## 1 Introduction  
Among natural hazards, floods are currently the most frequent and costliest [1], causing worldwide fatalities as well as huge economic damage, affecting both rural and urban environments [2]. For instance, in 2017, 47% of the economic losses due to natural catastrophes were specifically related to floods (including both river flooding and flash floods) and another 35% to meteorological (i.e., storms) events [3]. Moreover, flood risk and the associated losses are projected to significantly increase in the future due to both human activities (i.e., land use/cover changes, new infrastructures construction, etc.) and natural causes (i.e., the effects of climate change, subsidence, etc.) [2,4,5]. To reduce the effects of these potential threats, effective flood risk management is required [2] as well as, in case of disaster, a prompt detection of flooded areas in order to support decision makers with relief and rescue operations [6]. In this framework, satellite remote sensing data have become a powerful tool, thanks to the growing availability of several satellite/sensors systems able to provide different information about inland surface water presence useful to manage flooding events [7,8]. Microwave sensors can provide useful evidence (i.e., 24 hours and under cloudy conditions) about flooded areas, with different characteristics depending on the specific technology used [9]. Active systems, such as Synthetic Aperture Radar (SAR), can furnish data at a high spatial resolution (up to few meters) but, generally, with a long revisit period (up to five to six days), hence often resulting not suitable for assuring a quick identification and a continuous monitoring of flood-inundated area [10,11]. Their capabilities greatly improve when national space agencies focus the acquisitions of their satellites on the affected area or when specific services, such as the International Charter Space and Major Disasters [12] or the Copernicus Emergency Management [13] are activated. On the other hand, passive microwave sensors allow acquiring data with a poor spatial resolution (up to tens of kilometres) but with a high temporal frequency (up to few hours), especially if considering those instruments on board of polar weather satellites constellation [14]. Their spatial and temporal resolution makes these sensors particularly suitable for studying large-scale floods [6] but less adequate in case of moderate/small size events. Optical sensors, acquiring data in the visible (VIS), near infrared (NIR) and shortwave infrared (SWIR) bands, allow for the detection of flooded areas during daytime and in absence of clouds [7,10]. The spatial resolution of these data ranges from few to hundreds of meters while the temporal resolution from some hours to a few days [10,15,16,17]. Therefore, in order to ensure continuous and near real time information in daytime conditions about flood dynamics, optical sensors onboard weather polar satellites represent one of the most suitable solution in furnishing useful data, in terms of both spatial, spectral and temporal resolutions [18]. Furthermore, considering that both optical and microwave sensors are often present on these satellites, their integration is an added value in providing a more comprehensive overview of the ongoing phenomena [6,18,19,20]. In the last years, optical data acquired by the Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) have been analysed by implementing the Robust Satellite Technique (RST) [21] for detecting flooded areas and therefore christened RST-FLOOD, with satisfactory results [22,23]. In this paper, RST-FLOOD has been applied to Suomi National Polar-orbiting Partnership (Suomi-NPP) (SNPP) Visible Infrared Imaging Radiometer Suite (VIIRS) imagery to analyse the flooding event which hit the Basilicata and Puglia regions (southern Italy) in the first week of December 2013.