with cooling, revealing considerably lower values than those typically assumed for basalts. This new evidence showed the largest and smallest increase in average emissivity during cooling in the MIR and TIR regions (~30% and ~8% respectively), whereas the shorter wavelengths of the SWIR region showed a moderate increase (~15%). These results applied to spaceborne data confirm that the variable emissivity-derived radiant heat flux is greater than the constant emissivity assumption. For the differences between the radiant heat flux in the case of variable and constant emissivity, we found the median value is 0.06, whereas the 25th and the 75th percentiles are 0.014 and 0.161, respectively. This new evidence has significant impacts on the modelling of lava flow simulations, causing a dissimilarity between the two emissivity approaches of ~16% in the final area and ~7% in the maximum thickness. The multicomponent emissivity input provides means for ‘best practice’ scenario when accurate data required. The novel approach developed here can be used to test an improved version of existing multi-platform, multi-payload volcano monitoring systems.

Mapping volcanic flow deposits can be achieved by considering backscattering characteristics as a metric of surface roughness. In this study, we developed an approach to extract a measure of surface roughness from dual-band airborne Synthetic Aperture Radar (ASAR) backscattering data to characterize and map various volcanic flow deposits—namely, debris avalanches, lahars, lava flows, and pyroclastic density currents. We employed ASAR and Indian Space Research Organization (ISRO) airborne SAR datasets, from a joint project (ASAR-ISRO), acquired in December 2019 at 2 m spatial resolution, to assess the role and importance of incorporating dual-band data, i.e., L-band and S-band, into surface roughness models. Additionally, we derived and analyzed surface roughness from a digital surface model (DSM) generated from unoccupied aircraft systems (UAS) acquisitions using Structure from Motion (SfM) photogrammetry techniques. These UAS-derived surface roughness outputs served as meter-scale calibration products to validate the radar roughness data over targeted areas. Herein, we applied our method to a region in the United States over the Mount St. Helens volcano in the Cascade Range of Washington state. Our results showed that dual-band systems can be utilized to characterize different types of volcanic deposits and range of terrain roughness. Importantly, we found that a combination of radar wavelengths (i.e., 9 and 24 cm), in tandem with high-spatial-resolution backscatter measurements, yields improved surface roughness maps, compared to single-band, satellite-based approaches at coarser resolution. The L-band (24 cm) can effectively differentiate small, medium, and large-scale structures, namely, blocks/boulders from fine-grained lahar deposits and hummocks from debris avalanche deposits. Additionally, variation in the roughness estimates of lahar and debris avalanche deposits can be identified and quantified individually. In contrast, the S-band (9 cm) can distinguish different soil moisture conditions across variable terrain; for example, identify wet active channels. In principle, this dual-band approach can also be employed with time series of various other SAR data of higher coherence (such as satellite SAR), using different wavelengths and polarizations, encompassing a wider range of surface roughness, and ultimately enabling additional applications at other volcanoes worldwide and even beyond volcanology.

As volcanism may be considered synonymous with heat, the MODVOLC system utilizes thermal infrared satellite data from MODIS instruments to monitor the eruptive state of active volcanoes in near-real-time. This automatic hot-spot detection system is used here as the primary data source. We present a 25-year (2000–2024) record of MODVOLC lava discharge rates for Mount Etna in Sicily, Italy. Examples are given for four large flank eruptions occurring in 2001, 2002–2003, 2004–2005, and 2008–2009. Derived “lower” and “upper” erupted volume estimates for these eruptions range from $28-53\times {10}^6 {\mathrm{m}}^3$ to $57-104\times {10}^6 {\mathrm{m}}^3$ respectively. Such values correspond favorably to earlier estimates determined in the field or from other satellite data. Given the similarity of results, we then apply the same approach to the analysis of selected eruptions of five other basaltic volcanoes. Inversion of MODVOLC-derived time averaged discharge rates and volume data for Mount Etna eruptions in this study provides estimated magma chamber dimensions of ~2.2 to 2.6 km in radius for “lower” estimates (2.6 to 2.9 for “upper”), with an estimated total volume between ~45–74 ${\mathrm{k}\mathrm{m}}^3$ (“lower) and ~74–102 ${\mathrm{k}\mathrm{m}}^3$ (“upper”), which can inform plausible depth ranges at approximately 5 km when combined with petrologic/geodetic constraints.

The new dual-frequency radar satellite ASAR-ISRO provide simultaneously and for the first time a wide wavelength spectrum which is critical to discriminate surface roughness based on different backscattering characteristics. Here we use such dual L-band and S-band airborne SAR system to characterize and map various volcanic areas in the Northern Cascades through their backscattering properties. Mapping volcanic flows (lava flows, pyroclastic currents, lahars) is vastly improved by using backscattering as a metric of surface roughness. Various types of volcanic flow deposits and surface textures are distinguished by their roughness measured with radar systems. The ability of radar systems to distinguish volcanic flow textures, represented by roughness, is a key factor in understanding the processes and timescales of flow emplacement. For instance, transition from pahoehoe to aa lava flows is associated with change in flux and steepness of topographic gradient. Therefore, lava textures are essential data for calibrating and improving lava flow emplacement codes. Similarly, the textures of high velocity, and more deadly, pyroclastic currents and lahars change along their flow paths, also revealing critical data about the mechanisms of flow emplacement. As with lava flows, we use the ASAR-ISRO L+S SAR system to characterize the run-out distances of pyroclastic currents and lahars where large numbers of blocks accumulate in such deposits (places where flow momentum was lost, whether due to friction or break-in-slope and vast quantities of blocks accumulate in a relatively small area compared to the total area inundated by the flow). Mapping volcanic flow textures in a variety of volcanic terrains will provide clues about modes and rates of emplacement, and change in these through time, in a way that is simply unavailable by traditional geologic mapping. The next generation of volcanic flow maps, used for hazard assessment, will rely on radar data to delineate these textures.