## 1 Introduction  
Several studies have shown the relevant contribution of satellite systems for investigating and monitoring active volcanoes, also in areas where ground-based devices are fully operational (e.g., [1, 2, 3, 4]). Those systems are capable of providing information about changes of thermal volcanic activity leading to eruptions and of estimating the radiant flux and the mass eruption rate (e.g., [5, 6]). Moreover, they enable the identification of thermal anomalies associated with hot degassing. This aspect is particularly relevant, considering that short-term variations of non-eruptive thermal fluxes are essential for volcano monitoring (e.g., [7]).  
Among the systems developed to monitor active volcanoes from space, MODVOLC exploits MODIS (Moderate Resolution Imaging Spectroradiometer), MIR (Medium Infrared) and TIR (Thermal Infrared) data, at 1 km spatial resolution, to detect and quantify high-temperature features such as lava flows. MODVOLC provides information about thermal anomalies in terms of hotspot pixel number, total MIR radiance and radiant flux, in both nighttime and daytime conditions [8, 9].  
MIROVA [3] is another well-established MODIS-based system, performing over more than 300 active volcanoes [10]. This system shows a good efficiency in also detecting subtle hotspots (e.g., [3]). On the other hand, the lack of sensitivity of MODVOLC to low-level thermal anomalies, ascribable to the use of a fixed threshold test used globally, was demonstrated in several previous studies, also through comparison with MODLEN [11] and RST (Robust Satellite Techniques) (e.g., [12; 13]). The latter is a multi-temporal scheme of satellite data analysis, which was used with success to study and monitor several active volcanoes located in different geographic areas, using high temporal resolution satellite data, from sensors such as AVHRR (Advanced Very High Resolution Radiometer), MODIS and SEVIRI (Spinning Enhanced Visible and Infrared Imager) (e.g., [14; 15]), offering an extended dataset of multi-year satellite observations. The algorithm has also shown a high potential in detecting subtle thermal activities, which may precede volcanic eruptions (e.g., [2; 4; 16]).  
In this work, we assess the RST potential in detecting and mapping volcanic thermal anomalies by satellite through ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) TIR data, at 90 m spatial resolution. ASTER was largely used in volcanology, despite the nominal revisit time of 16 days, thanks to its features in terms of spectral and spatial resolution (e.g., [17; 18] and reference herein). Here, we show the results of the preliminary RST implementation on ASTER data, performed under the Google Earth Engine (GEE) environment. GEE is a cloud-based platform providing access to thousands of satellite images (e.g., European Space Agency-Sentinel, United States Geological Survey-Landsat), and enabling their handling and analysis at planetary scale (see [19] for more details). The high computational resources of GEE were previously exploited to develop an freely accessible tool devoted to map volcanic thermal anomalies at global scale ([[https://sites.google.com/view/nhi-tool](https://sites.google.com/view/nhi-tool)]([https://sites.google.com/view/nhi-tool](https://sites.google.com/view/nhi-tool))), using MSI (Multispectral Instrument) and OLI (Operational Land Imager) SWIR (shortwave infrared) data at 20/30 m spatial resolution [20; 21]. Here, we evaluate the contribution of an RST-based system analyzing ASTER TIR data, named RASTer (Robust ASTER Thermal anomaly system), in supporting the operational monitoring of active volcanoes from space, particularly for subtle hotspots identification. Mt. Etna (Italy), Shishaldin (AK, USA) and Shinmoedake (Japan) thermal activities are analyzed in this study by comparing RASTer detections to those from the largely accepted AVA (Aster Volcano Archive) database.