# Detection of Surface Water and Floods with Multispectral Satellites
## 1 Introduction  
Remote sensing techniques play a crucial role in monitoring water bodies and assessing river dynamics, providing effective support to surface water management. Considering the growing availability of medium-high-resolution and free remote sensing data, both active and passive sensors onboard different satellites are being extensively used for water segmentation and flood mapping. Satellite data are, in fact, of particular interest when observations over wide areas are necessary, for example, to assist with large-scale flood phenomena [1]. Active and passive satellite sensors operate in the microwave segment of the electromagnetic spectrum, while passive satellites include both sensors operating in the microwave spectrum segment and in the portion from the visible to the thermal infrared (optical imagery). Although active microwave sensors provide their own source of illumination, thus being in operation day and night and under all weather conditions, the use of passive multispectral sensors is relatively straightforward [1], and observations are easily interpretable. The availability of several spectral bands with different wavelengths, in fact, makes it possible to derive valuable information from each band and surfaces' spectral signatures, or through direct interpretation of true- and false-color composites. In addition, with simple math algebra, vegetation indices exploit the reflectance characteristics of different objects. Multispectral images have been successfully used for water body and river monitoring, change detection, and water feature extraction [2, 3, 4, 5]. In addition, when cloud cover does notrepresent a major issue, the application of optical remote sensing to maps of flooded areas [6; 7; 8] offers the possibility of quickly and reliably identifying hazardous areas and supporting the implementation of flood coping strategies and response activities. In this context, the use of Unmanned Aerial Systems (UASs) may also provide high-resolution data in the presence of clouds, given the low-altitude range of these systems that allow flying below the cloud layer to be achieved (e.g., [9; 10]). Moreover, the advent of Global Navigation Satellite System (GNSS) and, in particular, the Cyclone GNSS (CYGNSS) constellation, has recently demonstrated the potential of passive microwave instruments to estimate flood inundation and map inland surface water [11; 12; 13; 14; 15; 16]. In fact, CYGNSS benefits from the L-band microwave capabilities of penetrating cloud cover and low-medium vegetation density, thus avoiding scattering problems due to precipitation and clouds [17]. Multispectral satellite data have also been recently proven to be suitable for monitoring the long-term spatio-temporal dynamics of river planform morphology and vegetation coverage, as well as land use/land cover evolution [18; 19; 20; 21]. [PERSON] et al. [18] used vegetation indices derived from multispectral images to assess changes in the wetted river planform morphology and vegetation coverage along Po River Basin (Italy) with a multi-temporal Landsat image analysis (from 1988-2018). Similarly, [PERSON] et al. [19] used Landsat scenes to determine the spatio-temporal trends of vegetation extent and channel position of six different sites along Tagliamento River (Italy). The incorporation of morphological processes into the evaluation of flood hazard has been carried out over both long- [18; 19] and short-term timescales [22] and has shown to be of relevance for flood risk management. In addition, the hydrodynamics characteristics of the flow during a flooding event can modify vegetation coverage and flow resistance through erosion and sediment deposition [23; 24]. In this regard, the information that can be inferred from optical remote sensing data represents a unique opportunity for monitoring planform, vegetation, and land cover changes, improving and supporting flood hazard predictions and modelling.