## 1 Introduction  
Among natural disasters, floods are more easily investigable using satellite data. In 2016, among the 36 activations of the International Charter \"Space & Major Disasters\", 17 (i.e., 44%) of them were related to floods [1], demonstrating the effectiveness of the information that satellite remote sensing can provide in this context. Several indications can be furnished in all the phases (i.e., mitigation, preparedness, response, recovery) of the flood risk management cycle. In particular, among the different possible contributions, information about flood mapping and monitoring activities can be useful for all the above-mentioned phases [2; 3; 4]. A flood map is prepared during/after a flood occurrence in order to delineate the inundated areas, while flood maps of different times are suitable for monitoring water expansion and regression [2; 3]. Moreover, multi-temporal maps can aid in detecting critical spatial changes in flood hazards and vulnerability over time. These products can be used for flood prone area delineation in order to prevent future floods, providing crucial information to identify appropriate protection measures and strategies for risk mitigation and producing efficient response plans [5]. Once a flood event occurs, emergency planners and rescuers can use inundation maps to detect the most affected areas, then identify evacuation routes and plan the assistance and aid. During the recovery stage, flood maps can support the identification of places for reconstruction and multi-date maps aid in the monitoring of community rebuilding [6]. Microwave and optical-band data have been widely used to produce flooding maps, exploiting the specific advantages of each spectral band and technology used [7; 8]. Microwave sensors enable an all-day (i.e., 24 h) and all-weather detection capability, with spatial resolution ranging from few meters to dozens of kilometers when moving from active to passive technologies, respectively [5]. On the other hand, active sensors (e.g., Synthetic Aperture Radar (SAR)) allow for medium-long temporal frequency (up to five to six days), while passive radiometers have sub-daily temporal resolution [5]. Therefore, SAR data can provide infrequent detailed information about small-scale flooded areas, while passive microwave data could represent the most suitable solution if timely information is required for investigating large-scale flooding events [9]. Optical sensors onboard polar satellites, usually deployed in satellite constellation, can assure the better trade-off among spectral/spatial/temporal resolutions useful for a near real-time and continuous monitoring of flooded areas [10; 11]. Obviously, cloud cover can fully hamper any kind of acquisition in this spectral region, limiting the applicability of this data. Hence, the integration of data acquired by sensors operating at different wavelengths is preferred to avoid such an issue, as well as to make the most of their potential [12]. The Robust Satellite Techniques (RST) [13] is a general multi-temporal satellite data analysis methodology that has already been applied for detecting flooded areas (RST-FLOOD [12; 14]) on Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. Both of these sensors acquire data in the Visible (VIS) and Near Infrared (NIR) regions, allowing for flooded area detection thanks to the particular spectral behavior of water at these wavelengths. Compared to other common land cover and features (like bare or vegetated soils), water generally shows a reflectance (R) in the NIR lower than in the VIS region, with the latter that corresponds for both sensors to the Red (RED) portion of the electromagnetic spectrum.